Airbus has picked European cloud and AI firm Scaleway as its sovereign cloud provider, and plans to transfer dozens of critical applications to its cloud platform over the next two years.

The contract covers workloads requiring strong governance, resilience, and legal protection, according to the aerospace company.

These include business-critical applications across aircraft design, engineering, manufacturing, and enterprise operations.

In keeping these core systems within a European cloud environment, Airbus aims to strengthen the protection of its intellectual property and industrial data while ensuring the continuity required across its global aerospace operations.

Why Airbus chose Scaleway

The deal follows a competitive tender, with several other suppliers in the ring. They were evaluated on the basis of technical capabilities, including advanced cloud services, interoperability and scalability and AI capabilities.

Airbus also took into consideration factors such as security, resilience, service continuity, and seamless integration within its existing multi-cloud ecosystem.

The firm specifically sought legal and governance safeguards, including European jurisdiction, data protection, and protection against non-European extraterritorial legislation.

“Artificial intelligence is redefining how the world's most advanced industries design, manufacture and operate," said Damien Lucas, Scaleway CEO.

"Unlocking its full potential requires digital infrastructure that combines world-class performance with trust, openness and long-term control."

A “significant milestone” for Airbus

Scaleway will provide a sovereign cloud platform that will be fully integrated into Airbus' existing technology ecosystem.

The company said this is designed specifically to evolve alongside the company's engineering and enterprise environments, while keeping operational control and flexibility.

"This collaboration marks a significant milestone in our broader commitment to European digital sovereignty," said Catherine Jestin, executive vice president digital, at Airbus.

"By integrating a trusted, high-performance cloud environment that keeps our critical data assets shielded from foreign extraterritorial laws, we are ensuring that our digital infrastructure keeps pace with our aerospace innovation, while maintaining control and resilience of our industrial operations."

Digital sovereignty in the spotlight

The deal has been a couple of years in the making, and marks a move away from AWS as Airbus, like many organizations, sharpens their focus on digital sovereignty.

Earlier this year, the firm announced plans to deploy Mistral's AI technology across military programs and certified aviation systems.

Research published last month by Civo found that two-thirds of UK businesses were considering ditching US cloud providers, with three-quarters saying digital sovereignty was a strategic priority.

Hyperscalers have accelerated efforts to comply with growing sovereignty requirements. AWS, for example, launched its own European Sovereign Cloud which it claims provides users with a fully independent setup located entirely within the EU.

Microsoft and Google Cloud have also made similar moves over the last 18 months.

European firms are still concerned about the US Cloud Act, however, which allows the US government to request data held in overseas data centers that are owned by US firms.

Earlier this year, the European Commission announced that it had selected Scaleway, along with Post Telecom, StackIT, Proximus, and Mistral for an €180 million contract to enhance European data sovereignty.

"This project proves there are robust alternatives in Europe, able to answer the highest standards," said Octave Klaba, CEO of OVHcloud, one of Scaleway's partners.

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Amazon Web Services (AWS) has announced a series of changes to Amazon OpenSearch aimed at streamlining data log analysis.

A new purpose-built log analytics engine for the service will provide users with marked performance gains and up to 70% lower storage costs, according to the firm.

OpenSearch allows users to search, analyze, and visualize data in real-time, and is typically used for application monitoring, observability, and AI/ML search applications.

The hyperscaler said the update comes in direct response to surging volumes of log data handled by enterprises in 2026, largely due to AI.

Research from AWS shows that log volumes have grown between 30-40% year over year, which is stretching budgets and creating bottlenecks.

Amazon OpenSearch overhaul

As part of the update, Amazon revealed OpenSearch will now store data in the Apache Parquet format. This is a column-oriented data file format designed specifically for more efficient data storage and retrieval purposes.

The service previously relied on inverted indexing. Amazon noted the shift will deliver significant efficiency gains and faster search and retrieval capabilities.

“Apache Calcite parses and optimizes each query, then routes operations to the engine best suited to execute them: Apache DataFusion for analytical operations on columnar data, or Lucene for search predicates,” the company explained in a blog post.

“The two hand off mid-query, so a single query can search log content and aggregate the results without additional roundtrips.”

Amazon noted that OpenSearch now also supports the Piped Processing Language (PPL) and SQL query languages, both of which “execute natively” through the platform.

Amazon eyes optimized log analytics

From a performance perspective, Amazon noted users can expect significant improvements alongside lower costs.

OpenSearch now boasts up to four-times price improvements compared to the existing engine, based on internal benchmarks.

Users can also capitalize on two-times faster analytics queries due to the fact the engine processes data in columnar batches, even across larger data sets. A two-fold improvement on ingestion rates also aims to reduce bottlenecks.

“The optimized engine sustained 1.78 million documents per second at matched concurrency, approximately 2x the throughput of the Lucene baseline, while consuming less CPU,” the hyperscaler explained.

“Both domains ran with zero write rejections. For teams ingesting terabytes per day, the throughput advantage translates to fewer nodes for the same volume, or longer retention on the same infrastructure.”

How to access Amazon OpenSearch

The new log analytics engine is available now for enterprises in AWS regions where OpenSearch Optimized instances are supported, the company noted. Similarly, there will be no additional premium for the optimized engine.

It’s worth noting that the new engine is a setting selected at creation time, meaning users can’t add this to an existing domain or enable it within individual indices or fields within a general-purpose domain.

“To adopt the optimized engine, create a new domain and migrate your ingestion pipelines into it,” the company explained.

“Create a new domain in the Amazon OpenSearch Service console and select Observability as your use case. The optimized engine is enabled by default.”

The in-built console will provide users with a side-by-side comparison of capabilities based on individual needs.

“After your domain is ready, ingest JSON documents through the same Bulk API and client libraries you use today. No changes to your ingestion pipelines or application code are required.”

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Forward deployed engineers (FDEs) could be the key to driving successful AI deployments, as hyperscalers pledge billions to embed specialists within customer teams.

Last week, Microsoft announced plans to invest $2.5 billion in a new division, the Microsoft Frontier Company. The aim here is to deploy upwards of 6,000 AI experts and engineers inside customer organizations.

These specialists will work with enterprises to co-design and build AI systems in a bid to accelerate adoption rates, according to the tech giant.

The announcement came just days after Amazon Web Services (AWS) announced similar plans with a $1 billion investment in its Forward Deployed Engineering segment, once again aimed at bolstering customer AI capabilities.

With the scale of investment – and sheer number of engineers required – for AWS and Microsoft’s push on this front, FDEs are rapidly emerging as the most sought-after technology professionals globally.

Alastair Williamson‑Pound, CTO at Mercator Digital consultancy, told ITPro that the focus on FDEs is an “exceptionally strong signal” that this could become a key growth area for the industry – and a vital pool of talent to drive AI adoption.

“FDEs have become increasingly critical because they sit inside the client, where they can drop barriers, cut through red tape, and get in front of the decision-makers quickly,” he said.

“It’s perhaps why we’re increasingly seeing them considered as a commercial weapon by cloud providers to secure long-term relationships and spend,” he added.

“Another good aspect is that pricing is fixed and based on outcomes rather than time and materials (T&M), which gives customers greater certainty around delivery.”

Williamson‑Pound noted that this aligns with “what companies are after these days”, mainly support in pushing AI adoption projects from pilot to production.

AWS noted that its FDE strategy aims to “compress timelines from months to days” in terms of AI progress, and is “designed so customers are self-sufficient when a deployment ends”.

“Those organizations that are stuck between piloting and deployment can be given that final push by [an] FDE,” he commented.

“The training and documentation they leave behind also tends to give customers that final confidence boost, helping internal teams continue developing and maintaining the system by themselves.”

The rise of forward deployed engineers

Microsoft and AWS are by no means the first big tech providers to put their faith in FDEs. Palantir somewhat pioneered this approach more than a decade ago, and other companies in the AI space have ramped up activities on this front.

As ITPro reported in May, OpenAI launched a new consultancy arm aimed at embedding engineers within customer organizations.

A key distinction here, however, is that the OpenAI Deployment Company is a standalone entity, while both Microsoft and AWS have their own internal divisions dedicated to FDEs.

Crucially, both moves mark the latest attempt by big tech providers to move the needle with regard to enterprise AI adoption, which research shows has been sluggish and at times underwhelming.

Analysis from PwC in January this year found that executives have become increasingly restless when it comes to returns on investment (ROI). Separate research, meanwhile, shows a significant portion of AI projects fail at the first hurdle.

A key factor in adoption project failure often lies in technical capabilities, or lack thereof, according to research from Dynatrace.

With this in mind, providing enterprises with a helping hand throughout the process could provide a much-needed boost for IT leaders.

Initial feedback on Microsoft’s FDE activities show promise on this front, according to Judson Althoff, CEO of Microsoft’s commercial business. In a blog post last week, Althoff claimed that early results have demonstrated “meaningful impact”.

The tech giant embedded engineers within the London Stock Exchange Group (LSEG), for example, helping accelerate AI adoption and providing finance pros with tools to provide answers to complex queries.

Close collaboration between Microsoft’s FDEs and frontline staff at LSEG helped streamline adoption and essentially create a foundation for future improvements, according to Althoff.

“The solution is underpinned by a foundation that is iteratively refined through client feedback and real-time user testing that accelerates each cycle and steadily improves model quality and scope,” he wrote.

Partnerships with Unilever and Novo Nordisk have also delivered marked improvements in terms of AI adoption, Althoff noted.

How FDEs work

FDEs essentially operate like systems integrators (SI), albeit with a few notable distinctions. An SI, for example, is typically an external contractor used to streamline the adoption of individual solutions.

With FDEs, these engineers act as consultants embedded directly within the enterprise. They also offer technical guidance, but it’s the practical support in terms of custom product development that’s a key differentiator. Simply put, they’re building alongside your own engineers.

“Typically, FDEs work in small pods for a fixed period of time, during which they sit within the engineering and technical teams of the client, writing production grade code,” Williamson-Pound explained.

“They leave the customer with a working system in place supported by full documentation, as opposed to an implementation plan.”

JetBrains CEO Kirill Skrygan told ITPro there are a range of benefits to using FDEs for enterprises, and they’re more than just a temporary boost to engineering capabilities.

“FDEs work closely with customers to translate complex organizational challenges into solutions that technology can actually deliver. Doing that well requires more than coding ability," he said.

“It demands architectural expertise, technical leadership, communication skills, and sound business judgment — all qualities that are difficult to automate.”

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Amazon has hit back at EU lawmakers after the European Commission signalled its intent to designate the hyperscaler as a “gatekeeper” under the Digital Markets Act (DMA).

In a statement on 25 June, the Commission noted that Amazon Web Services (AWS) and Microsoft “hold an entrenched and durable position” in the EU cloud computing sector, with both potentially harming competition across the region.

AWS and Microsoft have already been designated as gatekeepers in other business areas, and with cloud computing, lawmakers are equally concerned the duo could stifle competition.

“Their cloud computing services AWS and Azure have achieved significant turnover, and their operational capacity and investments seem to have significantly outpaced those of competitors,” the Commission said.

“They both have vast and entrenched user bases and appear to benefit from lock-in effects and high switching costs, in addition to a large ecosystem.”

The Commission also highlighted competition concerns regarding the influence of AI services on the broader market, noting that both firms’ AI tools have “become a decisive factor in cloud procurement”.

“Whilst AI is significantly increasing the demand for cloud-related services, AWS and Azure appear to retain a large proportion of this increased demand within their respective ecosystems.”

While the Commission noted that this is a “preliminary view”, the statement follows a seven month investigation into the influence of both companies.

If designated under the legislation, lawmakers could impose a series of obligations on both companies, such as the introduction of new interoperability and data portability features.

Teresa Ribera, the EU’s executive vice president for Clean, Just, and Competitive Transition, said both companies will have the opportunity to respond before “final decisions are taken”.

AWS hits back at EU claims

AWS has contested the claims made by the European Commission, with a spokesperson suggesting the preliminary findings “disregard the breadth of cloud services available to European customers”.

The spokesperson added that designation under the legislation could risk “deterring future European investment and innovation”.

“AWS faces healthy competition and customers across Europe have more choice, lower prices, and greater flexibility than ever before,” the spokesperson said.

“The EU already has comprehensive cloud regulation through the Data Act, and adding another heavy layer of overlapping regulation under the DMA undermines European competitiveness and access to cutting-edge information technology.”

AWS said it intends to work closely with the Commission to “reach the right outcome for customers”.

Long-running competition concerns

The move by the Commission comes as relations between US-based tech giants and the EU grow increasingly tense.

European regulators have made repeated attempts to limit the influence of US firms across the region, having been locked in a series of battles with Microsoft over its dominance in the productivity software market.

Geopolitical tensions, however, are adding fuel to the fire on this front, particularly with regard to data sovereignty.

Critics argue that European organizations have become over reliant on US technology services, prompting calls to seek alternative, home-grown options.

Earlier this month, the Commission unveiled the technological sovereignty package, a series of measures aimed at strengthening digital sovereignty capabilities across the EU - spanning areas such as AI, cloud computing, and semiconductor manufacturing.

Speaking at the time, Ursula von der Leyen, president of the European Commission, said the package comes in direct response to concerns about overreliance on foreign technology services.

“We cannot afford to depend on others for the technologies that keep our hospitals running, our energy grids stable, and our services secure,” she said.

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Amazon Web Services (AWS) has confirmed a recent outage that impacted customers was caused by overheating at a North Virginia data center.

The disruption affected one of AWS' six Availability Zones, use1-az4 in the AWS US-EAST-1 region. This is one of the company's most heavily used regions globally.

Notably, the incident hit platforms including cryptocurrency exchange Coinbase, disrupting core exchange functions for more than five hours. Other reported victims include the CME Group trading platform and major gambling company FanDuel.

Coinbase last night warned that some users might experience delayed sends and receives on the Solana network and for ALEO, but said it was working on the issue.

The crypto trading platform has since resumed operations. In a statement, Coinbase said: "All markets have been re-enabled for trading on coinbase.com and in the Coinbase iOS and Android apps. Coinbase customers can log in to trade."

FanDuel, meanwhile, posted a statement on X, saying it was working to troubleshoot the issue. "Our team is aware and investigating the current technical difficulties prohibiting users from accessing our platform," it said.

Overheating behind AWS outage

In an update to customers, AWS attributed the cause of the outage to overheating. The hyperscaler is yet to confirm how the overheating occurred.

"We have experienced an increase in temperatures within a single data center, which in some cases has caused impairments for instances in the Availability Zone," AWS said in a status report.

"EC2 instances and EBS volumes hosted on impacted hardware are affected by the loss of power during the thermal event."

In its latest update, AWS said it had shifted traffic away from the impacted zone. The hyperscaler said it was still carrying out mitigation efforts.

These are taking longer than expected to bring additional cooling system capacity online and recover the remaining affected infrastructure safely and in a controlled manner.

AWS warned some customers will continue to see their affected EC2 instances and EBS volumes as impaired until it can achieve full recovery. It said it currently didn't have an ETA for this.

What services are back online?

A number of services are back online following the outage, according to the hyperscaler. This includes:

• AWS IoT Core
• AWS NAT Gateway
• Amazon Elastic Kubernetes Service
• Amazon Elastic Load Balancing
• Amazon Redshift

Some services are still impacted at time of writing, including:

• Amazon ElastiCache
• Amazon Managed Streaming for Apache Kafka
• Amazon OpenSearch Service
• Amazon SageMaker

Yet another AWS outage

It's not the first time that a major AWS outage has caused chaos. Last year, hundreds of apps and websites including Slack, Zoom, Coinbase, Snapchat, and Signal were taken down in a global outage.

Banking applications including Lloyds and Halifax also saw customers unable to access services. On that occasion, AWS attributed the outage to a DNS issue.

The incident highlights the extent to which major websites and apps are dependent on just a few tech giants.

In 2024, for example, issues with CrowdStrike saw hospitals, banks, and airports in Australia, New Zealand, India, Japan, the US, Germany, and the UK seriously affected.

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AWS CEO Matt Garman has a bullish outlook on the future of the SaaS industry despite continued claims of a looming “SaaSpocalypse”.

Speaking during a recent interview with Fortune, the AWS chief dispelled worries that the SaaS industry faces an existential threat in the form of agentic AI - so much so that the company is making its own foray into the space.

Last week, the company unveiled sweeping changes to Amazon Quick, a desktop AI assistant which acts as a single information source connecting the disparate applications, tools, and data used by workers in their daily lives.

AWS is framing the revamped platform as a boon for personal productivity, noting in an announcement that it is “continuously running in the background” monitoring desktop activities and “surfacing what needs attention”.

As the company explained in a blog post, this could include information contained in Slack threads, for example, or important unread emails and file uploads.

AWS’ foray into this domain was inspired by the fact that “so many applications are getting done with AI and agents”, according to Garman, who described Amazon Quick as a “huge business opportunity”.

“We think that there is just such a massive change out there that everything is going to be remade,” Garman told Fortune. “I don’t think personal productivity has really been remade for the last 30 years,”

“There are going to be millions of successful applications that people use,” he added. “Obviously the vast, vast majority of them will not be built by Amazon or AWS, but we think there are a handful of them that we can build that will be pretty successful and that customers will like.”

Garman’s comments suggest that, far from heralding the doom of traditional software, AI will ultimately act as an enabler to deliver more intuitive workplace tools.

This isn’t the first time Garman has poured cold water on threats of a pending SaaSpocalypse. As ITPro reported in February this year, Garman said while there is “huge disruption” ahead for the SaaS industry, “much of the fear is overblown”.

Garman’s comments came at the peak of software stock sell-offs sparked by the launch of a handful of powerful new AI solutions, with Anthropic’s Claude Cowork tool ranked chief among these.

The workplace productivity tool gives users sector-specific plugins designed to automate tasks across a wide range of areas, spanning legal, marketing, sales, and data analytics.

That launch spooked software investors due to fears the technology could ultimately render dedicated SaaS solutions in these domains obsolete.

AI transforming software

Despite a positive outlook, Garman told CNBC in February that the advent of generative AI, and more recently AI agents, will transform how software is built and sold.

Long-term, that could create a more challenging market for providers, who will be operating in an increasingly competitive marketplace.

“AI is absolutely a disruptive force that’s going to change how software is consumed and how it’s built,” he said.

“The SaaS providers and the larger players of today have an inside track to winning that business. Now, they have to innovate, just like the rest of the world. They can’t stand still. If they stand still, they’re absolutely going to be disrupted.”

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Hyperscaler cloud revenues are still surging, according to recent earnings reports, but questions still remain about how much longer they can continue investing massive sums in AI infrastructure.

Alphabet, AWS, Meta, and Microsoft have all posted positive results this quarter with overall revenue in the hundreds of billions of dollars, helped in part by booming demand for data center capacity amid the AI roll-out.

However, analysts have questioned whether spending on AI is sustainable and will deliver a return on investment (ROI).

The current estimate is for tech's leading companies to invest $600 billion in infrastructure to power AI this year alone, with some tech giants already upping their predicted spends as part of their quarterly results.

"The public cloud platform earnings numbers are big as usual — but the capital investment to achieve them are getting big faster," said Forrester’s principal analyst Lee Sustar. "That's why questions will persist about the sustainability of hyperscaler AI data center buildouts."

"Together, the public cloud revenue numbers and the capital expense figures will raise questions about the sustainability of the AI boom," he added. "But with the potential payoff of AI leadership seemingly so high, the companies continue to make those bets, forcing investors and customers alike to assess how their interests are impacted."

According to LSEG data shared by Reuters, Amazon stock is up 13%, Alphabet's is up just shy of 12%, and Meta is up 3% – but Microsoft has slid 12%.

Alphabet's cloud success

Google-owner Alphabet saw overall revenue leap 22% to $109.9 billion for its first quarter, topping estimates, with income climbing to $39.7 billion.

Google Cloud climbed 63% to $20 billion, marking the best growth rate for the cloud company in more than six years, though still below Alphabet's other revenue sources, including Services at $89.6 billion and Search at $60.3 billion.

Google Cloud income climbed from $2.2 billion in the first quarter in 2025 to $6.6 billion this year, underlining significant growth over the last 12 months. Sustar said the figures show the cloud division "can significantly contribute to the wider Alphabet portfolio after years of big operating losses".

In an investor call, Sundar Pichai said that capacity constraints prevented even higher growth, with Google Cloud's backlog doubling to $460 billion.

"Our enterprise AI solutions have become our primary growth driver for cloud for the first time," he said.

In a statement, Pichai added: "Our first-party models, like Gemini, are now processing more than 16 billion tokens per minute via direct API use by our customers, up 60% from last quarter. It’s really exciting to see how our AI investments are delivering value for our users, customers and business."

CFO Anat Ashkenazi said Google would increase its capital expenditure forecast by $5 billion to somewhere between $180 billion and 190 billion. Last year, the tech giant’s capital expenditure reached $91.45 billion, with much of this focused on AI-related spending.

That huge cloud backlog and leap in revenue suggests that Google's capex spending isn't wildly out of place, Thomas Monteiro, a senior analyst at Investing.com, told Reuters.

"Perhaps even more importantly than Alphabet's massive cloud growth pace is the broader justification that the $180 billion capex plan — that surprised the market last quarter — is well within the company’s spending power, considering the durability and quality of the revenue curve shown today," he said.

But concerns remain, according to Sustar, who pointed to the quarterly figures. He noted that "the capital expenditure of $35.7 billion — which Alphabet attributes largely to AI — is much bigger" than the $20 billion in quarterly revenue from the cloud unit.

AWS leaps ahead, but not quite as much

Amazon's overall revenue climbed 17% to $181.5 billion in the first quarter, while revenue at Amazon Web Services (AWS) climbed 28% to $37.6 billion in the first quarter. AWS operating income climbed to $14.2 billion from $11.5 billion in the same quarter last year.

While AWS’ revenue growth rate wasn't as high as Google Cloud's, it's still significant coming from the market leader. Andy Jassy, CEO of Amazon, said in a statement that it was AWS' "fastest growth in 15 quarters."

Jesse Cohen, senior analyst at Investing.com, said that the "reacceleration" in AWS sales was a positive sign, adding that the hyperscaler’s customer base is "fully embracing new workloads, especially in AI."

Amazon has projected $200 billion in capex this year, with $44.2 billion spent in this quarter.

"AWS bagged $37.59 billion in revenue in the first quarter but data center buildouts accounted for a big part of the $44.2 billion capital investment in the same period, even though AWS had an operating income of $14.2 billion," said Sustar.

"That puts pressure on AWS to keep up its historic role of keeping Amazon as a whole in the black from quarter to quarter.

Social media props up Meta

Facebook owner Meta posted revenue of $56.3 billion, up 33% from $42.3 billion the same quarter last year, with income of $22.8 billion, up about 30%.

Meta raised its expected capital expenditure forecast from between $115 billion-$135 billion to $125 billion-$145 billion, which sent stocks sliding 6%.

In a statement, Meta said: "This reflects our expectations for higher component pricing this year and, to a lesser extent, additional data center costs to support future year capacity."

In a conference call, Meta's chief financial officer Susan Li said that such spending was necessary to catch up, as Meta has previously "underestimated our compute needs".

CEO Mark Zuckerberg said it was unclear how the increased spending would pay off.

"I don't think we have a very precise plan for exactly how each product is going to scale or anything like that," he said, per reports from the BBC.

"But I think we have a sense of the shape of where these things should be... and I'm quite comfortable that the lab we're building is on track to be a leading lab in the world."

In the meantime, social media continues to pay Meta's bills.

“The irony is that Meta’s future‑facing AI ambitions are being underwritten almost entirely by the company’s legacy business: advertising inside social media apps," said Forrester’s VP research director Mike Proulx. "There’s no material AI revenue yet. Reality Labs remains a loss. Muse Spark has momentum, but not monetization."

“The question is whether Meta’s core can continue to act as a cash cow while the company reduces headcount and diverts focus toward AI," he added.

"If Meta’s ad engine slows, the market’s margin for patience shrinks fast. Meta’s slight dip in daily active users is already beginning to raise eyebrows. Q2 will tell us if it’s really just a blip or the start of a trend."

Microsoft says margins are strong

Microsoft said its quarterly revenue was up 18% to $82.9 billion, with operating income up 20% to $31.8 billion, though AI spending helped cash flow slip by $6 billion to $15.8 billion.

"We are focused on delivering cloud and AI infrastructure and solutions that empower every business to eval-max their outcomes in the agentic computing era," said Satya Nadella, Microsoft CEO.

"Our AI business surpassed an annual revenue run rate of $37 billion, up 123% year-over-year."

Microsoft Cloud revenue climbed 29% to $54.5 billion, with Azure and other cloud services up 40%.

"For its part, Microsoft claims an upswing of 40% growth in Azure and $54.5 billion in revenue for the wider Microsoft Cloud category," said Forrester's Sustar.

"The company does not break out Azure operating revenue, but with its AI-focused capital investments of $31.9 billion, the cloud revenue is clearly expensive to obtain."

Microsoft's spending on AI has raised concerns, but the company pushed back saying income remains strong. "The margins have been and remain better in our AI business than when we were in our cloud transition," said CFO Amy Hood.

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AI adoption is ramping up at a rapid pace globally, of that there’s no doubt. But there’s more to successful adoption than just buying shiny new tools and finding yourself in a productivity paradise.

While that might seem like stating the obvious, it’s still a problem a significant portion of enterprises find themselves facing – and there’s little sign that it will improve any time soon.

Research from Amazon Web Services (AWS), released to coincide with its annual AWS Summit London this week, showed progress on the adoption front compared to last year.

The study, which focuses primarily on UK-based firms, has some positive takeaways, with British enterprises outpacing adoption compared to their European counterparts.

Clearcut gains with the technology are also being made, according to AWS, with workers now basking in the productivity and efficiency gains promised by it and other big tech providers.

Speaking during the keynote address at the summit this week, Alison Kay, AWS’ VP and managing director for UK&I, waxed lyrical about the benefits of AI for customers and the company itself.

Developers are working at lightning speed delivering projects previously deemed insurmountable while customers such as Motorway are recording the same gains.

“We’re living through just an incredible moment in history, a breakthrough moment in technology advancement,” Kay told attendees.

“And what makes this moment so exciting is that the things that are being built, they almost defy belief. They almost feel like magic.”

AI might look and feel like magic, but IT leaders aren't living in a fantasy land – they're facing the harsh reality of how difficult AI implementation can be. They've got the trendy new tools and staff are loving them, yet they’re not seeing any significant progress on a business-wide level.

AI pilot purgatory persists

AWS’ study found the actual use of AI in the enterprise is still very basic, with employees using the technology to summarize documents or answer basic questions using chatbots.

That’s so 2023, but at least they’re enjoying it. More than two-thirds (68%) of employees are reporting marked productivity and efficiency improvements.

AWS’ findings align closely with similar research from Accenture earlier this month, which pointed toward “localized” gains whereby individual workers are seeing gains, but the companies themselves are still struggling.

So what’s stopping enterprises from making the leap toward more “advanced” AI uses? The same old problems many businesses have with digital transformation projects.

Skills and expertise, legacy systems, and outdated infrastructure are stifling progress.

It’s been a common recurring theme with AI adoption over the last three and a half years and one that must have IT leaders bashing their heads off the wall over.

Research from Google Cloud in August 2024 warned British firms in particular were stuck in a “pilot purgatory”.

At that point, only two-in-five firms had pushed generative AI projects to production and were facing a “substantial hurdle” in scaling the technology internally - an issue the aforementioned Accenture study found is still a key problem.

The situation is even worse with agentic AI, with a January study from Dynatrace showing that half of agent adoption schemes are wallowing in the proof of concept (PoC) stage.

Phil Le-Brun, executive in residence at AWS, told ITPro that a “lack of imagination” is often a key factor in this inability to scale AI adoption and reach more advanced uses.

An increasing volume of research also points toward the frantic nature of the generative AI boom as a key factor behind failed adoption efforts.

Research from Forrester in early April suggested that a “lack of understanding” when it comes to AI, combined with the rabid appetite to invest in the technology, has resulted in a slap-dash approach to AI innovation.

Executives have been caught up in the hype, and all they can see are dollar signs and the marketing materials promising huge productivity improvements.

But Forrester noted those who take a more conservative, “deliberate” approach to AI adoption have recorded far better results – and a key factor here is focusing on creating value for customers rather than productivity and cost reductions.

Speaking to ITPro, Le-Brun touched on this customer-centric approach with AI, noting that some of the more agile companies it engages with, such as startups, are making great strides in this regard.

Simply put, keep an eye on the productivity and cost benefits, but sharpen your focus on actually delivering for customers.

“The application of AI to fundamentally rethink how you’re delivering a product or service to the customer would be an example of advanced AI,” he said. “That’s where we see startups doing some amazing things.”

“They’re willing to really dive into what it is the customer wants, and how can we apply this new technology to change, rather than for large enterprises - it’s much harder because they have a lot of established processes.”

A long road ahead

The current pace of progress in pushing from pilots and basic use-cases toward more advanced AI uses highlights the sorry state of affairs for many businesses - and there’s still a long road ahead. A very long one, if AWS findings are to be taken at face value.

Just 24% of firms have reached an advanced AI phase in 2026, according to AWS, marking just a single percentage increase compared to last year. If things continue at this pace of progress, it’ll be 2102 before all AI adopters in the UK reach an advanced stage.

As Le-Brun told ITPro, businesses will be in a good position “by the end of the century”.

AI adoption continues to gather pace across the UK, but many organizations are struggling to scale the technology – and it’s potentially leaving billions in economic gains on the table.

That’s according to new research from Amazon Web Services (AWS), which found the estimated productivity gains of broader AI adoption could unlock £35 billion in economic growth by 2030.

The appetite for AI tools across the country has grown over the last year, AWS found, with nearly two-thirds (64%) of organizations now using the technology – an increase compared to 52% last year

AWS noted that the benefits of AI are becoming clearer for enterprises, with 68% reporting marked productivity gains. Nearly three-quarters (72%) said they expect AI to increase business growth in the year ahead, while 79% said the technology is accelerating innovation.

While these are all positive takeaways from the report, Phil Le-Brun, executive in residence at AWS, warned that they mask a recurring problem with enterprise AI integration – it’s largely for basic tasks.

Most organizations are using the technology to speed up simple activities, such as summarizing documents or answering queries using chatbots. More advanced AI uses, however, haven’t yet materialized.

Indeed, just 24% of adopters have reached an advanced stage, which, by AWS’ definition, means AI forms a “part of core processes and decision-making”.

Those stats mark just a one percent increase compared to the year prior, highlighting a painfully slow rate of improvement.

Speaking to ITPro at AWS Summit London, Le-Brun noted that a key factor here is a “lack of imagination in organizations” – these simple improvements appear to be boosting productivity, but it doesn’t paint the full picture.

“We have organizations today designed to be efficient for the last 150 years,” he told ITPro. “So how do we increase efficiency, which naturally turns into productivity (or not)?”

While a lack of imagination is stifling innovation, Le-Brun noted that it’s extremely difficult to “fundamentally rethink how your business operates in the first place”.

The findings by AWS align with a recent study from Accenture, which highlighted a trend of “localized” AI adoption, with broader business-wide benefits not being realized.

The consultancy noted that while workers are using the technology to automate basic tasks, enterprises are failing to redesign “systems and workflows” to accommodate the technology.

Only one-quarter of employees said that a major process in their team had been “restructured around AI”, for example.

AWS’ study specifically highlighted the importance of redesigning workflows around AI, noting that this helps accelerate decision-making and supports the development of new products and services.

Those that make the shift from basic to advanced uses, AWS noted, report average efficiency gains of 68% compared to 40% of those still stagnating in basic use-cases.

Skills a key barrier to AI growth

Progress on this front is being stunted in part by a lack of relevant internal expertise, according to AWS. Indeed, nearly half (49%) of respondents cited AI and digital skills-related shortages as their main challenge.

Concerningly, this marks an increase compared to the 46% who cited this as a key issue last year. The company noted that as AI adoption rates accelerate, the situation is becoming worse.

Just 17% of organizations said they have a “strong” AI skillset at present, and 84% expect AI-related skills to grow in importance over the next five years.

The situation has reached such an extent that organisations are now willing to pay an average 41% salary premium for top AI talent, AWS found.

High stakes for the UK economy

This inability to scale AI or shift toward more advanced uses has wide-reaching implications, AWS found. Businesses themselves risk falling behind more agile competitors, but the broader economic impact on the UK is huge.

The £35 billion figure touted by the hyperscaler represents roughly the economic output of the city of Manchester. Given the current rates of improvement, Le-Brun said, “By the end of the century, we’ll be in a good position”.

Progress compared to other nations paints the UK’s current situation in a more positive light, however. With 64% of UK organizations now using AI, and with a yearly growth rate of 23%, it stands 10% above the European average.

That’s the equivalent of a business adopting AI every 40 seconds compared to an average adoption rate of one every 60 seconds on the continent.

Similarly, positive moves by the public sector with AI adoption should also be a point of pride for the UK, Le-Brun told ITPro.

Simply put, progress may be slow, but some movement is better than none at all.

“There is a massive opportunity, [and] the UK in particular is an ideal place to capitalize on this,” he said. “We’re showing a faster rate of adoption and a more advanced use of AI than most European countries.”

“That’s something [to be] very proud of,” Le-Brun added. “We just need to go faster.”

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Software developers at Amazon Web Services (AWS) are recording marked efficiency gains with AI tools, according to the company’s UK chief.

Speaking at the AWS Summit London, Alison Kay, VP and managing director for the UK & Ireland, told attendees that developers are relying heavily on its own Kiro coding tool to speed up processes.

Indeed, devs at the firm have been able to successfully deliver projects that previously would have been extensive in a far more efficient manner.

“At AWS we needed to completely rebuild the inference engine behind Bedrock from scratch,” she explained. “Now, if you'd asked me two years ago what that would’ve taken, I would’ve said ‘40 engineers, 12 months, and a whole lot of coffee’.”

Using AI, Kay noted this rebuild project was completed by six engineers in just 76 days.

“They weren’t working alone,” she added. “They were working alongside Kiro agents that wrote code, tested it, found bugs, fixed them, and deployed it around the clock. While the engineers slept, the agents kept building.”

AWS announced the launch of Kiro in mid-2025, and since launch has received a series of updates. At the company’s annual re:Invent conference in December 2025, the coding service received a big upgrade with new agentic capabilities.

As ITPro reported at the time, the Kiro Autonomous agent maintains “persistent context” across the development lifecycle, essentially lingering in the background and supporting human developers.

Talking up AI

Much like its competitors, AWS has been keen to emphasize both the capabilities of its own AI tools, but also how staff are using them across the company.

Speaking during a podcast appearance last year, CEO Matt Garman noted around 80% of developers at the firm were using AI “in some way” on a daily basis.

Notably, Microsoft and Google both touted the increasing use of AI-generated source code, which, at the time, Garman suggested was a “silly metric” by which to measure internal AI successes.

“There might be bad code, by the way. Measuring lines of code is never actually the best metric. Oftentimes, fewer lines of code is way better than more lines, so I’m never really sure why that’s the exciting metric that people like to brag about.”

Increased AI use at AWS isn’t restricted to software development, either. Speaking to ITPro at AWS re:Invent in December last year, CISO Amy Herzog revealed security practitioners have ramped up use of agentic AI tools in areas such as CVE attribution and threat detection.

Indeed, Herzog revealed security teams had recorded a “500% increase” in helping practitioners “piece together” information on emerging threats and vulnerabilities.

So far, Herzog noted there has been a “500% increase” in the company’s ability to “piece together information” for security teams on this front.

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Microsoft and Amazon have announced changes to cloud practices following a lengthy probe by the Competitions and Markets Authority (CMA), provoking mixed reactions from industry stakeholders.

While the regulator concluded in 2025 that both hold “positions of significant market power”, neither were given a Strategic Market Status (SMS) designation.

This is a label given to organizations that hold a disproportionate influence on markets and allows the CMA to impose “conduct requirements or introduce pro-competition interventions” under the Digital Markets, Competition, and Consumer Act (DMCC).

In the wake of the investigation, both hyperscalers have agreed to take action on key issues such as cloud egress fees, interoperability, and the ability of customers to switch providers.

In a statement, the CMA said this will “support greater choice” for businesses and public sector organizations across the country.

“These changes will reduce expense and effort for UK customers when using more than one cloud provider,” the regulator said.

As part of the announcement, the CMA revealed plans to launch a separate SMS probe into Microsoft’s software practices due to competition concerns. Expected to begin in May, the investigation will see the regulator examine the firm’s business software licensing practices.

In a blog post reacting to the cloud market decision, Microsoft president Brad Smith said the company is committed to working “quickly and constructively” to address the CMA’s concerns.

“We appreciate the opportunity we have had for direct and constructive conversations with the CMA and its staff and look forward to an ongoing dialogue in relation to relevant cloud issues in the future,” he wrote.

Amazon said it is working toward a “new UK Addendum that formalizes our commitment to customer choice through clear, comprehensive rights around multicloud adoption, data portability, and switching processes”.

Industry stakeholders aren’t sold

Experts have mixed reactions to Amazon and Microsoft’s moves to address issues flagged in the cloud market probe.

CCIA senior director Matthew Sinclair said the decision will avoid “overly broad and prescriptive interventions” that could harm UK cloud innovation.

“The regulator can focus its efforts on action to address specific issues, particularly restrictive software licensing terms for legacy software, which are costing UK users a fortune,” Sinclair noted.

Nicky Stewart, senior advisor at the Open Cloud Coalition, urged the regulator to take “swift action” against both organizations if they fail to meet commitments on egress fees and interoperability.

“Slow progress on these issues continues to hamper growth, innovation, and resilience in the UK cloud marketplace,” Stewart commented. “Decisive action will set a benchmark for competition authorities across Europe and beyond.”

In contrast, Mark Boost, CEO at UK-based cloud provider Civo, questioned whether the voluntary actions by both firms will deliver changes called for by industry stakeholders.

“Voluntary arrangements made with parties outside of the SMS framework will not provide real impact, and by delaying its final decision regarding Microsoft and excluding AWS altogether, there is a risk for CMA to unnecessarily prolong uncertainty and miss an opportunity to future-proof the UK’s digital infrastructure,” he said.

Boost added that the CMA’s decision does not provide “adequate solutions” to solve lingering concerns over the dominance of both hyperscalers in the UK market. Last year, the regulator found Amazon and Microsoft controlled a share of the market ranging between 30-40%.

“There needs to be a fair digital market in which domestic innovation is encouraged, alongside continuing to help build opportunities for international collaboration and trade,” he said.

“If the CMA is serious about delivering on this, it will need to adopt an integrated approach as opposed to only partially regulating these hyperscalers. If the same standards are not applied to both parties, the UK will jeopardize its objectives related to digital sovereignty and economic stability.”

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COBOL experts aren’t at risk of losing out to generative AI, even as the technology helps noticeably speed up mainframe modernization, according to an AWS executive.

Asa Kalavade, VP of AWS Transform, told ITPro that AI holds immense potential for workload modernization – but that it can’t and shouldn’t replace experts in the field.

AWS Transform is the firm’s agentic AI modernization platform, intended to speed up the translation and update process for legacy code, infrastructure, and applications.

First unveiled in May 2025 it was expanded upon at AWS re:Invent, and is a core offering for firms looking to modernize at scale.

AWS Transform for Mainframe is specifically designed for AI translation of mainframe codebases in languages such as COBOL, JCL, and BMS, and systems including CICS, DB2, and VSAM, into a modern language such as Java.

Generative AI has made it easier than ever to translate code from one language to another. However, at an enterprise level leaders need to know that this process won’t introduce logic errors or otherwise make workloads unpredictable or harder to audit.

Translating COBOL is no mean feat

When it comes to translating COBOL, AWS Transform gets around this by extracting system management facility (SMF) records, logs generated in IBM z/OS mainframes.

These contain details on the correct steps for implementation, execution, and workload routines to ensure that code generated by Transform retains the integrity of the original code.

Kalavade added that using AWS Transform, organizations can compare the efficiency of migrated workloads against existing P90 and P95 records to confirm no loss in performance.

AI within the tool can also be used to generate test cases to stress test the migrated mainframe code. However, Kalavade stressed that human experts are still needed at all stages of the modernization process.

For example, she explained that human experts with familiarity of mainframe systems are needed to help pressure test cloud systems post-migration.

In February, shares in firms such as IBM plummeted after Anthropic claimed its latest Claude release could translate COBOL into modern programming languages.

“You do need those COBOL experts, because how do you validate this code? And the point is, the COBOL expertise is declining.

“So in fact, we find in our team some of our unicorns are those that have come from years of doing COBOL, but now they know how to translate and they can verify so that whole human reinforcement that is needed to verify that the output is matching the input that is required.”

Kalavade added that COBOL is not just one language and that experts are still needed for proper understanding and handling of code translation.

“There are so many variants of COBOL, there are so many languages within a mainframe application, whether it's PL/I [or] Easytrieve, so you need those experts to even define what these transformations are.”

AWS has benefited in modernization efforts from its 2021 acquisition of Blu Age, a French company that had over 20 years of experience in like-for-like code translation.

“The core asset that came out of that understanding was to build the control flow graph of that old application, and that is what gives us the ability to combine the old and the new,” Kalavade explained.

IBM z/OS mainframes are still widely used across financial services, government, and healthcare among other critical industries, so it’s important that any migrated workloads are done.

“Our mainframe workloads have got the most signal where customers who thought they could previously never modernize these applications are now really accelerating some of this modernization.

Kalavade pointed to customers like BMW and Brazil-based Itaú bank as customers that are already leaning heavily into AWS’ mainframe modernization tools.

“What was most exciting to me was, we launched Transform back in May as GA and at re:Invent we had four or five of these mainframe customers providing references and experiences,” Kalavade noted.

“One might wonder, why is it so exciting? These projects typically took two, three, five years, so even if it's a start, having customers finish these projects within at least some workloads – it's not like they finished their entire mainframe project – has been very rewarding to see.”

Not every workload will move right to the cloud, Kalavade added, and IBM is a strong AWS partner for on premises workload management.

VMware licence spurring cloud migration

A noticeable factor in cloud migration has been the VMware licence changes, which have spurred 86% of customers to reduce their VMware footprint.

While one option is to go cloud native via a lift and shift process from VMware workloads to AWS EC2, others are finding the move a laborious undertaking involving unpicking numerous interdependencies.

Kalavade told ITPro that VMware licences have not only motivated customers to move to the cloud, but also to use this shift as an opportunity to modernize and adopt containers. AWS is currently beta-testing a dedicated agent for containerization, while AWS Transform can handle the code contained in migrating VMs.

“Those VMs often will have a database that is on that VM, or you’ll have a Windows Server, so some customers will look to move those VMs, and then once they're in the cloud then they might want to modernize the database from SQL Server to [Amazon Aurora PostgreSQL], or to go from .NET Framework to Core.”

AWS is working to make the entire process easier for customers through integrated AI agents. For example, Kalavade described how administrators can use a chat window to ask questions about code modernization plans directly within AWS Transform, which can be connected with a coding agent to generate code directly from a user’s natural language inputs.

“What we see could be happening is over time, as these coding agents become more autonomous, once you've defined the spec, then the agent can go and do more and more long-running tasks to generate the code, create the test cases, and validate which is what the LLMs are starting to get really good at.

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Amazon Simple Storage Service (S3) is 20 years old, and while simplicity was, as the name suggests, the original inspiration, it has since become a sprawling platform.

But that doesn’t mean simplicity and ease of use aren’t still core tenets of the storage service, according to Andy Warfield, vice president and distinguished engineer at Amazon Web Services (AWS).

Speaking to ITPro ahead of the anniversary, Warfield said simplicity is still the “singular most important aspect” of S3. When it launched in 2006, a brief blog post outlined the core goal: “Amazon S3 is the storage for the internet”.

With a simple Representational State Transfer (REST) interface, users could PUT (store objects) and GET (retrieve them later) with relative ease. Warfield told ITPro that “parking the service” behind this architecture made it simple and easy for customers to adopt.

“At the time S3 launched in 2006, a lot of the verbs that we were using and a lot of the ways that the team approached presenting storage [were] actually really guided by the existing HTTP verbs,” he explained. So things like the GET and PUT support.”

“It made it incredibly easy to adopt. I think one thing that kind of taught the team, and it’s been true through the lifetime of S3, is that we do best when we focus on the customer, which you hear from us all the time, but on delivering for the customer in a way that is as simple as possible to consume so folks don’t have to do extra work.“

An explosion of growth for Amazon S3

To say Amazon S3’s growth over the last two decades would be a gross understatement. When it launched in 2006, S3 offered a total of one petabyte of storage capacity, spread across several hundred storage nodes in three data centers – it also had a maximum object limit of 5GB.

Compare that to 2026, and the numbers are jarring. As ITPro reported at AWS re:Invent 2025, the service now offers a maximum object size of 50TB, marking a ten-fold increase on the original limit.

Additional figures detailed by the company emphasize the sheer scale of S3 compared to its early days. Today it boasts:

• 500 trillion stored objects globally
• 200 million data requests per second
• 123 Availability Zones worldwide
• 39 AWS Regions

S3’s rapid-fire growth coincided with – and benefited from – an enterprise data explosion during the late 2000s and early 2010s. Indeed, Warfield notes that in 2006, you would have been “hard pressed to find something that you wanted to put in an object that was larger than 5GB”.

But with growing camera resolutions as a simple example, the rapid accumulation of enterprise data, and the formation of data lakes, demand surged. In 2026, Warfield admits the numbers are still rather mind-boggling.

“One that stands out to me is that the service processes over a quadrillion requests every year,” he said.

“We have tens of thousands of customers who, each individually, have objects that are spread over more than 10 million hard drives,” Warfield added, noting that the prospect of an individual enterprise building a storage setup of that scale as a “wild thing to think about”.

Underpinning enterprise innovation

Amazon S3 quickly moved beyond being a simple object storage service. Indeed, it became the underpinning foundation and enabler of customer data innovation.

The service helped kickstart the creation and subsequent growth of data lakes, and today, more than one million of these are stored on AWS. Warfield described this as a “structural aspect of why S3 is successful”.

Enabling enterprises to host data in a single source and all in one place helped break down long-running siloes that many had battled for years. It created a “shared foundation” for data.

“The data gives them this incredible flexibility and velocity to move quickly. And the data ends up being non-zero sum in terms of future value,” he said, reflecting on discussions with one particular customer.

“They often find that data they built for one system allows them to move into another opportunity.”

S3 in the age of AI

S3’s flexibility in adapting to customer demands over the last 2o years has been a key factor in its longevity and success - along with that of the company at large. AWS still boasts a large hyperscale market share o alongside Google Cloud and Microsoft Azure, for example.

With the advent of generative AI raising the stakes for big tech providers, the storage service is once again evolving to accommodate skyrocketing storage demands.

Indeed, the company is heavily focused on positioning S3 as the critical foundation for AI workloads. At AWS re:Invent in December, the company officially cut the ribbon on S3 Vectors, which has generated significant excitement across the company.

When it comes to AI, vector search is used to identify similarities between specific data points. At the time, the company described vectors as a "numerical representation of unstructured data created from embedding models".

Uploading, storing, and querying vectors is costly, though which is something this particular service aims to remedy. The company claims it can reduce costs on this front by up to 90%.

“The thing that we really wanted to do with S3 Vectors was to get a vector indexing service that had the simplicity and elasticity of S3 that you could just pick it up and use it with just ten vectors, but scale to billion and trillions of vectors and pay something that was closer to storage costs because it was anchored on hard drives,” Warfield explained.

“We’ve seen incredible growth on it.”

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Amazon’s strategic partnership with OpenAI is a win-win for the duo, according to analysts, as the companies forge closer ties on infrastructure and AI development.

The pair announced a multi-year deal last week that will see Amazon invest $50 billion in the AI developer, building on a £38 billion pledge made in November last year.

As part of the deal, OpenAI will lean heavily on AWS infrastructure, committing to deploy 2 gigawatts of Trainium chips for its new enterprise-focused platform, Frontier. AWS will also serve as the exclusive third-party cloud distribution provider for Frontier.

OpenAI’s Frontier platform allows businesses to build and deploy AI applications and agents. As ITPro reported last month, the platform is a key focus for the firm as it looks to ramp up enterprise adoption rates.

The company has since brought in consultancies to act as systems integrators for customers to streamline adoption processes.

Elsewhere, the deal will see the duo create a ‘Stateful Runtime Environment’ through Amazon Bedrock, again with a focus on development and deployment. This will allow AWS customers to build generative AI apps and agents at “production scale”

“Stateful developer environments are the next generation of how frontier models will be used, seamlessly enabling models to access elements like compute, memory, and identity,” AWS said in a statement last week.

“A Stateful Runtime Environment allows developers to keep context, remember prior work, work across software tools and data sources, and access compute.”

Mutually beneficial ties

From Amazon’s perspective, the partnership allows the hyperscaler to continue pushing ahead with its “go build it” approach to AI, according to Lee Sustar, principal analyst at Forrester.

Amazon’s AI strategy has centered largely around its Amazon Bedrock service, which allows customers to build and deploy AI solutions in a similar vein to OpenAI’s Frontier. It has since built on this with the launch of AgentCore, enabling enterprises to create custom agents.

With OpenAI’s sharpened focus on enterprise adoption, this represents a mutually beneficial partnership aimed at both pushing broader enterprise uptake while helping AWS capitalize on lucrative infrastructure deals signed by competitors.

“The OpenAI-AWS deal is the latest example of the hyperscalers’ complicated dance with the big AI players,” Sustar said. “AWS has doubled down on its traditional “go build it” approach with AI, which means it must have partnerships like this.”

“Notably, it gives AWS exclusive third-party cloud distribution with OpenAI Frontier, potentially giving AWS a competitor to Azure OpenAI Services as well as Google Cloud offerings,” he added.

Diversification continues

OpenAI’s Trainium commitment marks a huge win for AWS, Sustar noted, allowing the company to “build a rival GPU ecosystem alternative to Nvidia”.

Like Google, Amazon has invested heavily in its in-house chip capabilities over the last five years in a bid to reduce reliance on Nvidia hardware.

The move also highlights OpenAI’s continued efforts to diversify infrastructure and hardware options.

OpenAI’s once-exclusive ties with Microsoft saw it lean heavily on Azure infrastructure, but over the last year the company has secured a slew of agreements with industry stakeholders on compute capacity and chips.

The company signed a landmark deal with Oracle on compute capacity, for example, while October saw it sign a multi-billion dollar deal with AMD to use six gigawatts of AMD GPUs.

In the wake of the Amazon agreement, Microsoft and OpenAI issued a joint statement insisting the partnership remains “strong and central”.

Amazon is hedging its bets

While OpenAI is diversifying its infrastructure partners, closer ties with Amazon also highlight the latter’s efforts to broaden its own AI partners.

Anthropic, for example, initially acted as Amazon’s champion in a similar light to the relationship between OpenAI and Microsoft.

Amazon, along with Google Cloud, has invested heavily in Anthropic over the last three years through multiple funding pledges. The company’s Claude models are also used extensively by the hyperscaler, powering products such as Alexa+.

While the deal might have raised questions about the ongoing relationship with Anthropic, Amazon CEO Andy Jassy poured cold water on any speculation last week.

Speaking to CNBC, Jassy said the current deal with OpenAI won’t change relations with the firm's long-time competitor.

“That relationship will stay strong, and we’re really excited about the partnership we’re building over a long period of time with OpenAI,” he told the broadcaster.

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Sumo Logic is expanding its EMEA footprint with planned availability of its AI-powered security solutions on the AWS European Sovereign Cloud and Swiss Data Center region.

The move aims to bolster support for European organizations' data privacy, sovereignty, resiliency, and security needs as they push ahead with digital and AI strategies.

Sumo Logic said the expansion will enable businesses to deploy its security analytics and SIEM capabilities while keeping data in-country or within designated time zones as demand for sovereign cloud services grows.

According to research from IDC, 63% of organizations are now more likely to adopt sovereign cloud services due to recent geopolitical events, with spending tipped to reach more than $400 million by 2029.

Despite the growing market, Eric Avery, global head of infrastructure and data at Sumo Logic, said strict data sovereignty regulations are creating barriers for many organizations – particularly across regulated sectors such as healthcare, finance, and the public sector.

“Previously, enterprises in highly regulated industries have been limited in their choice of cloud security solutions while meeting compliance requirements like Switzerland’s FADP,” he explained.

“Sumo Logic's innovations around SIEM and agentic AI, combined with AWS' European Sovereign Cloud infrastructure, provides the ideal response.”

AWS sovereign cloud and Swiss expansion

Under the expansion, Sumo Logic’s Intelligent Security Operations platform will be made available for deployments on the AWS European Sovereign Cloud to help customers operate cloud workloads in an independently governed environment while using Sumo Logic to log, track, and secure deployments.

The security vendor also confirmed plans to roll out its platform in Switzerland in an effort to better support customers that require faster in-country data processing in line with the Swiss Federal Act on Data Protection (FADP), as well as GDPR obligations.

By expanding its footprint to the AWS Swiss Data Center, Sumo Logic said organizations operating within Swiss borders will be able to leverage its agentic AI-driven log analytics and advanced SIEM capabilities to boost compliance, while benefitting from a faster, low-latency environment.

“We deliver reliable security operations that help organizations stay secure and compliant while running services locally with the performance and scale they need,” Avery added.

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AWS CEO Matt Garman doesn’t appear concerned about the long-term impact of AI on the software industry, but admits there will be some disruption.

Speaking during an interview with CNBC, the AWS chief said recent concerns about software stocks have been blown out of proportion despite widespread sell-offs.

“Look, my opinion is that much of the fear is overblown,” he told CNBC, albeit acknowledging that “there’s a huge disruption” underway in the industry.

Garman’s comments come in the wake of huge market disruption sparked by the launch of recent AI solutions, particularly Anthropic’s Claude Cowork tool.

The launch of the tool, which includes sector-specific plug-ins aimed at automating tasks in areas such as legal, marketing, sales, and data analytics, spooked software investors amid fears the technology could render some provider solutions obsolete.

The subsequent sell-off hit stocks of software companies operating in all of the aforementioned industry verticals.

Last week, the S&P 500 software and services index slipped nearly 5%, losing $830 billion in market value across six straight days of devastating losses.

Across 2026 so far, the iShares Expanded Tech-Software Sector ETF, which tracks software stocks, shows a 24% dip, marking its worst year since 2022.

The SaaS industry has to innovate

While Garman told CNBC the situation has been overblown, he did concede that the current state of affairs in the industry will make things challenging for software providers.

That doesn’t necessarily mean the end of the road for these companies, however. The reality is that they’re operating in an increasingly competitive landscape and will have to work harder for market share moving forward.

“AI is absolutely a disruptive force that’s going to change how software is consumed and how it’s built,” he said.

“The SaaS providers and the larger players of today have an inside track to winning that business. Now, they have to innovate, just like the rest of the world. They can’t stand still. If they stand still, they’re absolutely going to be disrupted.”

Garman isn't alone in shutting down hysteria

Garman isn’t alone in his skepticism. As ITPro reported last week, Nvidia CEO Jensen Huang displayed an optimistic outlook on the future of the software industry during an appearance at the Cisco AI Summit.

Asked whether AI will render the industry obsolete, Huang thoroughly dismissed the idea.

“There’s this notion that the tool in the software industry is in decline, and will be replaced by AI…it is the most illogical thing in the world, and time will prove itself,” he told attendees.

Databricks CEO Ali Ghodsi also shook off concerns during an interview in the wake of a recent financial report. Speaking with Techcrunch, Ghodsi took a similar tone to Huang.

“Everybody’s like, ‘Oh, it’s SaaS. What’s going to happen to all these companies? What’s AI going to do with all these companies?’ For us, it’s just increasing the usage,” he said.

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AT&T is forging closer ties with Amazon Web Services (AWS) and Amazon Leo – the company's low Earth orbit satellite network – to offer fixed broadband services to businesses.

As part of the deal, AT&T revealed it will migrate workloads to AWS infrastructure and will work closely with Amazon Leo to extend networking capabilities for customers across the US

AWS is also set to benefit from the extended partnership, according to Jan Hofmeyr, AWS VP for telecommunications. The move will see AT&T provide high-capacity fiber connectivity for the cloud computing giant's data centers across the country.

"AWS is working with AT&T to advance their goal of expanding connectivity across the United States," Hofmeyr said.

“AT&T gains access to AWS's cloud capabilities and AI tools to accelerate their infrastructure modernization, while AWS benefits from AT&T's expertise in high-capacity fiber networking,” he added.

“By combining AT&T's leadership in advanced fiber networking with AWS's cloud and AI capabilities, we're creating new opportunities to deliver innovative services to customers nationwide.”

Mutually beneficial for AWS and AT&T

In a statement confirming the deal, AT&T revealed it will migrate workloads from several of its current on-premises technologies to AWS on-prem services as well as the firm’s managed hybrid cloud offering, AWS Outposts.

With the help of AWS Professional Services, the telecoms provider will also use Amazon Q Developer and other AWS Agentic Services to accelerate migration of network service enablement.

According to AT&T, the collaboration with Amazon Leo has dual objectives: bolstering data center connectivity as well as networking capabilities for US-based customers.

Under the terms of the partnership, Amazon Leo will offer internet connectivity services to AT&T, enabling it to broaden connectivity capabilities and deliver fixed broadband services to business customers in areas where such services are needed.

Shawn Hakl, senior vice president for product at AT&T Business, said the partnership marks a “pivotal step forward in shaping the future of connectivity in the United States”.

"Fiber is the foundation of that future – it delivers the speed, capacity, and reliability that modern networks demand,” he said.

“By pairing our expanding fiber infrastructure with AWS’s cloud capabilities, and through our collaboration to deliver the infrastructure of the future by connecting data centers, we’re creating a more resilient, scalable, and intelligent connectivity ecosystem.

What is Amazon Leo?

Launched last November and operating as a separate business, Amazon Leo's mission is to deliver fast, reliable internet beyond the reach of existing networks.

The company aims to provide networking services for an array of customers, ranging from individual households and small businesses to large enterprise and government customers.

Amazon Leo is powered by an initial constellation of more than 3,000 satellites, connected to a global network of ground gateway antennas and dedicated fiber.

This includes a series of compact, high-performance antennas –Leo Nano, Leo Pro, and Leo Ultra – that communicate with satellites passing overhead. The entire system is designed, built, and operated in-house at Amazon.

The project is still in its early stages, with only 180 of the planned 3,200 satellites currently in orbit. However, the long-term aim is to connect tens of millions of customers globally.

Amazon said it plans to start offering services to business customers later this year ahead of a full rollout.

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Efforts by Amazon Web Services (AWS) to expand data center infrastructure across Europe face severe delays due to sluggish grid connection practices, a senior company figure claims.

In a recent interview with Reuters, Pamela MacDougall, AWS’ head of energy markets for EMEA, said the length of time it takes to get a connection to energy grids had become a major factor when deciding where to invest in new infrastructure.

Indeed, she said delays in Europe had hampered plans by the company to build data centers in high-demand regions, warning that delays were “challenging our growth aspirations."

"There's a misalignment. We want to expand and grow within two years,” MacDougall said. However, the AWS exec noted that grid connections can take up to seven years in Europe.

Last year, power constrains forced AWS to reportedly scrap plans for an industrial plant in Ballycoolin, Ireland that was going to build server racks.

Data from the International Energy Agency (IEA) shows that securing a grid connection ranges from two to ten years, depending on the country. MacDougall added that the problems weren't limited to a few countries.

"We're finding more and more across Europe that certainty of the delivery date has continued to be delayed."

An AWS spokesperson told ITPro it’s charging with plans to "rapidly expand its infrastructure across Europe, with ongoing investments in edge locations and data center regions in more than 20 countries”.

“We remain committed to expanding at pace to meet growing customer demand,” the spokesperson added.

Figures published as part of Amazon's Q3 2025 earnings report revealed the firm had added more than 3.8 gigawatts of power in the 12 months prior. The spokesperson told ITPro it plans to continue adding capacity across 2026 and into 2027.

AWS isn’t alone in grid woes

The IEA noted last year that the data center project pipeline equals 130% of existing capacity – but based on its own modelling, capacity will likely grow by just 70% because of delays and power constraints.

One solution is building data centers in regions with existing grid capacity, rather than focusing on existing hubs as is normally the case. The IEA added that smart grid tech can help boost capacity while battery systems can help balance demand, but noted that further investment in transmission infrastructure remains necessary.

Indeed, it's not just Europe that is struggling to keep up with data center power demands. The US is also facing "significant concerns" over the impact of data center growth on regional energy grids.

In the UK, the situation is much the same. In 2024, former National Grid CEO John Pettigrew called for "bold action" to boost energy infrastructure to keep up with surging power demands.

"Future growth in foundational technologies like artificial intelligence and quantum computing will mean larger scale, energy-intensive computing infrastructure," Pettigrew told attendees at the Aurora Spring Forum in Oxford.

This predicament for big tech shows no signs of improving any time soon, either, and experts have warned aging energy grids could pose a serious challenge to ambitious infrastructure projects.

Two-fifths of data centers have faced power constraints, according to research from Gartner, while analysis by McKinsey projects data center energy demands to triple by the end of the decade.

Big tech courts alternative energy sources

Big tech companies such as AWS, Microsoft, and Google have all been exploring alternative energy sources to power infrastructure projects.

While renewables have been a long-term focus for cloud computing providers, the advent of generative AI – and the associated pressure on data center infrastructure – brought nuclear power back into vogue.

AWS, for example, shelled out $650 million for a data center co-located with a nuclear power plant – though the project faced significant pushback from regulators.

Elsewhere, Microsoft signed a 20-year power purchase agreement (PPA) with energy provider Constellation in a move that will power data centers with nuclear energy.

The partnership involves the reopening of ‘Unit 1’ of the ‘Three Mile Island’ site in Pennsylvania.

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Amazon’s rumored OpenAI investment plans have drawn criticism from analysts amid suggestions the move shows a “lack of confidence” in its own in-house AI model range.

According to reports from the Wall Street Journal, the hyperscaler could invest up to $50 billion in the AI company as part of a multi-stage funding round which includes backing from Nvidia, Microsoft, and SoftBank.

While exact details on the funding remain unclear, OpenAI has been seeking suitors for an additional $100 billion in investment, largely to fund future infrastructure projects.

Amazon boasts close ties with Anthropic, a key competitor for OpenAI in the generative AI space. Amazon Web Services (AWS) has served as the company’s primary cloud provider since 2023, and in 2024 signed a fresh agreement to become the firm’s primary training and inference partner.

In recent months, reports suggest a warming of ties between Amazon and OpenAI, particularly as the latter embarked on a spending spree.

CNBC reported in December that the duo were locked in investment discussions, with OpenAI apparently keen on an agreement which would allow access to Amazon’s in-house AI chips.

What the OpenAI investment suggests

OpenAI has made no secret about its fundraising efforts over the last two years. In November 2024, the firm raised $6.6 billion in funding at a $157 billion valuation, but it hasn’t stopped there.

2025 was a whirlwind year, with the AI developer signing a host of megadeals with industry titans such as Oracle, AMD, Nvidia, and Broadcom.

For OpenAI, the aims are crystal clear: it has an insatiable appetite for compute power and it’s burning cash at an alarming rate.

The company has lined up more than $1 trillion in spending over the next decade, prompting repeated concerns about its long-term viability and whether it can meet the terms of deals signed with Oracle, for example.

With this in mind, backing from Amazon – and crucially, investment – would mark a major seal of approval for the company. From Amazon’s perspective, the situation appears rather convoluted, according to Forrester principal analyst Rowan Curran.

For Amazon to justify this investment, the deal will likely have to center around heavy use of AWS infrastructure for training and inferencing purposes, as well as use of Amazon’s in-house chips.

“Amazon’s reported coming investment in OpenAI would be a tremendous expenditure of capital that will only benefit Amazon if that money goes right into OpenAI using AWS servers for training and inferencing,” he said.

From an AI model perspective, the deal doesn’t seem to add up for the hyperscaler, which already hosts OpenAI models through its Bedrock service.

Enterprises are increasingly using a mixture of options rather than sticking with a monolithic approach to the technology – a trend that AWS sought to capitalize on with the launch of Bedrock in 2023.

“The foundation model market is not commoditized, but investments of this scale into a single company do not reflect the realities of an increasingly diverse model market, and the demands of mature customers who are using an array of models to achieve their goals, rather than a single model,” Curran commented.

Similarly, the company has invested heavily in its own in-house Nova AI model range.

Amazon unveiled the launch of the Nova models at the 2025 AWS re:Invent conference in Las Vegas. As ITPro reported in December, these models have since received an array of updates and improvements.

Notably, however, Curran suggested this could signal a “lack of confidence” in the Nova models and perhaps a growing sense of frustration at progress on this front.

“This external investment would further signal a lack of confidence in AWS's internal family of Nova models to achieve a level of functionality and usage with customers that will produce significant ROI,” he noted.

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Amazon Web Services (AWS) and NTT Data have announced a new partnership aimed at modernizing legacy systems for enterprises across Europe.

The multi-year deal will see the duo team up to support enterprise IT overhauls across the region, with the goal of supercharging cloud adoption and agentic AI innovation.

Abhijit Dubey, President and CEO of NTT Data, said the agreement will help enterprises “move beyond experimentation” with technologies such as AI, allowing them to scale “impactfully and responsibly”.

"Cloud and AI are central to enterprise transformation," Dubey commented.

"This collaboration underscores our commitment to deliver secure, industry-specific solutions that create tangible business value for our clients worldwide."

Four priorities for European cloud

The agreement has four priorities, the duo said. The first is AI-driven cloud transformation, which focuses on migrating and modernizing on-premises workloads on AWS, using generative and agentic AI to create new ways of doing business.

The second is delivering consistent, reliable industry cloud solutions via AWS, taking advantage of NTT Data’s Industry Cloud. The latter aims to develop dozens of new cloud solutions using AI for specific industries and sectors, including finance, healthcare, public sector, and manufacturing.

Elsewhere, the partnership aims to spur AI and data innovation in secure, compliant cloud environments. This will see the launch of new sandboxes and innovation labs to help develop new solutions.

Sovereign cloud for Europe

The fourth priority lies in digital sovereignty via AWS’ European Sovereign Cloud, with NTT Data as a launch partner. Alongside that, NTT Data has formed a dedicated AWS business group and will certify an additional 10,000 AWS experts over the next three years, doubling the existing number.

"This collaboration will help more enterprise organizations unlock the potential of the cloud and AI to modernize their operations and accelerate innovation," said Greg Pearson, VP AWS Global Sales.

"Through industry-aligned architecture platforms, agentic AI ecosystems, AI-driven customer experience and support in meeting evolving regulatory requirements through the AWS European Sovereign Cloud, we’re enhancing their ability to transform legacy workloads and build the next generation of digital experiences on AWS."

Data sovereignty in the spotlight

Companies are increasingly shifting to local data centers for cloud and AI roll-outs amid a wider push for digital sovereignty. This has been a long-running trend that’s gained significant traction over the last 18 months, largely due to geopolitical conditions.

A recent survey of British tech professionals showed many have grown concerned about US cloud providers cutting access to services at the behest of the Trump administration.

The research noted that six-in-ten respondents believe data sovereignty is now a strategic priority.

Earlier this month, AWS announced general availability of its European Sovereign Cloud, revealing plans for a wider expansion across the continent. Microsoft and SAP have announced similar projects.

Like Microsoft in early 2025, AWS has had to confirm that its European Sovereign Cloud would be truly European – and even promised it would be fully operated by EU citizens with no crucial dependencies on non-EU infrastructure.

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Nationwide Building Society and Amazon Web Services (AWS) have announced a new agreement aimed at driving digital service offerings for the high street lender.

Building on an existing partnership between the two organizations, Nationwide said the new deal will help deliver “more personalized experiences” for the its 17 million customers.

The move by Nationwide comes amidst a long-running digitization scheme at the building society. In 2024, for example, the company completed an overhaul of its IT infrastructure as part of a shift to Amazon EKS.

Similarly, just this month, the organization announced plans for a new AI-powered transaction analytics feature for consumers.

Looking ahead, Nationwide plans to further “consolidate” workloads on AWS, modernize services for customers, and equip staff with new AI tools and capabilities.

"As we continue our digital transformation, we need cloud technology that can support our ambition to deliver better customer experiences, while keeping safety and security at the forefront,” said Suresh Viswanathan, group chief operating officer at Nationwide.

“With AWS, we can better support our frontline colleagues to help improve member experience and deliver better outcomes for over 17 million customers."

Nationwide already uses AWS’ cloud-based contact center platform, Amazon Connect, when dealing with customer support enquiries. This gives customer support teams access to a range of AI-powered tools that help drive operational efficiency and staff productivity.

The building society has used Amazon Connect to underpin new customer services, including the recently-launched Call Checker tool. This helps customers establish whether they are speaking to a legitimate Nationwide worker to crack down on scam calls.

"By consolidating and modernizing their workloads on AWS, Nationwide can accelerate innovation, enhance operational resilience, and deliver the digital experiences their members expect—all while maintaining the security and compliance standards that are paramount in financial services,” said Alison Kay, VP and Managing Director of AWS UKI.

Nationwide targets AI, cloud training for staff

As part of the agreement, AWS revealed it will work closely with Nationwide to bolster workforce skill capabilities. This will include access to AWS training schemes to equip them with cloud and AI-related skills.

“This will support Nationwide’s ability to adopt AWS technologies for the benefit of its customers and colleagues,” the hyperscaler said in a statement.

Training schemes running parallel to digital transformation projects have become a recurring theme in announcements such as these.

As ITPro reported last week, Lloyds Banking Group has embarked on a company-wide AI training program as the company looks to integrate the technology across core operations.

The financial services provider said it plans to train 100% of its employees in AI skills by the end of this year alone, enabling staff to easily adopt these tools and improve customer service capabilities.

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Amazon Web Services (AWS) is downplaying reports that a CodeBuild vulnerability could have compromised thousands of enterprise user accounts.

CodeBuild is a managed Continuous Integration (CI) service that’s often connected to GitHub repositories, triggering builds on events like new pull requests.

The vulnerability, dubbed by Wiz researchers as ‘CodeBreach’, stemmed from a subtle flaw in how core AWS GitHub repositories handled build triggers.

"The issue allowed a complete takeover of key AWS GitHub repositories - most notably the AWS JavaScript SDK, a core library that powers the AWS Console," said Wiz.

"By exploiting CodeBreach, attackers could have injected malicious code to launch a platform-wide compromise, potentially affecting not just the countless applications depending on the SDK, but the Console itself, threatening every AWS account."

Researchers found that just two missing characters in a Regex security filter - the start (^) and end ($) anchors - allowed unauthenticated attackers to compromise the build environment and leak privileged credentials.

These anchors are essential to ensuring an exact match; without them, the filter simply searches for a string that contains the pattern. As a result, Wiz said any GitHub user ID containing an approved maintainer’s ID as a substring would look legitimate.

“This creates a critical risk: if an attacker can compromise a single build, they are just a memory dump away from stealing credentials that often possess powerful permissions over the source repository,” the company explained in a blog post.

How the CodeBuild vulnerability was discovered

In dissecting the vulnerability, Wiz researchers created thousands of GitHub bot accounts until one matched the criteria, allowing them to push a pull request that looked legitimate.

This successfully extracted GitHub credentials for the aws-sdk-js-automation account, which had admin privileges over several AWS repositories, including private ones.

Wiz acknowledged that the issue wasn't a service-wide flaw, but warned that CodeBuild customers could introduce the same misconfiguration to their own projects.

The company disclosed its findings to AWS, which fixed the issue within 48 hours.

AWS also implemented global hardening measures within the CodeBuild service to prevent similar attacks, most notably with a new Pull Request Comment Approval build gate.

The company said it had audited all AWS-managed open source GitHub repositories, and found that none involved this type of misconfiguration.

"These activities had no impact to any AWS customer environments and did not impact any AWS services or infrastructure. No customer action is required," said the firm.

Regardless, Wiz recommends that CodeBuild users should enable the new Pull Request Comment Approval build gate or use CodeBuild-hosted runners to manage build triggers via GitHub workflows.

If there's really a need for webhook filters, they should ensure their regex patterns are anchored.

Organizations should also secure the CodeBuild-GitHub connection by generating a unique, fine-grained Personal Access Token (PAT) for each CodeBuild project, strictly limiting the PAT's permissions to the minimum required, and perhaps using a dedicated unprivileged GitHub account for the CodeBuild integration.

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AWS has announced the general availability of its European Sovereign Cloud, touting plans to expand the service across the continent.

The new scheme will offer European-based customers a fully independent cloud located entirely within the EU. This means enterprise data will be hosted and stored solely in the region and kept separate from other AWS Regions worldwide.

The service will be operated out of Germany, according to AWS, and underpinned by more than €7.8 billion in investment.

AWS said it plans to expand options to other European countries as part of the move, with new AWS Local Zones earmarked for Belgium, Portugal, and the Netherlands.

“The AWS European Sovereign Cloud’s unique approach provides the only fully featured, independently operated sovereign cloud backed by strong technical controls, sovereign assurances, and legal protections designed to meet the needs of European governments and enterprises for sensitive data,” the hyperscaler said in a statement.

The move by AWS comes amidst an intense focus on sovereign cloud for European customers. Spurred on by customer demands and regulatory scrutiny, a host of major cloud computing providers have launched - or are in the process of rolling out - sovereign cloud services.

Last year, for example, Microsoft launched a new sovereign cloud scheme covering private and public cloud, along with the launch of dedicated National Partner Clouds in France and Germany.

So what can customers expect from the new AWS Sovereign Cloud project?

What to expect from the AWS European Sovereign Cloud

First and foremost, the new sovereign cloud setup is “physically and logically separate” from other global AWS Regions, enabling European enterprises to meet stringent regulatory requirements on data residency and privacy.

Enterprises operating on the sovereign cloud will have “full control over where their data is stored”, the company said. This includes complete control over all metadata they create – down to roles, permissions, resource labels, and configurations.

Control of sovereign Identity and Access Management (IAM) data, billing, and usage metering systems is also guaranteed.

Crucially, AWS said the new setup places a strong focus on “operational autonomy”, meaning it’s operated “exclusively” by EU residents and has no dependence on non-EU infrastructure.

“Its unique design enables it to continue operations indefinitely,” the hyperscaler explained. “Even in the event of a communications disruption with the rest of the world”.

This aspect of the sovereign cloud scheme is noteworthy, particularly amidst growing concerns about potential US overreach and frosty transatlantic political relationships.

Last year, Microsoft was forced to reassure customers it would take legal action against the US government in the event the Trump administration pressured providers to shut down services in Europe.

The comments from Microsoft President Brad Smith followed the signing of a memorandum in early 2025 to defend US companies from “overseas extortion” in response to the EU Digital Markets Act (DMA).

Reliance on US tech providers has become a key concern for IT leaders in both the UK and EU over the last two years. A study from Civo in May 2025 showed 60% of respondents think the UK government should cut its use of US cloud services over data protection and privacy concerns.

AWS said that in the event of “communications disruption”, AWS employees located in the EU will have “independent access to a replica of the source code needed” to maintain the service.

Security and compliance gains

Elsewhere, AWS said the new sovereign cloud gives enterprises access to “leading technical and compliance controls”. These controls come in the form of the AWS Nitro System, which allows enterprises to enforce strict security boundaries and access restrictions for data held in the region.

“Nobody, including AWS employees, can access customer data running in Amazon EC2,” the company said.

“AWS also provides advanced encryption, key management services, and hardware security modules that customers can use to further protect their content. Encrypted content is rendered useless without the applicable decryption keys.”

The hyperscaler has also launched a new “Sovereignty Reference Framework”, which aims to provide enterprise customers with information and guidance on sovereignty requirements in the region, helping streamline regulatory compliance.

“Customers can use the third-party validated ESC-SRF auditor report to demonstrate clear and enforceable sovereignty assurances,” AWS said.

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Digital services and consulting giant Infosys has signed a deal with AWS aimed at boosting the use of generative AI internally and across its client base.

The agreement will see Infosys Topaz, a set of services, solutions, and platforms using generative AI, combined with Amazon Q Developer, AWS’ generative AI-powered coding assistant.

Infosys Topaz, the firm noted, offers more than 12,000 AI assets, 150 pre-trained AI models, and more than 10 AI platforms steered by AI-first specialists and data strategists, with a ‘responsible by design’ approach.

Amazon Q Developer, meanwhile, can handle tasks including implementing features, documenting, testing, reviewing, and refactoring code, as well as performing software upgrades.

It's claimed to boost developer productivity by up to 40% and speed up developer tasks by up to 80%.

The aim of the new collaboration is to enhance the company's internal operations and drive innovation for customers across sectors such as manufacturing, telecom, financial services, and consumer goods.

"The combined strengths of Amazon Q and Infosys Topaz will help organizations innovate, achieve operational agility, and unlock differentiated value for their clients," said Sandeep Dutta, president of Amazon Web Services India and South Asia.

"Through this collaboration, Infosys and AWS are committed to delivering solutions rooted in technical excellence and tailored to address the unique demands of global industries.”

Infosys eyes gains with Topaz platform

Infosys plans to use Infosys Topaz to drive AI-powered transformations across key functions, such as software development, HR, recruitment, sales, and vendor management.

For example, in the Software Development Lifecycle (SDLC), the integration of Infosys Topaz with Amazon Q Developer will enable automated documentation and provide tailored support for tasks like code generation, debugging, testing, and legacy code modernization.

This will significantly enhance workflow efficiency and accuracy, the firm said.

The company also plans to use AWS generative AI services to deliver industry solutions such as advanced end-user engagement capabilities for sports and entertainment, powered by Infosys Topaz and Amazon Bedrock.

This, it said, will enable dynamic, real-time personalized experiences to enhance engagement for millions of fans worldwide.

“Our collaboration with AWS is fundamentally reshaping how enterprise value is created and delivered. By integrating Amazon Q Developer with Infosys Topaz, we are not just transforming our internal functions, such as development cycles, but also enabling our clients to reimagine critical functions like HR, recruitment, and vendor management," said Balakrishna DR, executive vice president, global services head, AI and industry verticals, at Infosys.

"Together, we are building an AI-first ecosystem that empowers enterprises to navigate their next business transformation with agility and precision. This is about amplifying human potential to drive innovation and deliver impact at an unprecedented scale.”

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CrowdStrike, AWS, and Nvidia have picked 35 startups for their Cybersecurity Startup Accelerator, saying they've been chosen for their innovation, their potential to create market impact, and the caliber of their teams.

“This year’s cohort reflects a global movement: founders building cloud- and identity-first defenses that put security teams ahead of the speed and scale of AI-emboldened adversaries," said Daniel Bernard, chief business officer at CrowdStrike.

"With AWS and Nvidia, we’re creating a community and growing 'the crowd', giving these start-ups the opportunity to turn breakthrough ideas into market-shaping technologies, and push the industry forward.”

The free, eight-week program runs from now until March 3, offering mentorship, technical expertise, funding, and go-to-market support along with access to top cybersecurity experts and global visibility across partner ecosystems.

The program will come to a head with a final pitch day for five finalists during the RSA Conference in San Francisco on March 24, where an expert panel will select one innovation award winner, which will potentially win investment from the CrowdStrike Falcon Fund.

"AI is reshaping cybersecurity at every level, demanding new approaches that can operate at cloud scale and defender speed,” said Bartley Richardson, senior director of agentic AI and cybersecurity engineering at Nvidia.

“Through the accelerator, Nvidia, AWS, and CrowdStrike are empowering start-ups with the compute, frameworks and guidance they need to advance agentic AI and build the next wave of intelligent, resilient security technologies.”

The companies expanded the program in November, opening it to startups worldwide. The 2026 cohort includes firms working on AI-driven threat detection, cloud workload protection, identity security, and secure data handling, from North America, Europe and other regions.

Now in its third year, the Accelerator has graduated 59 startups in total, which between them have collectively raised more than $730 million in funding following their participation.

Nvidia’s support comes via its Inception program, which supports companies through critical stages like product development, prototyping, and deployment.

Members get a personalized range of benefits, including Nvidia Deep Learning Institute credits, preferred pricing on select Nvidia hardware and software, and guidance from technical experts.

Last year's Accelerator winner was Terra Security, picked for its work in agentic AI-powered, continuous web application penetration testing, while Remedio was the winner of the 2023–2024 cohort – both firms raised sizeable funding rounds following the program.

"Participating in the AWS CrowdStrike Accelerator Program has truly been a wonderful experience for Remedio. The invaluable content and strategy sessions have significantly boosted our company's growth," commented Tal Kollender, CEO and co-founder of Remedio.

"What's been most rewarding on a personal level is the exceptional mentorship and the opportunity to connect with industry leaders I've long admired. It's surreal to witness their genuine interest and eagerness to help."

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Amazon Web Services (AWS) has quietly raised the prices of EC2 Capacity Blocks for machine learning, upping them by around 15%.

First spotted by The Register, the changes mean the cost of a p5e.48xlarge instance has risen from $34.61 to $39.80 per hour across most regions, while the pricing for p5en.48xlarge has gone up from $36.18 to $41.61.

There's an even bigger increase in the US West (N. California) region, where p5e rates have risen from $43.26 to $49.75.

Amazon EC2 Capacity Blocks allow GPU capacity to be booked in advance at a locked-in price, and are mostly used by large organizations with substantial cloud budgets, generally for business-critical ML training.

This gives customers guaranteed GPU capacity at predetermined times, allowing them to reserve capacity for a fixed time window, ranging from one day to several weeks, paying an agreed rate up-front.

The blocks can be reserved up to eight weeks in advance.

"With Amazon EC2 Capacity Blocks for ML, you can reserve just the amount of accelerator capacity you need to run your machine learning workloads. EC2 Capacity Blocks pricing consists of a reservation fee and an operating system fee," AWS explained in promotional materials.

"The reservation fee is charged up front at the time you schedule the reservation. Your Capacity Block is charged at the prevailing rate at the time of purchase, even if the Capacity Block is scheduled to start after the price is updated."

Why has AWS increased prices?

Capacity Blocks have always been subject to variable pricing, based on supply and demand and adjusted every quarter based on expected market conditions.

AWS has previously reduced pricing three times: once in 2024, and twice in 2025.

While demand for compute power for AI and machine learning continues to grow, supply is limited, with a global shortage of advanced GPUs.

The change comes just a few months after AWS cut prices for some GPU instances, particularly for On-Demand and Savings Plans, by up to 45%.

The hyperscaler specifically highlighted price cuts at its annual re:Invent conference in Las Vegas in December.

Capacity Blocks were not included in those reductions, though.

"Regular price reductions on AWS services have been a standard way for AWS to pass on the economic efficiencies gained from our scale back to our customers," the company said at the time.

"These pricing updates reflect the AWS commitment to making advanced GPU computing more accessible while passing cost savings directly to customers."

The next review of pricing is set for April 2026.

A spokesperson for AWS told ITPro: “EC2 Capacity Blocks for ML pricing are dynamic and vary based on supply and demand patterns, as described on the product detail page.

“This price adjustment reflects the supply/demand patterns we expect this quarter. AWS’s commitment to not raise pricing on fixed pricing models like On Demand and Savings Plans remains unchanged.”

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Global spending on cloud infrastructure continues to skyrocket, new research shows, as enterprise demand for AI moves from early tests into full production deployment.

New figures from Omdia show global spending on cloud infrastructure services reached $102.6 billion in the third quarter of this year, up 25% year-on-year and marking the fifth consecutive quarter in which growth has been above 20%.

Amazon Web Services (AWS), Microsoft Azure, and Google Cloud kept the same market rankings as in the previous quarter – collectively accounting for 66% of global cloud infrastructure spending. Together, they saw 29% year-on-year growth.

AWS’s revenue grew by 20% – its strongest performance since 2022 – with a 32% market share. Omdia attributed this growth to an easing of compute supply constraints and incremental demand driven by its partnership with Anthropic.

Microsoft Azure maintained its place as the world’s second-largest cloud provider during the quarter, with a 22% market share and 40% year-on-year revenue growth.

Meanwhile, recorded 36% year-on-year growth and increased its market share to 11%, mostly thanks to enterprise AI offerings.

Backlog levels among leading cloud providers continued to rise, with all three reporting further increases during the third quarter.

AWS, for example, reported a total backlog of $200 billion by the end of the quarter, while Google Cloud saw levels increase to $157.7 billion, up sharply from $108.2 billion in Q2.

Hyperscalers target platform gains

Omdia noted that ss enterprises look beyond AI platforms' model capabilities towards multi-model strategies and agent-based applications, hyperscalers are moving towards platform-level AI capabilities.

AWS, Microsoft Azure, and Google Cloud are all integrating proprietary foundation models alongside an expanding array of third-party and open-weight models.

This approach by the trio is centered around leveraging managed platforms and services such as Amazon Bedrock, Azure AI Foundry, and Vertex AI’s Model Garden to expand support.

“Collaboration across the ecosystem remains critical,” said Rachel Brindley, senior director at Omdia.

“Multi-model support is increasingly viewed as a production requirement rather than a feature, as enterprises seek resilience, cost control, and deployment flexibility across generative AI workloads.”

Real-world impact still a struggle

Notably, many organizations are struggling with real-world deployment, and hyperscalers are stepping up investment in agent build-and-run capabilities, Omdia revealed.

Recent examples of this trend include AWS AgentCore and Microsoft’s Agent Framework, which provide standardized foundational capabilities aimed at helping enterprises more efficiently build, deploy, and operate AI agents in production settings.

“Many enterprises still lack standardized building blocks that can support business continuity, customer experience, and compliance at the same time, which is slowing the real-world deployment of AI agents,” said Yi Zhang, senior analyst at Omdia.

“This is where hyperscalers are increasingly stepping in, using platform-led approaches to make it easier for enterprises to build and run agents in production environments.”

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Russian-backed hacker groups are exploiting misconfigured edge devices – now preferring that tactic over hunting down traditional vulnerabilities to gain access to company networks.

That's according to an end-of-year report by Amazon Threat Intelligence, which included details of a nearly five-year-long campaign by Russian state-sponsored hackers that AWS said marked a pivot in tactics.

Now, the primary initial access vector has become misconfigured customer network edge devices, according to AWS Security CISO CJ Moses, with a decline in traditional vulnerability exploitation.

"This tactical adaptation enables the same operational outcomes, credential harvesting, and lateral movement into victim organizations’ online services and infrastructure, while reducing the actor’s exposure and resource expenditure," Moses noted in a post on the AWS security blog.

Amazon isn't the first to spot a shift to edge devices. Sophos noted in April that edge devices like firewalls and routers were the main initial attack vector for 30% of incidents last year, while governmental security agencies issued guidance about vulnerabilities in edge devices back in February.

Last year, Fortinet's FortiGate edge devices were exploited by China-backed hackers, and the FBI warned that Ubiquity EdgeRouters were targeted via a wide-ranging hacking campaign.

How the edge campaign unfolded

According to Amazon, hackers targeted enterprise routers, VPN concentrators and remote access gateways, network management appliances, and cloud-based project management systems, as well as collaboration and wiki platforms.

Moses said the evidence suggested that the hackers were using packet capture and traffic analysis to target network edge devices. This involves attackers compromising an edge device hosted on AWS, capturing packets to harvest credentials, and then using those to penetrate an organization's services or infrastructure, gaining access to wider systems.

AWS telemetry suggested the attackers maintained persistent connections, allowing for data to be stolen.

"Targeting the 'low-hanging fruit' of likely misconfigured customer devices with exposed management interfaces achieves the same strategic objectives [as vulnerability exploitation], which is persistent access to critical infrastructure networks and credential harvesting for accessing victim organizations’ online services," Moses added.

Notably, the company revealed those attacks included customer network edge devices hosted on AWS.

"This was not due to a weakness in AWS; these appear to be customer misconfigured devices. Network connection analysis shows actor-controlled IP addresses establishing persistent connections to compromised EC2 instances operating customers’ network appliance software," Moses noted.

That said, AWS did take action. For example, the cloud giant notified affected customers that they were compromised, fixed compromised EC2 instances, and alerted network alliance vendors.

"Through coordinated efforts, since our discovery of this activity, we have disrupted active threat actor operations and reduced the attack surface available to this threat activity subcluster," Moses added.

To protect edge devices against this style of attacks, organizations must secure and monitor their edge devices, Moses advised, keeping watch for unexpected packet capture files or utilities and enforcing strong authentication – in particular those working in the energy sector or critical national infrastructure.

A 'clear evolution in tactics'

This particular string of attacks dates back to 2021 and appears to be associated with Russia's Main Intelligence Directorate, Moses said.

Similarly, the campaign focused primarily on critical national infrastructure in the West, targeting the energy sector and its supply chain in particular.

Moses traced a timeline back to 2021's WatchGuard exploitation, saying that's when Amazon first spotted the hackers targeting misconfigured devices.

That continued in the next few years with misconfigured devices targeted alongside exploits such as the Confluence and Veeam flaws, but by 2025 the hackers' success with edge devices led to that taking centre stage with zero-day exploitation activity declining.

"The campaign demonstrates a clear evolution in tactics," Moses said.

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Agents, agents, and more agents. It’s the big trend that’s taken the tech industry by storm over the last year, and truth be told, I’m at the point where I’ve covered the topic so much that I’m dealing with a severe case of semantic satiation.

AWS announced a new class of agents at its annual re:Invent conference last week. Known as “frontier agents”, these are more powerful, intuitive, and better equipped to deal with extended periods of operation than the first generation of agents.

From start to finish, the event reeked of hype and hyperbole, with CEO Matt Garman placing agentic AI as on par with the web and cloud computing in terms of its potential long-term impact on businesses.

I’ve no doubt that agentic AI will mark a step change in the evolution of the technology, but I was at least expecting AWS’ old guard reputation in the industry to temper expectations. On that front, I was way off the mark.

As with generative AI, the agentic trend is nowhere near the point of delivering on the bold promises made by major industry providers. An MIT study in August, for example, found enterprises have invested upwards of $35 billion in generative AI projects.

Yet despite these huge investments, they still haven’t reached the productivity-related promised land predicted by big tech.

On the agentic AI front, the situation is roughly the same, with a similar pessimistic outlook on success rates. Analysis from Gartner found that over 40% of projects will be cancelled by 2027, underlining the high stakes involved.

A key factor here, the consultancy noted, lies in “escalating costs, unclear business value, or inadequate risk controls”.

That gives AWS and its industry counterparts roughly two years to drive home the messaging before enterprise IT leaders start wondering where all the money has gone – and that’s if we’re being generous and assuming patience will last.

AWS' old tricks could work with new trends

To AWS’ credit, it has the experience and know-how to potentially deliver on this promise. Indeed, the company is pursuing a similar strategy to the early days of the cloud shift.

Start with the hardware and infrastructure and build from there. In this regard, there’s no denying the company has the capability to deliver: it has strong, deep roots and still holds the title of the largest of the three hyperscalers.

The hyperscaler covered all bases in this regard across the four-day event: from new Trainium chips to Amazon S3 upgrades and an array of AI-related announcements aimed at lowering the barrier to entry for enterprises.

Chief among these was the launch of Amazon Nova, a new system that allows customers to build frontier models. The platform enables customers to combine in-house data with AWS’ open training models, with the result being a bespoke model curated specifically for an enterprise’s individual needs.

This will undoubtedly bridge what has typically been a gap for many enterprises since the advent of generative AI: the lack of financial muscle required to build their own models.

Notably, these custom models will be hosted through Bedrock, the firm’s one-stop shop for in-house and third-party AI tools and a key focus for the company over the last two years.

There is an argument to be made that AWS is building a walled garden here. It obviously wants to keep customers operating within its ecosystem, and platforms like Bedrock and the AgentCore service – a similar setup for sourcing and deploying agents – will help it achieve that.

However, this is less of a walled garden approach akin to the cloud era and more clearly aimed at cultivating an ecosystem that covers all the bases for customers. The company has made no secret of its willingness to simplify integration with other hyperscalers and its relationship with AI providers like Anthropic further highlights this.

Getting projects off the ground

Shiny new tools might get customers excited, but whether enterprises can actually capitalize on these is another question. That's where partners will come in handy for the hyperscaler.

The AWS partner ecosystem is going to play a key role in driving adoption rates, particularly on the agents front. This thriving ecosystem of systems integrators and independent software vendors (ISVs) was critical during the halcyon days of cloud adoption.

As ITPro learned at re:Invent 2025, Rohan Karmarkar, managing director of AWS’ partnership solutions architecture, said partners have been “critical from day one” – the same rules apply with agentic AI.

With 140,000 partners to draw from, AWS customers have no shortage of expertise and support if they’re dabbling in agents. From the hyperscaler’s perspective, this presents a huge opportunity to simplify adoption processes, which are going to be a challenge if it's going to hit the ground running with this strategy.

Tangible business use-cases

One recurring gripe enterprises and industry stakeholders alike have had with generative AI has been the pie-in-the-sky claims from providers.

We’ve all heard the talking points about productivity improvements and efficiency gains, but the reality is that there simply hasn’t been enough concrete evidence to support the idea that the technology will be the game changer it’s framed as.

Agentic AI has - and will continue to - suffer the same problem. In this sense, AWS made a big statement in highlighting its own internal use of agents - and so far the signs are promising.

As AWS CISO Amy Herzog told ITPro, the company has been using agents in security operations for some time now, enabling teams to drastically reduce manual toil and speed up incident response capabilities.

During the same panel session where Herzog touted the technology’s potential, Hart Rossman, VP, Office of the CISO, also detailed the company’s success with an internal “security response agent”.

AWS’ reputation as a reliable, no-nonsense hyperscaler precedes it. If the company draws on its cloud credentials to push agentic AI and continues showcasing tangible business use-cases, then it might finally stake its claim as the go-to AI shop after what was a rocky start in the early days of the generative AI race.

AI agents are already being put to good use by cybersecurity teams at Amazon, according to AWS CISO Amy Herzog, with the tech giant ramping up in-house adoption of its own agentic solutions.

Speaking during a panel session at the company’s re:Invent conference last week, Herzog told attendees she’s “optimistic about what a boon this will be for defenders”, later telling ITPro that agents are helping to reduce workloads and streamline processes.

Responding to critical vulnerability exploits (CVEs), for example, is a prime area in which agents are helping reduce manual toil, Herzog noted. This has traditionally been a laborious process, especially given the volume of CVEs on an annual basis and Amazon’s need to shore up a myriad of networks, platforms, and solutions.

“Analyzing CVE changes or updates is a thing my team has to do at scale,” she told ITPro. “In particular, we have to combine the kind of massive scale, the number of CVEs in a year, with the scale of the AWS network that we need to evaluate.”

“There's tiers of analysis of these, starting with fully automated and then we get into deeper human interaction. We sort of funnel them right,” Herzog explained. “And [with] the deeper human interaction we can cover so much more.

So far, Herzog noted there has been a “500% increase” in the company’s ability to “piece together information” for security teams on this front.

This marks a step change in efficiency for security practitioners, and with agents, teams are able to lower manual activities and focus on the aforementioned “deeper human interactions”.

It’s the cybersecurity equivalent of the “focusing on more rewarding aspects of your role” talking point frequently touted by providers. In this instance, however, the company has tangible examples of the technology actually delivering on promises.

“Outside of response scenarios, we’re seeing a similar pattern of benefit to our workers, where they've got a task to do, it involves some amount of piecing together information and stitching it together and understanding of richer context that used to be quite manual and somewhat painful in many cases, especially for our responder teams,” she said.

“Now the agents can help prepare the information that they need to take that high judgment human action with a lot less toil. They're making the humans more effective and having to do less of the kind of toil stitching together work that it's the bread and butter of a security job.”

AWS is all-in on agentic AI

Herzog’s comments came off the back of a week filled with agentic AI announcements by AWS, with the company doubling down on this latest iteration of the technology.

The launch of powerful new “frontier AI agents” were among the big talking points of the week, with agents aimed specifically at security operations and software development announced by CEO Matt Garman.

As ITPro reported, the AWS Security Agent looks to bolster security capabilities for developer teams, working in-tandem alongside dedicated DevOps and Kiro coding agents to streamline the software development lifecycle.

From initial production projects to launches, AWS wants customers to embed agents across workflows to drive efficiency.

An agentic AI paradox

Herzog wasn’t alone in highlighting the gains security teams are unlocking with agentic AI. Hart Rossman, VP for Office of the CISO at AWS, also told ITPro the company has had a “security responder agent” in production for some time now.

In the case of a responder receiving a signal, evidence, or a ticket, Rossman said cyber practitioners could ask the agent “a question or two to develop some context” and speed up response times.

While the agent has proved effective on this front, it did highlight somewhat of a paradox. The responder agent has streamlined processes for security teams, but Rossman revealed testing showed these gains were offset by the sheer interest in the tool’s capabilities.

Simply put, users found themselves asking more questions than needed, thereby slowing down processes – albeit marginally.

“What we found was that they actually spend time to ask, on average, 11 questions of the bot because it was so compelling. One question led to another question, and then [after] around 10 or 11 questions they would kind of go back to their workflow,” Rossman told ITPro.

“So on one hand, we were excited that they were seeing the value in the agentic solutions, but on the other hand we said, well now that’s created a little bit of an inefficiency itself,” he added.

Fine-tuning of the tool, and how cybersecurity professionals use it in daily operations, has resulted in significant improvements, Rossman revealed.

“We really don't want them asking 11 questions of the bot. We now want to take that feedback and say, can we get them the same result in two questions,” he said.

“So we’ve been on that journey and it’s dramatically reduced the time to get from initial signal to plausible courses of action, to remediate, and then correction or root cause analysis.”

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AWS has unveiled a new service aimed at helping enterprises build AI models in a bid to democratize access.

Amazon Nova Forge, unveiled at the company’s annual re:Invent conference in Las Vegas, will allow customers to “blend” their own in-house data with the company’s Nova model range.

Building a frontier AI model from scratch is a costly process, and one that most businesses simply can’t afford, CEO Matt Garman told attendees at the conference. In launching the service and combining customer data with its own open weight models, this bridges the gap for those without the necessary financial resources.

“Nova Forge is a new service that introduces the concept of open training models,” he said.

“With Nova Forge, you get exclusive access to a variety of Nova training checkpoints, and then you get the ability for you to blend in your own proprietary data together with an Amazon-curated training dataset at every stage of the model training.”

These “checkpoints” cited by Garman refer to stages within the training process of an AI model, whether that be pre-trained, mid-trained, and post-trained. Users can integrate their own data at certain points of this process depending on their individual requirements.

The advantage here, Garman claimed, is that the service both reduces the technical and financial load on the enterprise while giving them a bespoke model that “deeply understands” their data and specific business needs or area of expertise.

This understanding of the business’ knowledge base also has long-term advantages, allowing for easier fine-tuning and upgrades down the line.

“Because your baseline model already understands your business, these post-training techniques are actually much more effective,” he said. “Once you’re ready, you import this model, your Novella, into Bedrock, and you run inference on it just like you would any other Bedrock model.”

Customers will be able to begin building their own Novella custom models using its Nova 2 Lite model, also announced at the conference yesterday.

AWS bets big on Nova Forge

The announcement from AWS underlines the company’s long-term focus in terms of AI development and adoption: flexibility and customer choice.

As Garman noted, those who build models using the Forge service will be able to deploy it on Amazon Bedrock, the company’s platform which gives customers access to a range of third-party and in-house AI models.

This platform has been the foundation upon which AWS has built out its AI services over the last two years. In recent months, the company has added new agentic AI-related options through the Bedrock AgentCore service.

Keeping these models within the AWS ecosystem has added benefits, the company noted, particularly in terms of security and scalability.

“This complete solution – from building their own frontier model to production deployment – ensures organizations achieve optimal AI performance tailored to their specific business needs, with exclusive use of their model security hosted on AWS,” the hyperscaler said in a statement.

AWS CEO Matt Garman believes AI agents will have as profound an effect on global business as the advent of the web or cloud computing.

Speaking at the company’s annual re:Invent conference in Las Vegas this week, Garman pointed to the rapid evolution of AI over the last three years.

Initial tinkering with chatbots and AI assistants has now given way to an influx of agents, which are capable of operating autonomously in the background in place of workers rather than supplementing workflows.

This new paradigm in the AI space will have a huge long-term effect on business efficiency and individual productivity, Garman noted.

“Every single customer experience, every single company, frankly every single industry, is now in the process of being reinvented, and we’re still in the early days of what AI is going to deliver,” he told attendees.

“It wasn’t that long ago that we were all testing and experimenting with chatbots, and now it seems like there’s something new every day.”

Garman said that engagement with customers has highlighted poor returns on the technology so far in the generative AI race. Returns on investment have been a recurring talking point despite bold promises from big tech providers.

“Many of you out there, you haven’t yet seen the returns that match up to the promise of AI, the true value of AI has not yet been unlocked. But a lot of that is changing fast”

With agents, Garman expects enterprises will finally begin unlocking real value from the technology.

“This is where we’re starting to see material business returns from your AI investments,” he told attendees. “I believe that the advent of AI agents has brought us to an inflection point in AI’s trajectory.”

“This change is going to have as much impact on your business as the internet or the cloud,” Garman added. “I believe that in the future, there’s going to be billions of agents inside of every company and across every imaginable field.”

Are AI agents delivering on the hype?

Agentic AI has become a contentious topic over the last year. With Salesforce striking an initial lead on this front with the launch of its Agentforce service, big tech providers across the board have jumped on the bandwagon.

Just last month, Microsoft announced a slew of new agentic AI features across its core product and service lines, from Windows to Azure and Microsoft 365, agents are now deeply embedded across the breadth of the company’s products.

However, as with AI assistants and ‘copilots’, questions still remain over whether the technology is delivering tangible benefits for businesses or individual workers. This emerging aspect of the broader AI industry has also become swamped by hype and hyperbole.

Research from Gartner earlier this year suggested that a culture of “agent washing” had emerged as solutions providers scrambled to pivot to the new trend.

Gartner said the majority of products reviewed were essentially “repackaged” chatbots and robotic process automation (RPA) solutions.

AWS appears confident that its range of AI agents very much meet expectations, dubbing them “frontier agents” that represent a step up from the traditional class of agents out there on the market.

Frontier agents, by AWS’ definition, are capable of operating fully autonomously for hours or days without human intervention. Moreover, they’re highly scalable and continuously improve by shadowing human workers, monitoring activities and processes and reacting accordingly.

The company launched three new frontier agents at re:Invent this week, with a particular focus on streamlining processes in software development.

Agentic features in the Kiro coding tool, along with a dedicated AWS Security Agent and DevOps Agent look to speed up production across the entirety of the software development lifecycle.

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AWS has unveiled a set of powerful new “frontier agents” , which the hyperscaler said marks a step change in the potential of agentic AI technology and the automation of far more complex tasks.

Frontier agents aren’t your typical AI agent working away in the background, automating tasks and dealing with customer service queries. As journalists were told at a pre-briefing ahead of the annual re:Invent conference, they’re a “new class” of agent capable of working fully autonomously for hours or days without intervention.

These agents are highly scalable, self-learning, and represent the next iteration of the technology, according to the hyperscaler.

To mark its first foray on this front, AWS has launched three new frontier agents, which it said are primed to fundamentally transform software development. The company’s Kiro coding service, for example, is getting a big update with an agentic twist, dubbed Kiro Autonomous Agent.

Speaking to ITPro ahead of the event, David Yanacek, senior principal engineer for agentic AI at AWS, said these new capabilities will prove vital in helping developer teams speed up production in a safe and secure manner.

“These act as an extension to your team, more so than a tool for developers,” he said. “So we've started this category of what we call frontier agents. We've started by releasing three software development lifecycle related agents.”

According to AWS, the Kiro Autonomous Agent “maintains persistent context across a range of sessions,” meaning it’s lingering in the background learning from human processes.

While this appears similar to what one would consider a ‘traditional’ AI agent, this new class tracks human activity to improve continually, learning pull requests and providing users with feedback.

The agent comes with a range of capabilities, such as triaging bugs and improving code coverage, the company told assembled media.

“You can ask it questions, describe a task, and assign tasks in your backlog directly from GitHub,” AWS explained in a statement. Thereafter, the agent will “independently figure out” how to complete the task and share recommendations for changes, potential edits or pull requests.“

Security agents target safer software

Elsewhere, Yanacek told ITPro the new AWS Security Agent aims to drive the development of safer, more secure software.

According to AWS, the agent “embeds deep security expertise throughout the development lifecycle” by proactively reviewing design documents and scanning pull requests, comparing them to common vulnerabilities and in-house security requirements.

The launch of this frontier agent represents a step change in software development, according to Yanecek, addressing long-standing security-related issues and alignment between developer and security teams. The agent can perform penetration testing to probe for security vulnerabilities, for example, turning what was previously a laborious manual process into an “on-demand capability”.

“If you're a security team, you want to make sure that all of the teams in your organization are doing things in a secure way, ultimately, and so you want them to be penetration testing code, the changes that they make, the systems that they're building, that's an expensive thing to do,” he explained.

“It takes a lot of time and a lot of setup and execution,” Yanacek added. “Sometimes teams only get to practice only their most critical systems, because it just takes so much time.”

One AWS customer that’s already used the agent, photo-sharing firm SmugMug, was able to conduct penetration testing on multiple applications within the space of hours, rather than days, Yanecek told ITPro.

In simplifying and streamlining this aspect of the development lifecycle, agents are reducing manual toil and freeing up developers to focus on more critical tasks, he added.

“Now we've taken pen test time from weeks to hours, we can just cover more ground, so we can test more changes as they're going through than you could in practice before.”

DevOps gets the agentic treatment

The third and final frontier agent unveiled by AWS today, the AWS DevOps Agent, completes the agentic treatment for the SDLC. This tool aims to streamline DevOps practices, again with a focus on reducing toil for developers.

Similar to the security agent, this has a deep knowledge of user IT estates and applications, identifying relationships between areas such as observability tools, code repositories, and CI/CD pipelines.

It achieves this through mapping application resources, according to AWS, which enables the agent to rapidly respond to failures or bugs that often cause developers headaches.

“The DevOps agent works autonomously when there are alerts or things that will engage a human either in real time or later,” he explained. “It will do root cause incident management, come up with a safe mitigation plan, and shows all of its work along the way.”

Yanacek added that the agent will be proactive and continuously improve, studying previous incidents and identifying potential future issues.

“So it will find things around, maybe cost optimization of infrastructure, saying ‘hey, these are running underutilized’, or, ‘hey, your time to detect has been poor over time’,” he explained.

AWS has tracked an estimated root cause identification rate of around 86% using the agent to date, Yanacek told ITPro. Customers such as the Commonwealth Bank of Australia found that the agent was able to identify the root cause of software failure in just 15 minutes.

“It takes hours for this type of incident [to be identified] that they threw at it to try it out,” he noted. “So we’re seeing success with that.”

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Welcome back to ITPro's live coverage of AWS re:Invent 2025. It's day-two here in Las Vegas, and we've got another action packed morning ahead of us.

Leading the opening keynote today is Swami Sivasubramanian, Vice President of Agentic AI at AWS. He'll be running us through all the developer-focused service and product announcements, and we're expecting another rapid fire session to buckle up.

CEO Matt Garman kicked things off yesterday with updates across all of AWS' key product lines, including Amazon S3 and Bedrock. Naturally, the key focus was new agentic AI capabilities for customers.

AWS customers will be able to get their hands on powerful new "frontier agents" aimed at streamlining software development practices, as well as the ability to build their own frontier AI models using Amazon Nova Forge.

IT modernization was also another key talking point, again with agentic AI capabilities for AWS Transform.

You can read more about all these announcements below.

• Now anyone can build their own frontier AI model

• AWS CEO Matt Garman says AI agents will have 'as much impact on your business as the internet or cloud'

• Amazon S3 just got a big performance boost

• AWS targets IT modernization gains with new agentic AI features in Transform

• 'Frontier agents' are here, and AWS thinks they're going to transform software development

While most of the big announcements from AWS are yet to be revealed this morning, we have had some big updates rolled out for the company's Transform service. First announced earlier this year, AWS has doubled down on the IT modernization platform with an array of new agentic AI capabilities.

As part of the move, enterprises will be given access to powerful new AI features aimed at supercharging legacy code modernization spanning a range of programming languages, with additional tools for mainframe modernization also announced.

You can read more about the latest update to AWS Transform in our coverage below.

• https://www.itpro.com/technology/artificial-intelligence/aws-targets-it-modernization-gains-with-new-agentic-ai-features-in-transform

It wouldn't be a tech conference without some music absolutely blasting out at 7.30am. The keynote theater is filling up now with a torrent of people making their way through the Venetian Hotel.

We're just a couple of minutes out from Matt Garman's keynote now and the excitement is building. A packed conference hall here.

Matt Garman has taken to the stage, hailing the company significant growth over the last year.

"Amazon Bedrock is now powering AI inference for more than 100,000 companies around the world," he says, giving a shout-out to the AgentCore service launched earlier this year. Huge growth within just a few months and thousands of companies flocking to the agentic AI service.

Infrastructure expansion continues at pace, Garman says. In the last year alone the company has added 3.8 gigawatts of data center capacity, more than any other company on earth.

Networking infrastructure is also expanding rapidly, he adds.

"None of what we do at AWS happens without builders, and specifically developers."

"AWS has always been passionate about developers," he adds. This is a key tenet of the company, and with developers fueling the company's sharp AI focus they've never been more important.

Developers face significant challenges, however. They're spending too much time dealing with bottlenecks. Freeing up time for developers is the key to building successful products, Garman notes.

Naturally, AI is helping solve this problem, and with the advent of AI agents the potential here is huge.

"This change is going to have as much impact on your business as much as the internet or the cloud," he says.

So what do businesses need to drive agentic AI adoption? This will be a multi-pronged approach, according to Garman. Starting from the foundational infrastructure level through to data storage and the tools and solutions needed to build and deploy agents.

Of course, AWS has been focusing heavily on all these fronts.

"You have to have a highly scalable and secure cloud that deliver the absolute best performance for your workloads."

And with that we have our first big announcement here at re:Invent, the launch of AWS AI Factories.

“With this launch, we’re enabling customers to deploy dedicated AI infrastructure for AWS in their own data centers for exclusive use for them," Garman says.

“We give them access to leading AWS infrastructure and servers, including the very latest Trainium and UltraServers.”

We’ve moved onto Trainium now, with Garman touting its potential for inference - a big talking point we expected to see here at re:Invent with the focus on Google’s TPUs growing and the company's recent deal with Anthropic.

“We’ve deployed over one million Trainium chips to date,” he says. And AWS isn’t stopping there. “We’re selling those as fast as we can make them.”

Anthropic is also using Trainium chips for AI training and inference through Project Ranier.

And we have another big product announcement today - Trainium3 UltraServers general availability.

"Trainium3 offer the industry's best price performance for large scale AI," Garman says. Big performance gains here.

4.4x more compute, 3.9 times more memory bandwidth. With UltraServers, customers have 144 Trainium3 chips at their disposal - that's 362 PFLOPS and 706 TB/s bandwidth.

AWS is well along on Trainium4 development, Garman reveals. This upcoming range will offer six-times performance, four-times memory bandwidth and 2x memory capacity compared to Trainium3. Huge performance gains that customers can expect to see next year.

Infrastructure is only one part of the story, Garman says as we move onto explore inference, another key focus for the company through its Bedrock service.

More than 100,000 customers are using Bedrock, according to Garman. But it’s the “volume of the usage that’s astounding”, he says.

“We now have more than 50 customers who’ve processed more than 1 trillion tokens through Bedrock. Incredible scale and momentum.”

So how does Bedrock work? It’s essentially a marketplace for in-house and third-party AI models, with customers able to pick and choose based on their own needs.

“We never believed there was going to be one model to rule them all,” Garman says, and Bedrock certainly shows that. It’s doubled the amount of models hosted on the service in the last year, underlining the varied demand from enterprise customers.

And with that we’ve got another big announcement for Bedrock with four new open weight models, including Nvidia's Nemotron and Google Gemma.

Mistral Large 3 and Ministral 3 are also coming to Bedrock Garman reveals.

AWS has its own in-house models, the Nova range, which is getting a big update with the Nova 2 series.

“Nova has grown to be used by tens of thousands of customers today,” he says.

This includes three separate models - Lite for cost-effective reasoning, Pro, the “most intelligent” model for complex workloads, and Sonic, a multi-modal option. Amazon Nova 2 Omni is also coming soon, Garman reveals. This is a multimodal option which excels in reasoning and image generation, perfect for marketers and creatives.

Nova 2 Pro is a key focus here, particularly given its use in underpinning agents, according to Garman. I get the feeling we’re building towards a big agentic AI announcement.

So, you’re an enterprise and want to build your own AI model - seems simple, right? It’s far from it.

Training from scratch is a time-consuming, expensive process and not a realistic expectation for most enterprises.

Building with open weight models help take the edge off, but you can only go so far Garman says.

“You just don’t have a great way to get a great frontier model,” he says. AWS wants to solve that.

Amazon Nova Forge is a new service that “introduces the concept of open training models”. Essentially, you can build your own frontier AI model by combining internal enterprise data with AWS open weight models picking up the slack.

“We’ve already been working with a few customers to test out Nova Forge,” Garman says. This includes Reddit, which has built its own frontier model using the service.

“We think this idea of open training models is going to completely transform what companies can invent with AI,” Garman adds.

We've officially moved onto agents, one of the "biggest opportunities that are going to change everyone's business," according to Garman. The company has already had moves toward ramping up customer agentic AI adoption.

The Bedrock AgentCore service, launched earlier this year, gives customers access to a range of custom built agents as well as the ability to build and deploy their own.

"AgentCore is truly unique in what it enables for building of agents," he says, adding that flexibility and choice is a key focus of the service.

"You only have to use the building blocks you need. We don't force you as builders to go down a single fixed path."

AgentCore is a source of immense excitement at AWS, it seems.

"The momentum is really accelerating," Garman says, with enterprise customers flocking to the platform at a rapid pace since its launch earlier this year.

Security is a recurring talking point with agentic AI, Garman says. Identity security-related considerations and guardrails are causing headaches for security teams as agents weave their way through data sources behind the scenes.

"You can't with certainty control what your agent does and does not go," he says. Giving enterprises tools to set clear boundaries for agents is critical.

With that in mind, the company announces Policy in AgentCore, which allows users to set strict rules for agents to help them "stay in bounds".

Garman is running us through an example here involving an agent operating in a customer service capacity. Users can set a limit on the size of refunds issued by an agent. Hoping to chance your luck and get a refund on something over $1,000? That won't work.

So now that you've secured your agents, how do you track performance? You've invested a lot of money in these shiny new tools, but are they actually delivering a return on investment or even helping customers?

Another new service unveiled today, AgentCore Evaluations, helps enterprises keep track of agent activities and performance based on real-world interactions with customers.

"Evaluations helps developers continuously inspect the quality of their agent based on real world behavior," Garman explains. "Evaluations can help you analyze agent behavior for specific criteria like correctness, helpfulness, harmfulness."

AWS has been quietly working away building its own range of agents in recent months, Garman says. Amazon Quick, for example, assists users in visualizing and analyzing data or automating workflows.

Employees across the company are using Amazon Quick and recording marked benefits so far.

"Today we already have hundreds of thousands of users inside the company," he says. "Teams are telling us they're completing tasks in one-tenth of the time it used to take."

Amazon is also using agents in customer service roles, with Amazon Connect already being used by a range of major customers such as Toyota, Capital One, or National Australia Bank.

"The Connect business passed the one billion annualized run rate mark," Garman says.

Moving onto developers now, Garman says agents have great potential here to help reduce workloads and speed up operations.

This is where platforms such as AWS Transform come in, helping modernize legacy and mainframe code. Thomson Reuters, for example, is modernizing more than 1.5 million lines of code a month during the process of moving from Windows to Linux.

Elsewhere, solutions like Kiro, AWS' AI coding tool, is helping drive developer productivity.

Kiro is one of a growing array of AI coding tools out there on the market in 2025, but Garman says the reception has been huge, with "hundreds of thousands of developers" using the platform globally since launch.

Kiro has been a huge success internally at Amazon so far. Last week, the company made the decision to make it the official development tool for teams across the company.

With agentic AI gains over the last year, there's huge potential for developers, Garman says, especially with "frontier agents".

These aren't your bog standard AI agents, they're more intuitive, autonomous, and powerful - for developers, the Kiro autonomous agent could be a game changer.

This AI agent essentially acts like "another member of your team", according to Garman, learning from the processes and practices from the team to continually improve.

"We think this will help you move much more quickly," Garman says. The agent is going to help shipping more code, more quickly.

But there's more to software development than just writing code, there are key security considerations at play here. The new AWS Security Agent will help underpin safe, secure software development.

"This agent will help you build applications that are secure from the very beginning," Garman says. "It embeds security expertise upstream and enables you to secure your systems more often."

Security Agent also helps with penetration testing, giving developers teams what was traditionally a laborious process one that's now on-demand. Huge improvements to broader software security here, but also speeding up the development lifecycle.

Want to learn more about the new frontier agents from AWS? Check out our coverage and interview on the announcement below.

• AWS says ‘frontier agents’ are here – and they’re going to transform software development

With faster programming and improved security processes, there's only one part of the equation missing. Deployment of software. With this in mind, the new AWS DevOps Agent helps investigate incidents and proactively work to improve application deployments.

We've still got a bunch of launches expected here. Garman says he's going to rally through the next few announcements - 25 in 10 minutes.

"Buckle up everybody," he says. We're going to cut to the chase here and distill things into simple bullet points covering key areas, starting with Amazon S3.

• S3 object size limits are getting a big boost, a 10x boost to 50TB

• That's not all though, Amazon S3 Batch Operations are also now 10x faster

• Elsewhere, Amazon S3 Tables are also getting new intelligent tiering to help with cost optimization

• General availability of S3 Vectors

Elsewhere, we have some big database announcements.

• Increased storage capacities for RDS for SQL Server and RDS for Oracle are coming

• Optimized CPUs for RDS for SQL Server

• A big new database savings plan for customers - savings of up to 35%, according to Garman

And with that, the keynote session is over. We'll be back shortly with a roundup of everything we learned in the opening session. Thanks for following and remembered to keep tabs on our socials and newsletter for all content from AWS re:Invent across the week.

A steady stream of people entering the keynote theater now with just over 30 minutes until Swami kicks things off on day two.

Swami Sivasubramanian has taken to the stage now, asking the audience to think back to the first programme they built. Feeling rather left out at this point...

Good news though, Swami says "who can build is changing" as a result of generative AI and agentic AI. New AI-powered tools are lowering the bar for non-technical individuals.

So how is an agent different from a generative AI chatbot? Swami says imagine that traffic to a website goes down rapidly in a matter of days.

Using a chatbot, the response would be rather basic, but with an agent you'd get a response with deeper context and a concrete plan to solve the problem.

"The chatbot tells you what to investigate, the agent investigates, diagnoses the problem, and initiates the solution," Swami says.

Agents are the next big thing in the tech industry, and as we've seen already this week, AWS appears all-in. But building agents is a tricky process fraught with challenges and potentially disastrous pitfalls.

AWS wants to make that easier for customers, simplifying the process and enabling developers to build their own agents.

Strands SDK, for example, is helping supercharge developer building capabilities. The service was made generally available in July this year, and has seen great uptake already.

Now AWS is doubling down, offering support for TypeScript, one of the world's most popular programming languages. Elsewhere, Strands SDK will offer support for running agents at the edge - big potential in robotics here, Swami says.

Complexity is the biggest issue in building agents, Swami says. It's a long, difficult process in many cases. Ultimately, this slows down innovation.

Bedrock AgentCore seeks to address this, he adds. The service allows customers to build custom agents. The service has proved highly popular since its launch earlier this year and already boasts thousands of customers, Swami says.

"People love it because it works with any agentic framework and any model, giving you the freedom to use the tools that work best on your use case," he tells attendees.

"It's modular, so that you can mix and match using just the pieces you need for your solution," Swami adds. "AgentCore does the heavy work so you can focus on what matters most, creating these breakthrough experiences that solve real-world business problems."

And with that, we have two new capabilities for AgentCore. The first of these includes AgentCore Policy, which helps enterprises set more robust controls for agent interactions and behaviour.

Elsewhere, AgentCore Evaluations will help users keep tabs on how agents are performing, allowing them to fine-tune and tweak based on end-user feedback.

Another quick-fire announcement here with the launch of episodic memory capabilities for agents through AgentCore.

This, Swami says, will essentially give agents longer-term memory capabilities, helping them to remember and learn from past experiences.

Swami gives the example of air travel here as an area this capability could help. Travelling solo? get an agent to book a flight with a fairly quick turnaround at the airport. But travelling with family six months later, that same booking is going to be a disaster. Further down the line, using episodic memory, the agent would realize this and compensate.

Call me cynical, but this is just common sense. Why do you need an agent to remember a previous airport-related farce?

A tangible example of this being used in a business context would be great.

So far we've discussed how AWS is helping customers to build agents. Now we're moving on to look at making them more efficient.

Most agents are focused on basic functions right now, working away in the background, analyzing search results, writing code, or solving basic problems.

Scaling the capability of agents is the next step, giving them the ability to tackle more complex problems.

"Think of it as teaching your AI agent to be a specialist instead of a generalist. Like turning a family doctor into a cardiologist who is laser-focused on exactly what you need," he says.

Starting with pre-trained models makes sense here, and Swami says this is how most teams begin scaling agent capabilities. These are trained on curated agent-specific datasets.

"This creates permanent behaviour changes," he explains. "They don't require lengthy prompts, can dramatically improve performance on specific tasks."

But there's an issue here. Sometimes models can become too focused on specific tasks due to over training.

So what's the solution? Quality over quantity, essentially. Reinforcement learning, Swami says, helps build stronger, more intuitive agents.

"When an agent is troubleshooting a complex issue, you don't just want a final answer. You want the logical diagnostic steps," he says.

This is easier said than done, though. This is a costly process running between six-to-twelve months and requires deep in-house technical capabilities.

AWS has the solution here, who would've thought? Reinforcement fine-tuning is now available in Bedrock, Swami reveals. This will help markedly improve model accuracy and customization of AI agents.

All told, Swami says this delivers 66% accuracy gains. "That is how powerful these techniques are," he says.

Drilling down into deeper levels of customization, Amazon SageMaker AI is a big focus for AWS and customers. A new model customization feature, launching in preview, allows customers to tweak and fine-tune in-house or third-party models.

"With this release, you can customize popular models such as Amazon Nova, Llama, DeepSeek, and deploy them in a just a few steps," he explains.

"This comes with two experiences, and you can choose the right approach based on your comfort level - a self-guided approach for those who like to be in the driver's seat, and an agent-driven experience that uses an AI expert for folks who like to turn on autopilot in their cars."

Tweaking and fine-tuning AI models using AI agents. We're heading down the rabbit hole here.

We're joined now by Byron Cook, VP, distinguished scientist for automated reasoning at AWS, to discuss "neurosymbolic AI" and how the hyperscaler is working to make AI agents more trustworthy.

LLMs, as we know, can be tricked by bad actors, and that has downstream implications for agents. As a result, we introduce guardrails and essentially keep agents on a short leash.

But that limits their ability to deliver positive gains for users.

AWS uses automated reasoning to verify the outputs of the underlying LLM, which often provide instructions for the agents.

Automated reasoning is being used across a range of areas at the company, including storage and virtualization. Essentially critical areas where "failure is unacceptable".

We heard all about the new frontier agents AWS unveiled during yesterday's opening keynote - powerful new tools for developers spanning code generation, DevOps, and cybersecurity.

These will essentially act as teammates in the future, Sivasubramanian says. It's clear the company is pinning its hopes on a big push into the AI coding space with these new offerings.

They've got stiff competition though. Anthropic, OpenAI, Microsoft, GitHub, Google, and the various 'vibe coding' startups taking the industry by storm mean AWS will have stiff competition.

And that's a wrap on the day-two keynote. We've drilled down into a lot of the developer-focused product launches today, and we'll be sure to hear more as the week continues - tomorrow's keynote session is focusing specifically on infrastructure, a huge talking point in the age of AI.

We'll be back shortly with a comprehensive roundup of all the big talking points from both keynote sessions so far this week, so stay tuned!

Amazon Web Services (AWS) has announced a raft of new agentic AI features for its Transform IT modernization service.

Unveiled earlier this year, Transform aims to speed up processes for IT teams overhauling Windows .NET applications, mainframes, and VMware systems.

As part of the update, AWS Transform ‘custom’ capabilities look to accelerate “organization-wide code and application modernization”, the company noted in a statement.

This will enable teams to build custom, specialized AI agents to automate code and application transformation projects. These agents come pre-built for specific programming languages such as Python, Java, or Node.js, and can be tweaked based on company-specific languages.

Speaking to assembled media ahead of the AWS re:Invent conference in Las Vegas, Asa Kalavade, AWS’ VP of migration and modernization, said the new capabilities will help streamline modernization projects, which have traditionally been a time-consuming and expensive process.

“With custom you can create and execute modernization of all your custom code and applications,” she said.

“It’s very easy to use. All you do is define what you want your source [code] to be modernized into, you give some code snippets, you give documentation, you can even point it to a wiki and AWS Transform then comes up with the definition for modernizing this code,” Kalavade added.

AWS customers have unlocked significant gains from the use of the new Transform agentic features so far, according to Kalavade. Air Canada, for example, used the agentic AI features during a huge IT modernization project.

Using AWS Transform, the airline was able to modernize thousands of Lambda functions, recording an 80% reduction in “expected time and cost” for the project compared to a manual migration.

All told, using agents, enterprises can achieve transformation acceleration gains up to five-times faster compared to when conducted manually.

These agents also automatically capture feedback, meaning they can be continually tweaked and improved over time to further drive efficiency.

Mainframe modernization

Elsewhere, the company also announced new agentic AI features aimed at driving mainframe modernization efficiency gains.

This includes three new agents for automating code analysis, business rule extraction, and technical documentation analysis. Among these custom-built agents is one aimed at accelerating legacy code modernization, for example.

A new task agent also looks to “speed up test planning and validation” by automatically generating test plans and data collection scripts, processes which typically take up to half of project timelines, according to the hyperscaler.

Since the advent of generative AI in late 2022, mainframe modernization efforts have taken center stage for enterprises globally. A recent study from Kyndryl, for example, found a third of enterprises believe mainframes have become a critical foundation for running AI workloads.

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AWS has taken steps to boost resilience weeks after a major outage, rolling out a business continuity feature targeting DNS records.

Last month, an outage at the hyperscaler knocked an array of popular services offline – from Signal and Slack to Zoom and even Amazon itself – taking several hours to fully resolve.

The outage stemmed from DNS resolution issues and took place in what AWS calls US-EAST-1 Region, better known as northern Virginia, where plenty of massive data centers are located.

A month on, AWS has announced a new tool to help mitigate future incidents, helping to get systems back online within an hour after DNS issues, specifically in that often troublesome US-EAST-1 Region.

"Today, we’re announcing Amazon Route 53 Accelerated recovery for managing public DNS records, a new Domain Name Service (DNS) business continuity feature that is designed to provide a 60-minute recovery time objective (RTO) during service disruptions in the US East (N. Virginia) AWS Region," said Micah Walter, senior solutions architect, in a post on the AWS blog.

"This enhancement ensures that customers can continue making DNS changes and provisioning infrastructure even during regional outages, providing greater predictability and resilience for mission-critical applications."

AWS touts new tools

Walter explained that the tool targets DNS changes that customers can make within 60 minutes of a service disruption in that region.

"Customers running applications that require business continuity have told us they need additional DNS resilience capabilities to meet their business continuity requirements and regulatory compliance obligations," he said.

When services are disrupted, the new tool offers several benefits. "The feature maintains access to essential Route 53 API operations, ensuring that DNS management remains available when it’s needed most," Walter added.

"Organizations can continue to make critical DNS changes, provision new infrastructure, and redirect traffic flows without waiting for full service restoration."

However, the company also stressed that wasn't a sign of an issue at AWS, but pinned the need for the tool on demand from customers in sensitive industries.

"While AWS maintains exceptional availability across our global infrastructure, organizations in regulated industries like banking, FinTech, and SaaS want the confidence that they will be able to make DNS changes even during unexpected regional disruptions, allowing them to quickly provision standby cloud resources or redirect traffic when needed," Walter noted.

How the new tools work

The system works with existing setups and customers can continue using their existing Route 53 API endpoint without changes to apps or scripts.

"The implementation is designed for simplicity and reliability,” he said. This means customers won’t need to “learn new APIs or modify existing automation scripts”.

"The same Route 53 endpoints and API calls continue to work, providing a seamless experience during both normal operations and failover scenarios."

In the post, AWS noted that accelerated recovery isn't enabled by default, but switching it on for a new or existing hosted zone simply involves switching it on.

"You can enable this feature through the AWS Management Console, AWS Command Line Interface (AWS CLI), AWS Software Development Kit (AWS SDKs), or infrastructure as code tools like AWS CloudFormation and AWS Cloud Development Kit (AWS CDK)," he said.

Accelerated recovery is available now for Amazon Route 53 public hosted zones and is free.

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Amazon Web Services (AWS) is planning to invest up to $50 billion in purpose-built AI and high-performance computing (HPC) infrastructure for the US government.

The data center build, set to start next year, will see an extra 1.3 gigawatts of compute capacity added across AWS Top Secret, AWS Secret, and AWS GovCloud (US) regions across all classification levels: Unclassified, Secret and Top Secret.

Federal agencies will gain expanded access to AWS's AI services, including Amazon SageMaker AI for model training and customization, Amazon Bedrock for model and agent deployment, Amazon Nova, Anthropic Claude, and leading open weight foundation models, with the use of AWS Trainium AI chips as well as Nvidia AI infrastructure.

"Our investment in purpose-built government AI and cloud infrastructure will fundamentally transform how federal agencies leverage supercomputing,” said AWS CEO Matt Garman.

“We're giving agencies expanded access to advanced AI capabilities that will enable them to accelerate critical missions from cybersecurity to drug discovery. This investment removes the technology barriers that have held government back and further positions America to lead in the AI era."

The investment, the company said, will speed up discovery and decision-making across applications ranging from national security to scientific research and innovation, including autonomous systems development, cybersecurity, energy innovation, and healthcare research.

AWS said the move is aimed at supporting the priorities laid out in the US government's recently-published AI Action Plan, which promotes the development of AI infrastructure, as well as other advanced computing initiatives deployed on secure, US-based AI and cloud infrastructure.

AWS boasts deep government ties

The hyperscaler is already a major cloud provider to the US government, serving more than 11,000 government agencies including US intelligence communities, the Department of Defense, federal agencies and defense industrial companies.

In 2011, it became the first cloud provider to build infrastructure specifically for government security and compliance requirements with the launch of AWS GovCloud (US-West).

Since then, it's launched AWS Top Secret-East, the first air-gapped commercial cloud accredited to support classified workloads; AWS Secret Region, making it the first cloud provider accredited across all US government data classifications; and AWS GovCloud (US-East), AWS Top Secret-West, and AWS Secret-West regions.

"Federal customers and the supporting industrial base share a vision of AI and HPC convergence. This includes orchestrating expert AI models, agents, and natural language interfaces to enable researchers and engineers to explore complex problems through conversational interaction," said Amazon.

"This represents a fundamental shift from traditional HPC workflows to AI-accelerated discovery, where scientists can specify challenges and receive AI-driven recommendations backed by high-fidelity simulations and analysis."

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Box and Amazon Web Services (AWS) have announced a multi-year strategic partnership designed to transform how organizations use AI to extract value from their content.

Building on the pair’s existing long-standing relationship – which focuses on delivering enterprise-grade AI capabilities with Anthropic Claude and Amazon Titan – this latest strategic collaboration agreement (SCA) will see the creation of new Box AI agents that leverage AWS’ advanced AI services and infrastructure.

Box has also released a range of new integrations with AWS, including support for Amazon Quick Suite, customization of Amazon Q Developer, as well as compatibility for Amazon Strands, Kiro, and Amazon Bedrock AgentCore.

The intelligent content management (ICM) platform provider said the new capabilities will help customers streamline content-centric workflow automation and improve the quality of actionable insights.

“AI is only as powerful as the context it can access – and that context often lives within the contracts, plans, and ideas that make a business run,” explained Aaron Levie, co-founder and CEO of Box. “At Box, we’re focused on unlocking the insights from enterprise content that enable AI agents to deliver real impact.”

Box said the new AI-powered content solutions and integrations will help organizations extract greater value from their sensitive enterprise data to reap productivity and operational gains – especially those in regulated industries that require high-level security and compliance.

“By collaborating with AWS, we’re giving customers a secure, scalable foundation to turn their content into a competitive advantage,” Levie added.

Agentic integrations

Powered by Amazon Bedrock, the new Box AI agents aim to help organizations automate workflows and create new content directly from enterprise data by summarizing documents, generating multi-document FAQs, extracting metadata, as well as creating intelligent workflows that automate routine content tasks.

Box will also be able to perform advanced multi-modal content analysis through Amazon Nova Multimodal Embeddings to enable insights from diverse content stored within its platform.

From today, joint customers can utilize the new Amazon Quick Suite integration with the Box remote MCP server, enabling them to act on their Box content directly within Quick Suite.

Meanwhile, customization of Amazon Q Developer on the Box SDK and self-hosted MCP server aims to streamline the application building process.

The Box SDK now also includes compatibility with Amazon Strands, Kiro, and Amazon Bedrock AgentCore.

“Today AI agents are transforming how we work," commented Swami Sivasubramanian, vice president of Agentic AI at AWS.

"Through our Box collaboration, we're excited to help customers securely leverage their valuable business content with agentic capabilities, transforming how industries operate by making every piece of content work effectively."

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Amazon Web Services (AWS) is building a new transatlantic subsea cable system linking the US and Ireland known as Fastnet.

Fastnet is set for deployment in 2028 and will link Maryland and County Cork with a line offering more than 320 terabits per second. The cloud computing giant said equates to the entire digitized Library of Congress every three seconds, or 12.5 million HD films at the same time.

The aim of the Fastnet link is to boost capacity but also network resilience, with AWS insisting it will reduce service disruptions for its customers by offering an additional access point in case other cables have issues – a promise that comes weeks after a massive AWS outage caused by a DNS fault.

The cables are part of AWS' growing private network, which began in earnest back in 2016 and now makes up over nine million kilometers of cabling over land and under sea.

AWS noted that unlike the public internet, which requires networking devices to make a routing decision with limited network visibility, its own system uses real-time traffic monitoring for "complete visibility into every link within the global network”.

This, the tech giant said, will help optimize performance and avoid traffic congestion.

AWS eyes scalable networking

AWS said Fastnet makes use of advanced optical switching branching unit technology, a piece of kit that splits traffic via different routes, letting AWS choose the best path by remotely reconfiguring the system.

"This state-of-the-art unit is strategically positioned on the cable route, enabling seamless redirection of data to future landing points as network demands evolve," AWS said.

"This scalable architecture is specifically designed to handle growing AI traffic loads, allowing customers to rapidly expand their data demands while the system adapts to accommodate future growth."

Beyond that, AWS said it has armored the cable with extra layers of steel wires in areas closer to shore to protect against "natural and human activity". That comes a year after two Baltic subsea cables were severed in what appeared to be sabotage.

Notably, the landing point locations in Ireland and Maryland were carefully chosen to offer a route away from traditional cable corridors.

That offers a backup route if other cables have issues, but also lets AWS create a network designed to support growing demands from cloud computing, AI, and edge applications.

Taoiseach Micheál Martin welcomed the announcement, adding that the investment will help “reinforce the resilience of critical digital infrastructure” across the Republic of Ireland.

"By linking County Cork to Maryland in the United States, Ireland will become a true gateway to Europe for submarine telecommunications cables," Martin said.

Wes Moore, Governor of Maryland, added: "Building Maryland’s first-ever subsea fiber cable is an achievement bigger than broadband connectivity — it’s about securing Maryland’s status as a global hub for innovation, job creation, and high-tech investment."

"To grow our economy, we need to prioritize industries of the future," Moore added. "That is exactly what this project helps us deliver, in partnership with leaders with deep local ties and robust commitment to community engagement."

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OpenAI will start using AWS to scale AI systems to answer queries and for training, as the company continues to expand its partnerships beyond Microsoft.

The $38 billion, multi-year deal will give OpenAI access to hundreds of thousands of Nvidia GPUs, with the ability to scale up as necessary, the companies noted.

OpenAI will begin using AWS immediately, with all the capacity targeted to be deployed before the end of this year, and further expansion planned for next year.

"Scaling frontier AI requires massive, reliable compute," said OpenAI CEO Sam Altman in a statement. "Our partnership with AWS strengthens the broad compute ecosystem that will power this next era and bring advanced AI to everyone."

OpenAI noted that the infrastructure that AWS is setting up for OpenAI is designed to boost processing efficiency and performance.

This will be organized into clusters of Nvidia GB200s and Nvidia GB300s via Amazon's EC2 UltraServers, all on the same network for low latency. Those clusters will be designed to support different workloads, from answering ChatGPT queries to training future models, adapting as needed by OpenAI.

"As OpenAI continues to push the boundaries of what's possible, AWS's best-in-class infrastructure will serve as a backbone for their AI ambitions," said AWS chief executive Matt Garman.

"The breadth and immediate availability of optimized compute demonstrates why AWS is uniquely positioned to support OpenAI's vast AI workloads."

Is OpenAI trading Azure for AWS?

OpenAI has had a close partnership with Microsoft since 2019, centered on billions in investment from the firm as well as Azure access. But that partnership lost exclusivity in January and reports of tensions around OpenAI's move to a new structure.

That said, OpenAI continues to use Azure, and last week signed a $250 billion agreement to continue the partnership, but is at the same time expanding its options to avoid overreliance on one hyperscaler.

In recent months, the AI company has signed massive deals with both Google Cloud and Oracle, with the latter worth around $300 billion alone.

AI spending spree

OpenAI's massive contract with AWS further fuels concerns that AI companies are spending too much on infrastructure without the revenue to support such deals, sparking the threat of another tech bubble.

OpenAI runs at a loss, and is expected to post $20 billion in revenue this year, while this time last year it was trying to scrounge up $6 billion in investment just to keep the lights on.

Despite that, Altman said last week that OpenAI had already committed to spending $1.4 trillion over multiple years, which includes deals with cloud providers as well as multibillion-dollar contracts with Nvidia, AMD, and Broadcom.

Altman justified the huge spending spree during an interview with BBC News last month, noting that while the “investment loans are unprecedented…it’s also unprecedented for companies to be growing revenue this fast”.

Earlier this month, ITPro reported that the company was lining up ways to fund its AI ambitions, including adding subscribers, creating a personal AI device, and adding a checkout for AI-powered shopping.

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Microsoft’s latest earnings report might show promising cloud revenue growth, but capital spending has some analysts concerned.

The tech giant’s recent earnings report showed capital expenditure reached nearly $35 billion in the first quarter of its 2026 fiscal year, with expectations that this will continue rising across the year.

This capex spending was revealed amidst strong earnings growth in key segments. Growth in Microsoft’s Azure business surged by 40% in the previous quarter, outpacing analyst expectations. Current quarter expectations are also running ahead of estimates.

According to reports from Reuters, chief financial officer Amy Hood told analysts during an earnings call that growth could have been higher had the company not been burdened by capacity constraints amidst surging demand for compute.

So why is capital expenditure a lingering concern here? According to Forrester principal analyst Tracy Woo, the company’s skyrocketing investment in AI has some investors worried that enterprise uptake might not keep pace.

“Microsoft delivered on expectations but its level of AI investment is cause for concern,” Woo noted. “Average enterprise AI spend is significantly lower than expected – due in part to limited production-ready use cases.”

“This will change but resizes the question of whether Microsoft has invested too heavily and too early in AI.”

There are silvering linings here, however. Woo noted that Microsoft appears to still be benefitting from continued “AI hype” while cloud revenue has made “considerable gains” on AWS figures in recent years.

These revenue gains on what has long been a key competitor in the cloud computing space not only highlights Azure’s growing popularity, but that it’s now emerged as a “major revenue engine” for the tech giant.

This isn’t the first time in the last 18 months that Microsoft has faced investor questions about surging AI investment.

In August last year, the tech giant faced similar questions after capital spending on AI and cloud skyrocketed by 77% in the fourth quarter alone. That earnings call saw the company shuffle reporting of financial results to better showcase gains from AI in a bid to calm inventor fears.

Combine this with the recent capex increases coming in spite of the fact Microsoft predicted a cooling of spending, and for some this begs the question over whether the tech giant is getting bang for its buck at this stage of the global AI roll-out.

Last year, Hood told investors that heavy investment in the technology was required to unlock long-term gains, but noted it could take “over 15 years and beyond” for AI-related revenue gains to be fully realized.

Microsoft isn’t alone

Microsoft isn’t alone in facing questions over capital expenditures as a result of AI investment. Indeed, major industry competitors in this domain such as Google and Meta also reported surging costs across the last 15 months.

Alphabet, Google’s parent company, said “growth across our business and demand from cloud customers” have prompted an increase in projected capital spending, which is now expected to range between $91 billion to $93 billion.

This marks the second time this year the tech giant has hiked capital expenditure projections.

Elsewhere, in Meta’s Q3 earnings report the company said it expects capital expenditure for 2025 will range between $70 billion and $72 billion. Across the year so far, Meta has recorded $50 billion in spending.

Meta CEO Mark Zuckerberg defended this huge spending spree during an earnings call on Wednesday, per reports from CNBC.

“It’s pretty early, but I think we’re seeing the returns in the core business,” he said.

“That’s giving us a lot of confidence that we should be investing a lot more, and we want to make sure that we’re not underinvesting.”

Mike Proulx, VP research director at Forrester, suggested this increase appears to put a dampener on what has been a year of strong momentum for the firm.

“Unfortunately, Meta’s strong revenue and user growth in Q3 is tainted by significantly increased costs across the board,” he said. “True to form, Meta’s Reality Labs continued its streak of losses with no signs of slowing down.”

“Regulatory uncertainty places an ominous cloud over the company as it warned of what could result in a ‘material loss.’ This means headwinds abound for Meta in 2026 after a year of strong momentum,” Proulx added.

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Microsoft has confirmed its Azure cloud services are back online after a major outage impacted services across multiple regions.

It's a tough time to be a cloud provider, with the Azure incident coming hot on the heels of an AWS outage that knocked a wide range of companies and services offline last week.

According to Microsoft, the Azure outage was caused by a CDN configuration error, lasted eight hours, and saw a wide range of Microsoft customers affected, including Alaska Airlines, websites for Heathrow, NatWest, and more.

Even Microsoft's own 365 suite was affected by the outage while proceedings at the Scottish Parliament in Edinburgh were paused due to technical difficulties.

In a service update, Microsoft said error rates and latency are “back to pre-incident levels”, but warned that a “smaller number of customers may still be seeing issues” akin to the turbulent recovery period experienced by AWS customers last week.

The outage was due to a configuration fault in a content delivery network (CDN) system. As with the AWS incident, once the outage started, the interlinked nature of these systems meant the disruption quickly cascaded into a wider problem.

What happened with the Azure outage?

Microsoft has detailed its initial take on the outage on the Azure status page, noting that the incident started at 3.45pm UTC and was spotted within 20 minutes, with manual recovery beginning at 6.45pm. The outage was resolved by midnight.

The outage affected customers and Microsoft services using Azure Front Door (AFD), which is Microsoft's content delivery network service, causing latency issues, timeouts and errors.

"An inadvertent tenant configuration change within Azure Front Door (AFD) triggered a widespread service disruption affecting both Microsoft services and customer applications dependent on AFD for global content delivery," the update said.

Microsoft added that this wasn't spotted because protection mechanisms failed due to a software bug.

"The change introduced an invalid or inconsistent configuration state that caused a significant number of AFD nodes to fail to load properly, leading to increased latencies, timeouts, and connection errors for downstream services."

As the nodes failed, they dropped out of the global pool, meaning traffic distribution across the nodes that remained became unbalanced. Microsoft noted that this exacerbated the outage and expanded the impact, meaning some regions that weren't affected by the AFD issues also saw service degradation.

To recover, Microsoft blocked all configuration changes and rolled back to the "last known good" version, which required reloading across a large number of loads. The recovery was slow to avoid overloading systems as they came back online.

"This deliberate, phased recovery was necessary to stabilize the system while restoring scale and ensuring no recurrence of the issue," Microsoft said, adding it would publish a more detailed review in the next two weeks.

Time to diversify?

With two major outages at US hyperscalers impacting organizations around the world, it's no surprise that questions are being raised about concentrating too much in the hands of a few American tech providers.

AWS holds about 30% of the market, for example, while Azure commands a 20% share, underlining the tight grip both these companies have on the broader cloud computing landscape.

Mark Boost, CEO of Civo, said this latest incident should serve as a warning about diversification within the industry.

"Two of the world’s biggest cloud providers have suffered major outages in the space of a week," he said.

"It’s a wake-up call for governments and enterprises alike, why are so many critical UK institutions, from HMRC to major banks and airports, reliant on infrastructure hosted thousands of miles away?"

Nicky Stewart, Senior Advisor to the Open Cloud Coalition, echoed Boost’s comments on diversification, adding that interoperability and resilience are two key issues that need to be addressed.

"Successive outages on this scale show how a single technical fault can ripple through essential services, public infrastructure, and the wider economy," said Stewart.

"The pattern of repeated disruption underlines the urgent need for diversification, and the CMA must move at pace to implement remedies that foster a more open, competitive, and interoperable cloud market, one where resilience comes from choice, not dependence on the two dominant providers.”

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Hundreds of applications and websites impacted by the AWS outage are now back online and operating as normal. However, questions still remain over the cost of the incident and a growing reliance on a select few cloud providers underpinning the digital economy.

Over the course of Monday morning through to the afternoon, services running on AWS struggled with outages, hitting websites but also payment services.

AWS said the incident was triggered by a DNS issue and that services were largely up and running by the afternoon, though a backlog of messages would take time to work through.

The incident follows last year's CrowdStrike outage and a similar outage by AWS in 2021, highlighting our overreliance on digital systems and networks run by a few companies – a fact noted by many industry experts over the last day or so.

“AWS powers millions of websites and applications, elevating a technical glitch from an inconvenience to a global disruption," noted Forrester principal analyst Brent Ellis.

Ellis added that it was no surprise that DNS was at the heart of the issue.

"This particular outage exposes core issues with cloud resilience that stem from overreliance on services such as DNS, which were not architected for cloud-era technology demands," he said.

A timeline of the AWS outage

The outage began late Sunday night, AWS said in a statement, with increased error rates in what it calls the US-EAST-1 Region, which is northern Virginia – home to a huge swathe of data centers.

By just after midnight, Amazon realized the problem was caused by DNS resolution issues for regional DynamoDB service endpoints, and mitigated it by 2:24am PDT, so by just about half past 10am in the UK. However, the nature of the problem meant recovery took much longer.

"After resolving the DynamoDB DNS issue, AWS services began recovering, but a small subset of internal subsystems continued to be impaired," AWS noted.

"To facilitate full recovery, we temporarily throttled some impaired operations such as EC2 instance launches."

Alongside the EC2 impairments, AWS said it then spotted a problem in Network Load balancer health checks, leading to network connectivity issues in multiple services, including Lambda, DynamoDB, and CloudWatch. Those were fixed by 9:38 am.

"This kind of configuration-level failure, while not unusual in large-scale distributed systems, can cascade rapidly because so many online services rely on shared cloud infrastructure," said Dr Soohyun Jeon, Assistant professor/lecturer in Operation and Information Systems Management, Brunel University of London.

"What begins as a localized fault can therefore manifest globally within minutes, impacting platforms ranging from gaming and social media to banking, telecommunications, and government portals."

As part of the recovery effort, AWS revealed it “temporarily throttled” some operations, including EC2 instance launches and processing of SQS queues through Lambda Event Source Mappings.

“Over time we reduced throttling of operations and worked in parallel to resolve network connectivity issues until the services fully recovered."

The cloud computing giant said services were seeing "significant recovery" by lunch time Monday, and by 3pm PDT all services were back to normal, though many users still reported issues throughout the afternoon.

Who was impacted by the outage?

The widespread reliance on cloud computing providers such as AWS meant the impact was felt online and offline.

An array of major players saw outages on their services and platforms, including Canva, Coinbase, Duolingo, Perplexity, Reddit, Signal, Slack, Zoom and even Amazon itself.

This included issues with its Ring doorbells, Alexa smart assistants, and Kindle books.

Customers of banks including Lloyds and Halifax also reported issues, as did payment apps Venmo and Square. Media sites such as the New York Times and Wall Street Journal also saw errors and outages, as did UK government digital services.

"Even a single failure in a cloud region or streaming backbone can ripple across the stack, impacting everything from data movement to the models and applications that rely on it," said Wadkins.

The financial cost of the AWS outage

The exact scale of the outage in terms of costs to business is yet to be determined, however, previous research shows both website and IT downtime issues can be very costly for businesses.

Douglas Wadkins, CTO at Opengear, said the financial losses are often matched by reputational damage.

"As seen with the widespread disruption today, the consequences of downtime are severe and immediate – lost revenue and customer trust, with potential knock-on effects in today’s fragile macro-economic and geopolitical environment," he said.

Nicky Stewart, the senior advisor at the Open Cloud Coalition, suggested the costs could be eye-watering once fully counted.

"It’s too soon to gauge the economic fallout, but for context, last year’s global CrowdStrike outage was estimated to have cost the UK economy between £1.7 and £2.3 billion," Stewart said.

Overreliance on AWS?

AWS commands a 30% share of the lucrative cloud computing market, with about $29.7bn in quarterly revenue, followed by Microsoft Azure and Google Cloud.

Combined, those three companies control nearly two-thirds of the entire global market. Is that too much? Stewart suggested the incident highlights a growing overreliance on a select few providers.

"Today’s massive AWS outage is a visceral reminder of the risks of over-reliance on two dominant cloud providers, an outage most of us will have felt in some way," he said.

Of course, it's no surprise that companies rely on big players. They’ve been the go-to for enterprise for at least a decade at this stage, underpinning much of the modern digital economy.

But that’s not to say they’re immune to issues or failures, despite impressive uptime records.

"There’s great appeal to using tech giants, but assuming they are too big to fail or inherently resilient is a mistake, with the evidence being the current outage and past ones," noted Forrester's Ellis.

"The entrenchment of cloud, especially AWS, in modern enterprises, coupled with an interwoven ecosystem of SaaS services, outsourced software development, and virtually no visibility into dependencies, is not a bug – it’s a feature of a highly concentrated risk where even small service outages can ripple through the global economy."

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Google Cloud has announced the launch of a new multi-cloud data transfer service for enterprises based in the UK and European Union (EU).

In a blog post Jeanette Manfra, senior director for global risk and compliance at Google Cloud, said the new Data Transfer Essentials scheme comes in direct response to cloud interoperability principles outlined in the EU Data Act.

“Data Transfer Essentials is a new, simple solution for data transfers between Google Cloud and other cloud service providers,” Manfra said.

Notably, under the terms of the EU Data Act, cloud providers are allowed to “pass through costs to customers” for data transfers. Manfra noted that the Google service will come “at no cost to customers”.

Key competitors including Microsoft and Amazon Web Services (AWS) also provide data transfer options for customers. In Microsoft's case these come at a cost to the enterprise, while AWS allows EU customers to transfer data at a reduced rate.

“The original promise of the cloud is one that is open, elastic, and free from artificial lock-ins,” Manfra wrote.

“Google Cloud continues to embrace this openness and the ability for customers to choose the cloud service provider that works best for their workload needs.”

What to expect with Google Cloud's data transfer scheme

According to Google, the new service is specifically designed for “in-parallel” processing of workloads distributed across multiple cloud providers, giving enterprises greater flexibility.

“Data Transfer Essentials enables you to build flexible, multi-cloud strategies and use the best-of-breed solutions across different cloud providers,” Manfra said.

“This can foster greater digital operational resilience – without incurring outbound data transfer costs from Google Cloud.”

Data transfer costs, also known as “egress fees”, have become a point of contention in the cloud computing industry in recent years.

With enterprises flocking to hybrid and multi-cloud strategies, the costs associated with transferring workloads to alternative providers have been a major hurdle.

Indeed, egress fees were a key talking point in a recent probe into the state of the UK’s cloud computing industry. The investigation, conducted by the Competition and Markets Authority (CMA) following an initial probe by Ofcom, found egress fees created significant barriers to multi-cloud adoption.

“Customers face both commercial and technical barriers when seeking to multi-cloud or switch their cloud provider and many currently think that the costs outweigh the benefits,” the CMA reported in early August.

“Barriers to multi-cloud negatively affect many customers’ ability to use and integrate multiple public clouds, and this limits customers’ ability and incentive to exercise choice over their cloud provider."

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Amazon Web Service (AWS) CEO Matt Garman has issued a blunt message to enterprises thinking of replacing junior developers with AI, suggesting it’s the “dumbest thing” he’s ever heard.

Garman's comments came during a recent podcast appearance with Matthew Berman where the chief exec discussed the company’s current AI strategy and the technology’s impact on the industry.

The AWS chief’s stance on the topic follows repeated warnings that AI will disrupt white collar work across a range of industries, particularly entry-level roles where enterprises look to replace junior staff and automate processes.

Anthropic CEO Dario Amodei warned that entry-level workers are firmly in the crosshairs as a result of AI and automation, but it’s safe to say that Garman isn’t convinced.

Focusing specifically on junior developers - another area where notable concerns have been raised - Garman said they represent a vital part of a company’s long-term talent pipeline.

“That’s like, one of the dumbest things I’ve ever heard,” he said. “They’re probably the least expensive employees you have, they’re the most leaned into your AI tools.”

“How’s that going to work when ten years in the future you have no one that has learned anything,” he added.

“My view is that you absolutely want to keep hiring kids out of college and teaching them the right ways to go build software and decompose problems and think about it, just as much as you ever have.”

Garman’s outlook on the matter echoes previous comments from industry figures on future prospects for junior developers.

Earlier this year, outgoing GitHub chief executive Thomas Dohmke said junior developers will still be vital despite claims that AI has the potential to replace them.

Once again, Dohmke’s stance centered around the fact these up-and-coming developers are “AI native” who’ve frequently used the technology during college, or even earlier at school.

AI will be a net positive for enterprises and workers

Garman suggested that AI will ultimately be a net positive for enterprises, providing they avoid reactionary moves like workforce cuts in favor of the technology.

“There’s never been a more exciting time to be in technology,” he said. “I’m on the much more optimistic side.”

A key appeal of the technology lies in taking away the “toil” that workers across a range of professions currently deal with, Garman noted. Equipping them with the technology will enable them to focus on the “things that they’re excited about”.

It’s a common talking point among proponents - and crucially, providers - of the technology over the last two years: freeing people up to do the more ‘rewarding’ aspects of their job or to focus on creative endeavors.

Few have been able to fully articulate how that will work in practice long-term, but Garman still stuck to this particular talking point.

“I think if you look at a lot of white collar jobs today, the vast majority of things that people spend their time doing is not the things that they would ever tell you they get excited about for their job,” he said.

“It’s not putting my numbers into this particular system, or pulling a report together so that I can report on the thing that I’m doing, or trying to collate a bunch of information so that I can actually understand what it is that I want to work on.

“I think people would love to spend more of their time on that creative aspect, on the driving aspect of doing interesting analysis, on doing the parts of their job that they love and not the parts that they don't.”

Ignore the AI code generation hype

AWS has observed positive signs on the appetite for AI tools internally, Garman noted. Around 80% of developers are using AI in their workflows “in some way”, he told Berman.

“Sometimes it's writing unit tests, sometimes it's helping write documentation, sometimes it's writing code,” he said. “And that number is going up every single week.”

AWS isn’t alone on this front, of course. Developers at other major industry competitors such as Microsoft and Google are even going so far as to write code using AI.

Microsoft CEO Satya Nadella recently revealed that over 25% of the company’s internal source code is AI-generated, while Google CEO Sundar Pichai boasted similar figures last year.

But Garman thinks this is a “silly metric” by which companies are measuring the success of their own internal gains with the technology.

“I think for a while, for the last year or two, people have been excited about bragging about the number of lines of code that have been written by AI,” he said. “It’s like a silly metric.”

“There might be bad code, by the way. Measuring lines of code is never actually the best metric. Oftentimes, fewer lines of code is way better than more lines, so I’m never really sure why that’s the exciting metric that people like to brag about.”

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Google has unveiled that its first small modular (SMR) reactor from partner Kairos will be located in Tennessee, with operations beginning in 2030.

Last year, Google signed a deal to purchase nuclear energy from multiple small modular reactors (SMRs) developed by Kairos Power. That's in part to help power data centers, which are demanding ever more energy thanks to the rise in AI.

Google said last year that the deal was for seven SMRs, with the first online by 2030 and the rest following by 2035. Speaking at the time, Michael Terrell, Google's senior director, energy and climate, said this will provide 500MW of power to help "unlock the potential of AI for everyone".

Nearly a year on, the two companies have announced that the first SMR will be at Kairos Power's Hermes 2 Plant in Oak Ridge, Tennessee, offering up to 50MW of energy to Google's data centers in that state and neighboring Alabama, as well as bolstering supply to the wider Tennessee Valley Authority (TVA) grid.

Google’s nuclear plans gain traction

Kairos Power said in a statement that TVA was the first US utility to sign on to buy electricity from such a reactor. The company added that it will boost output at Hermes 2 from 28MW to 50MW with operations scheduled to start in 2030.

Google explained in a blog post that the TVA will purchase electricity from Kairos' Hermes 2 plant beginning in 2030.

"In this initial phase of the collaboration, we will procure clean energy attributes from the plant through TVA to help power our data centers in the region with locally sourced clean energy, every hour of every day," said Amanda Peterson Corio, Google's Global Head of Data Center Energy.

"By developing a technology, a supply chain, and a delivery model that can build an industry to unleash American energy, we can attract and support companies like Google and help America win the AI race," said Don Moul, TVA President and CEO, in a separate statement.

Moul added in the Google blog post that having the financial support of the tech company would help avoid customers having to pay for the high cost of development.

"Google is stepping in and helping shoulder the burden of the cost and risk for first-of-a-kind nuclear projects not only helps Google get to those solutions, but it keeps us from having to burden our customers with development of that technology," he said.

That point could be seen as deflecting criticism that such projects have a negative impact on local residents, particularly around AI demand for energy driving up costs for everyone.

The race for data center energy

Google isn't the only tech giant eyeing nuclear technologies to help power AI. The power-hungry technology is placing significant strain on data centers, prompting a rethink of energy sources in recent years.

Last year, cloud computing giant Oracle revealed it had secured building permits for three SMRs, with the aim of using them to power a 1GW data center.

Speaking during an earnings call at the time, CTO Larry Ellison said a key factor behind the nuclear push was the huge power demands as the company moved from AI training to inferencing, a more energy-intensive process.

Elsewhere, other industry giants are eyeing up the potential of nuclear energy to overcome power constrains.

Microsoft, for example, signed a power purchase agreement (PPE) with Constellation Energy in a move that will see 'unit 1' of the Three Mile Island nuclear plant used to power data center operations.

AWS also hopes to locate a data center next to a nuclear power station in Pennsylvania, though that has faced criticism from local residents and electricity providers over potential price rises.

The use of SMRs aims to help get plants up and running as soon as possible, versus the long lead times of traditional nuclear reactors, but this new technology could prove harder to roll out than existing, tested sustainable sources.

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Amazon Web Services (AWS) still leads the pack in the rapidly-growing Infrastructure as a Service (IaaS) cloud market – but its lead is narrowing.

According to research from Gartner, AWS maintained its lead in the IaaS space across 2024 with a 37.7% market share and revenues of $64.8 billion.

However, analysis from the consultancy showed a poorer performance compared to the year prior, when it held 39% of the market.

While this represents a marginal decline, gains at key competitors highlight growing pressure on the hyperscaler. Microsoft, for example, saw its market share rise from 23% to 23.9% while Google's increased from 8.2% to 9%.

Elsewhere, market share at Alibaba and Huawei also dipped across the year, Gartner found.

“Cloud providers are investing heavily in AI infrastructure and capabilities to become leaders in the rapidly evolving AI-optimized IaaS market," said Hardeep Singh, principal analyst at Gartner.

"They expect that AI will become a much larger revenue contributor in the future, even though it currently remains a relatively small slice of their overall revenue within the IaaS space."

Overall, the worldwide infrastructure as a service (IaaS) market grew 22.5% in 2024, reaching $171.8 billion.

This growth, Gartner noted, is driven by a demand for flexibility with data residency and sovereignty, as enterprises seek to gradually transition to the cloud while keeping control over their data and operations.

"As enterprises continue to seek greater flexibility, improved resilience and optimized performance, there is sustained demand for cloud migration and modernization services," Singh added.

"Enterprises want to transform their IT infrastructure by leveraging multiple platforms for AI and prioritizing modernization by migrating existing workloads to the cloud. They are also deploying cloud native applications across diverse environments.”

Meanwhile, emerging AI-optimized IaaS offerings from non-hyperscalers or GPU as a service (GPUaaS) providers are also playing a key role in addressing immediate capacity requirements by offering flexible, high-performance compute on demand.

Amazon’s cloud dominance faces big challenges

Gartner’s research isn’t the first to point to a declining state of affairs for AWS in recent months. A report from Canalys earlier this year showed sluggish growth rates for the hyperscaler, recording just 17% in the first quarter of 2025.

This not only marked a decrease compared to the 19% recorded in Q4 2024, but came in sharp contrast to growth rates of more than 30% at Microsoft and Google Cloud.

Growth is being driven by both enterprise end-users and providers, said Canalys, with leading hyperscalers ramping up their efforts to optimize infrastructure to accommodate AI adoption.

Amazon is also facing increased pressure in the UK alongside Microsoft over its market dominance.

After a three-year investigation, the UK's Competition and Markets Authority (CMA) issued a report late last month concluding that the two companies have "significant unilateral market power" in the UK's cloud infrastructure services market.

Combined, the two cloud computing giants command a 70% market share, dominating in both the IaaS and PaaS domains, the CMA found.

The competition watchdog recommended that both companies be assessed for Strategic Market Status (SMS), which could lead to targeted interventions to encourage greater competition.

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OpenAI has released two open weight LLMs which can be run on smaller hardware and even the latest AI laptops, with similar performance to some of its recent small language models.

The two models, gpt-oss-120b and gpt-oss-20b, are available under the Apache 2.0 license. ‘Open weight’ in this context means the full training parameters are publicly accessible, intended to improve transparency, safety, and make the models more customizable through fine-tuning.

Each model is a unique offering from OpenAI, which hasn’t released free models since GPT-2 in 2019. The larger of the two, gpt-oss-120b, has 117 billion parameters and can be run on a single Nvidia A100 GPU with 80GB of memory.

OpenAI claims its performance is comparable to o4-mini. In benchmarks published alongside the announcement, the model was shown to outperform o4-mini across health and expert questioning benchmarks, falling behind it slightly on code completion and math tasks.

The smaller model, gpt-oss-20b, has 21 billion parameters and can be run with just 16GB of memory – meaning it can be run on AI PCs or the kind of local hardware that is easily accessible to businesses.

Both models use a mixture of experts (MoE) approach, in which a model is trained to only ever use a specialized subset of its parameters on any given task, for faster inference and less expensive pre-training.

For example, gpt-oss-120b contains 128 total experts but only activates 4 per token, for a total of 5.1 billion active parameters per token.

“gpt-oss is a big deal; it is a state-of-the-art open-weights reasoning model, with strong real-world performance comparable to o4-mini, that you can run locally on your own computer (or phone with the smaller size),” wrote Sam Altman, CEO at OpenAI, in a post on X.

“We believe this is the best and most usable open model in the world.”

OpenAI’s open weight models target cost efficiency

In a post about the models, AWS claimed that gpt-oss-120b offers 10x the price performance of its Gemini counterpart – likely a reference to Gemma – and 18x the price performance of DeepSeek-R1.

OpenAI placed emphasis on the safety of open weight models throughout its announcement post. The firm stated it trained out “harmful data related to Chemical, Biological, Radiological, and Nuclear (CBRN)” and reinforced mechanisms to reject attempted prompt injection.

Open source and open weight AI models come with risk, chief among them being the degree to which they can empower attackers. By tweaking the guardrails and parameters within a model, threat actors can create malicious AI models used for launching more sophisticated attacks.

OpenAI acknowledged this possibility in its post, stating that it attempted to maliciously fine-tune gpt-oss models and found the models could not be used for “high capability” malicious purposes. Three independent groups of experts also weighed in on training safety.

In a further move toward establishing the safety of gpt-oss-20b, OpenAI has opened a red teaming challenge. Ethical hackers have until 26 August to submit evidence of exploits present in the model, for a maximum prize of $500,000.

The gpt-oss models are now available on Hugging Face, as well as Azure, AWS, Databricks among other deployment platforms.

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AWS is attempting to allay fears over its European Sovereign Cloud, promising that it will be operated by EU citizens only.

The service will be the only fully-featured, independently operated sovereign cloud, according to the hyperscaler, backed by strong technical controls, sovereign assurances and legal protections.

Notably, the service will have no critical dependencies on non-EU infrastructure.

As part of the shift, EU citizenship is to be added to the company's hiring requirements for AWS employees operating the cloud. This will ensure that staff with control of day-to-day operations, including access to data centers, technical support, and customer service will be EU residents exclusively, subject to EU law.

"The AWS European Sovereign Cloud is designed to provide customers with an autonomous cloud that operates independently in Europe and for Europe," the company said in a statement.

According to AWS, the move replicates a widely-used mitigation mechanism that's already established in the hiring practices of EU institutions and governments.

In the meantime, the company will continue to work as a blended team of EU residents and EU citizens, with all personnel working from EU locations, before gradually completing the switch to EU citizen operations for the sovereign cloud service.

"We are committed to supporting any employees impacted by this transition, and redeploying builders who do not meet the EU citizen eligibility requirement into other roles within Amazon," said the firm.

AWS said it's on track to launch the AWS European Sovereign Cloud by the end of this year, backed by a €7.8 billion investment through 2040.

The announcement comes as concern rises in the EU that sovereign cloud isn't always as ‘sovereign’ as it should be. The US Cloud Act means that companies can be forced to hand over data, regardless of where it is stored.

Last month, Anton Carniaux, Microsoft France's director of public and legal affairs, admitted that he couldn't guarantee that French citizen data would never be transmitted to US authorities without explicit French authorization.

The admission came during testimony before a French Senate inquiry into the role of public procurement in promoting digital sovereignty.

Recent analysis from Synergy Research Group found that US cloud providers, including Amazon, Microsoft and Google Cloud, hold a 70% share of the European market, compared with just 15% for local firms.

IT leaders are also becoming increasingly concerned about the influence of US-based cloud providers on the European market. More than half of UK IT leaders using public or hybrid cloud setups told Asanti that they’re planning to ditch US firms as a result of data sovereignty concerns.

AWS is keen to impress that its existing relationships with European regulators will be enough to calm worries about US overreach on this front.

"We’ve had deep engagements with European regulators, including national cybersecurity and data protection authorities, and customers to understand their sovereignty requirements and test our sovereignty approach,” the firm said.

“We designed the AWS European Sovereign Cloud to meet these stringent regulatory, data residency, and operational needs."

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The UK Competition and Markets Authority (CMA) has accused Microsoft and Amazon of harming competition in the country’s cloud computing market.

Following a long-running probe into the state of the industry, the regulator warned competition in the space is “not working well”, highlighting an array of business practices it said hampers competition.

The probe pointed specifically to a trend of market concentration in the Infrastructure as a Service (IaaS) space, noting that Amazon and Microsoft command “significant unilateral market power”.

Amazon and Microsoft are the two largest providers in this domain, each of which controlled a share of the market ranging between 30-40%, as of 2024.

The Platform as a Service (PaaS) market also showed signs of concentration, according to the CMA, with Microsoft’s share having increased to 20-30% since 2020.

All told, this market concentration is hampering the ability of competitors to enter the space, the CMA alleges.

“There are substantial barriers to entry and expansion in cloud services, particularly in IaaS as this requires significant capital investment in fixed assets such as data centers, networks and servers, and components which become largely a sunk cost,” the CMA report reads.

“There are also economies of scale, meaning that larger cloud providers have lower average costs compared to smaller providers,” it added.

“The largest cloud providers are making substantial investments in IaaS and AI capabilities to expand their services in coming years, and while this investment can have pro-competitive effects and benefit cloud customers, it may also deter market entry or expansion by potential rivals.”

The enterprise impact of cloud practices

A key focus of the CMA probe has been egress fees. The regulator noted that the number of customers switching suppliers each year was low – only around 1% – it suggested this could be more to do with barriers to doing so rather than businesses’ preferences.

“Customers face both commercial and technical barriers when seeking to multi-cloud or switch their cloud provider and many currently think that the costs outweigh the benefits,” the report noted.

“Barriers to multi-cloud negatively affect many customers’ ability to use and integrate multiple public clouds, and this limits customers’ ability and incentive to exercise choice over their cloud provider."

This applies equally to small businesses and larger enterprises, the CMA said, with the former lacking the financial resources and the latter facing high fees due to the large quantities of data they have stored in the cloud.

In addition to cloud-related concerns, the CMA also took issue with Microsoft’s licensing practices. It argued that the tech giant incentivizes customers to use Windows Server through its Azure cloud service rather than competing options.

This, the regulator noted, “further restricts” the limited choices faced by enterprises.

Recommendations outlined by the CMA report include a further investigation into AWS and Microsoft under the Digital Markets, Competition and Consumers (DMCC) Act.

“We recommend that the CMA Board use its digital markets powers to prioritize commencing SMS investigations to consider designation the two largest providers, Microsoft and AWS, with strategic market status in relation to their respective digital activities in cloud services,” the report states.

Microsoft and AWS hit back at CMA ruling

Microsoft and AWS have hit back at the regulator in the wake of the ruling. A Microsoft spokesperson said the report “misses the mark again”, and claimed the industry has “never been so dynamic and competitive”.

“Its recommendations (also) fail to cover Google, one of the fastest-growing cloud market participants,” the spokesperson said.

“Microsoft looks forward to working with the Digital Markets Unit toward an outcome that more accurately reflects the current competition in cloud that benefits UK customers.”

A spokesperson for AWS issued an equally scathing response to the report, saying it “disregards clear evidence of robust competition” in the UK IT services industry.

“The action proposed by the Inquiry Group is unwarranted and undermines the substantial investment and innovation that have already benefitted hundreds of thousands of UK businesses,” the spokesperson said.

“It risks making the UK a global outlier at a time when businesses need regulatory predictability for the UK to maintain international competitiveness. We will continue to engage constructively with the CMA as they consider their next steps.”

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