AWS said the problem started after temperatures rose inside a single data centre, blaming a cooling system failure while explaining that engineers brought extra cooling capacity online as recovery work continued.

The outage affected services in one Availability Zone, which is a group of connected data centres designed to operate separately within an AWS region. AWS said it redirected traffic away from the affected zone for most services to reduce disruption.

Later in the day, recovery was taking longer than expected because more cooling capacity was still needed before remaining systems could safely return online. AWS further added that it did not yet have a timeline for full recovery.

Coinbase confirmed its trading platform issues were directly linked to the AWS outage. Users reported problems accessing services and delays during trading, although the company later said all markets had been restored and trading resumed normally.

Meanwhile, CME Group reported login and latency problems on its CME Direct trading platform. In a notice to users, the exchange said it had completed “essential maintenance work” and confirmed customers could log back in. The company did not explain the cause of the disruption.

Neither AWS nor CME immediately responded to requests for additional comment outside normal business hours.

The incident again exposed how heavily large financial platforms depend on cloud providers such as AWS. Even a problem in a single data centre zone can spread quickly across trading services, apps and online platforms used worldwide.

AWS has faced similar problems before. In October last year, a major outage disrupted thousands of websites and apps, including Snapchat and Reddit. That disruption became one of the largest internet outages in recent years.

A month later, CME Group experienced another major interruption after cooling systems failed at a data centre operated by CyrusOne in the Chicago area. Trading across stocks, bonds, commodities and currencies stopped for several hours.

The latest outage also points to stress on data centres as companies expand artificial intelligence systems and use more high-density servers, which generate far more heat and demand stronger cooling systems.

AWS has advised customers to spread workloads across multiple Availability Zones and regions to reduce the risk of large-scale disruptions when outages happen.

Before now, Microsoft helped fund OpenAI’s rapid growth and used early access to its systems to build new tools across Windows, Office, Azure and other products.

Under the new agreement, Microsoft will remain OpenAI’s main cloud partner, but it will no longer have sole rights to host or distribute OpenAI technology.

That means OpenAI can now reach customers already using other cloud providers, instead of asking them to move to Microsoft Azure first.

Even so, OpenAI products are still expected to launch first on Azure unless Microsoft cannot, or chooses not to, support them.

Microsoft will also keep a non-exclusive licence to OpenAI’s intellectual property until 2032.

Another key change concerns money as Microsoft will no longer pay OpenAI a share of revenue from its own AI-related products. At the same time, OpenAI will continue paying Microsoft a 20% revenue share until 2030, though that amount now has a fixed upper limit.

Following the announcement, Microsoft shares fell about 1% in premarket trading on Monday, while Amazon and Alphabet, Google’s parent company, edged higher.

This means Microsoft has lost a strategic advantage, while its competitors now have a stronger path to offer OpenAI products through their own cloud services.

Still, aside from the exclusive deal, Microsoft is deeply tied to OpenAI. The software company owns about 27% of OpenAI, a stake estimated to be worth around $225 billion after OpenAI’s corporate restructuring last year.

The two companies have faced limitations in recent months, with reports in March saying Microsoft had considered going to court over a proposed $50 billion cloud deal involving Amazon and OpenAI that could have conflicted with earlier exclusivity terms.

There were also signs of stress inside OpenAI. Internal discussions reportedly revealed frustration that the old arrangement limited sales opportunities, especially among companies already committed to AWS or Google Cloud.

For OpenAI, the new structure provides room to expand faster and sell across more platforms.

For Microsoft, the deal removes exclusivity but secures long-term access to OpenAI technology while putting clearer limits on future payments.

For customers, it means more choice and less pressure to rely on a single cloud provider.

The agreement will see Meta use tens of millions of Graviton processing cores, according to Amazon Web Services executive Nafea Bshara, who said the contract would run for several years and be worth billions of dollars.

Demand for AI infrastructure is spreading beyond graphics processors made by firms such as Nvidia, while GPUs are essential in training AI models. Companies now need large volumes of central processing units to run trained systems, manage workloads and support AI agents.

Meta said the deal is part of its strategy to avoid relying on one supplier or one type of chip.

“As we scale the infrastructure behind Meta’s AI ambitions, diversifying our compute sources is a strategic imperative,” Santosh Janardhan, head of infrastructure at Meta, said in a statement.

Amazon said Meta chose its latest Graviton5 processor because of its price and performance. The chip is Amazon’s fifth in-house CPU generation and is produced by Taiwan Semiconductor Manufacturing Co.

“We pass that savings on to the customers,” Bshara told Reuters.

He added that most of the chip capacity for Meta would be based in the United States.

The partnership builds on an existing relationship between both companies that dates back several years. Earlier work had focused mainly on cloud services, Amazon’s Bedrock platform and GPU rentals.

For Meta, the latest agreement adds to its list of chip partnerships. The company has already signed major supply deals with Nvidia and AMD, while also working with Arm Holdings.

Amazon, meanwhile, is going deeper into AI infrastructure with both its own silicon and outside partnerships. Earlier this week, it announced another $5 billion investment in Anthropic, which will also use tens of millions of AWS Graviton cores.

The agreement, which expands a partnership the two companies began in 2023, strengthens Amazon’s place in the fast-growing market for advanced computing services.

Amazon said it will invest $5 billion in Anthropic immediately, with a further $20 billion available later if agreed commercial targets are met. That comes on top of the $8 billion Amazon has already invested in the company.

Anthropic, the maker of Claude, said it will use current and future generations of Amazon’s Trainium chips to train and run its models, expecting to secure up to five gigawatts of computing capacity over time.

The company also confirmed that one gigawatt of capacity using Trainium2 and Trainium3 chips should be available by the end of this year.

Giving Anthropic more access to the large-scale infrastructure needed to support high demand, Amazon gets a major long-term customer for its custom-built chips and cloud services.

More than 100,000 customers already use Anthropic’s Claude models on AWS, according to the companies.

Customers will also be able to access Anthropic’s Claude Platform directly through AWS accounts, allowing them to use existing billing, security controls and monitoring tools without separate contracts.

Amazon has invested heavily in expanding data centres and computing power as demand for advanced software tools rises. The company recently said it expects around $200 billion in capital spending this year, with much of that linked to technology infrastructure.

Chief Executive Andy Jassy said Anthropic’s long-term use of Trainium chips showed the progress both companies had made together.

“Our custom AI silicon offers high performance at significantly lower cost for customers, which is why it’s in such hot demand,” he said.

“Anthropic’s commitment to run its large language models on AWS Trainium for the next decade reflects the progress we’ve made together on custom silicon, as we continue delivering the technology and infrastructure our customers need to build with generative AI.”

Anthropic Chief Executive and co-founder Dario Amodei said demand for Claude continued to grow quickly.

“Our users tell us Claude is increasingly essential to how they work, and we need to build the infrastructure to keep pace with rapidly growing demand,” he said.

“Our collaboration with Amazon will allow us to continue advancing AI research while delivering Claude to our customers, including the more than 100,000 building on AWS.”

Amazon shares rose about 2.7% in extended trading after the announcement.

According to AWS’s official status dashboard update, two facilities in the UAE were directly struck by drones, while one facility in Bahrain sustained physical damage from a nearby drone strike.

The company stated: “These strikes have caused structural damage, disrupted power delivery to our infrastructure, and in some cases required fire suppression activities that resulted in additional water damage.”

This marks one of the first publicly confirmed physical military attacks on a major hyperscale cloud provider’s infrastructure.

The incidents affected the AWS Middle East (UAE) Region (ME-CENTRAL-1) and the AWS Middle East (Bahrain) Region (ME-SOUTH-1), leading to outages and degraded performance for services including EC2, S3, DynamoDB, Lambda, and RDS.

AWS has described the recovery as prolonged and unpredictable due to ongoing regional instability.

Customers have been advised to activate disaster recovery plans and migrate workloads to other AWS regions where possible.

Impact on Businesses and Users

The attacks caused service interruptions for banks, delivery apps, government services, and enterprises across the Gulf that depend on these availability zones.

With data centres becoming strategic targets in modern conflicts, this incident highlights the physical vulnerabilities of cloud infrastructure, even for tech giants like Amazon.

AWS and local authorities have not reported casualties from the strikes.

For African businesses and developers heavily reliant on AWS; common for Nigerian fintechs, startups, and enterprises routing through global cloud providers, this serves as a reminder of geopolitical risks.

Experts recommend multi-region redundancy and regular failover testing to avoid similar disruptions.

Amazon has not released detailed images or extent of damage, citing security reasons.

Recovery efforts were reported as making progress in some areas, but full restoration timelines remain unclear.

This new collaboration combines trusted digital security from G+D with best-in-class cloud agility and scale from AWS, enabling customers to confidently deploy and manage devices with eSIM connectivity worldwide.

Under this new collaboration, G+D will transition eSIM workloads to the AWS cloud environment.

This newly launched solution combines G+D’s focus on GSMA compliance and foundational security with AWS’ secure, high availability cloud infrastructure to deliver global provisioning and low-latency connectivity solutions across multiple geographies.

“As the pioneers in SIM and eSIM, and the undisputed leader in security for more than 170 years, we are delighted to be achieving another industry first today through our collaboration with AWS,” added Philipp Schulte, CEO G+D Mobile Security. “By bringing eSIM to the cloud and increasing agility and scalability, we will accelerate eSIM adoption in both consumer and IoT applications, providing a secure, future-proof and cost-effective solution for our customers. Together with AWS’s innovative solutions, customers benefit from an unparalleled offering that adapts quickly to their evolving requirements.”

The growth of eSIM-only devices across global telecommunications markets during the last year has driven a significant shift towards industry adoption of eSIM for both consumer and IoT applications.

Telecommunications operators increasingly need faster onboarding and elastic scaling of eSIM deployment, especially during peak demand periods.

Ensuring end-to-end security is also critical for the rollout of SGP.32 (IoT eSIM) and SGP.22 (consumer eSIM) compatible devices.

Gordon Mansfield, VP Global Technology Planning at AT&T commented,

“We have been successfully using G+D eSIM services for more than a decade. eSIM has passed the tipping point to become the primary means of connecting to our network. The means to distribute services across multiple GSMA certified cloud locations represents a significant opportunity for us to expand our offering globally across a broad range of verticals. The fact that we will also be able to source now G+D’s market leading technology directly from the AWS marketplace means a breakthrough in terms of time to market on a global scale.”

“Giesecke+Devrient’s launch of this global IoT connectivity solution demonstrates how AWS’s secure, scalable infrastructure is enabling innovation in the telecommunications industry,” said Jan Hofmeyr, Vice President, Telecommunications at AWS. “G+D’s reputation as a global leader in advanced security solutions, combined with AWS’s scalable cloud capabilities, creates a powerful foundation for expanding eSIM connectivity across consumer and IoT applications. This collaboration reflects the growing momentum we’re seeing in the industry towards cloud-native approaches to IoT connectivity.”

This new agreement expands the collaboration between G+D and AWS. G+D is already deploying its SGP.32 eSIM technology for Amazon’s eero Signal device, marking one of the first commercial deployments of the technology.

G+D will also offer its solutions via the AWS Marketplace, ensuring widespread accessibility to the technology for mobile carriers, enterprises, and IoT service providers.

The newspaper said the incidents resulted from errors involving Amazon’s own tool, known as Kiro. In one case in mid-December, AWS customers experienced a 13-hour interruption.

Engineers had allowed the tool to carry out certain system changes. It then decided to “delete and recreate the environment”, the report said, which led to the disruption.

AWS disputed that account.

In an emailed response to Reuters, a company spokesperson said the disruption was brief and blamed it on user error. “This brief event was the result of user error-specifically misconfigured access controls, not AI.”

The spokesperson added that the interruption was “an extremely limited event” affecting a single service in one of AWS’s two mainland China regions. It did not impact compute, storage, database, AI technologies, or any other AWS services, the company said.

The December incidents follow an outage in October that disrupted Amazon’s cloud operations globally. That earlier failure affected Amazon’s own services and several high-profile apps, including Reddit, Roblox and Snapchat.

AWS is the cloud division of Amazon and supports a large share of the internet’s infrastructure. Because of that reach, even short interruptions can affect millions of users and businesses.

Both Amazon Web Services outages in December have drawn attention because they involved automation tools that can act with limited human input.

Cloud providers have been expanding the use of such systems to manage complex infrastructure. At the same time, customers expect stability and clear accountability when problems occur.

Competitors including Microsoft Azure and Google Cloud are also developing automated tools to manage their platforms.

AWS maintains that the December disruption resulted from misconfigured access controls, not from the coding tool acting on its own.

Nearly 94% of enterprises run cloud services, and platforms like Amazon Web Services (AWS) command 29% of that market globally.

The cloud market is expected to grow to nearly $947 billion by 2026, buzzing with opportunities for builders, architects and developers alike.

However, we can’t take out the fact that humans are the ones driving those statistics. True careers built in real time.

Chibuike Nwachukwu has a typical story, giving a raw, instructive lens into what it takes to build a world‑class career in cloud, software engineering and modern tech at scale.

“I love games.”

That was the spark. Not elasticity, global scale, or distributed systems. Games.

Chibuike jokes now about how naive that beginning sounds. When he applied to university, he had two choices, Computer Engineering or Computer Science.

He chose the latter because he believed, “Computer science would be less intensive and allow me to play more games.” 

That simple desire laid a seed. Only later did he realise the kind of problems he’d end up solving would have little to do with fun and much more with resilience, performance and user impact.

In his first year of university, he met a friend who was already coding. They formed a small group of enthusiasts, initially dozens, later just four or five serious coders.

They built projects, taught others, got paid for solving problems like coursework automation or logging systems for departments. And something clicked! Software engineering was real work, not just lectures in a classroom.

By the time he graduated in late 2018, Chibuike was not just a graduate but a professional software engineer.

Early Lessons in Scale

His first professional role was with an education‑tech platform in Lagos. The problem was embedded in exams and quizzes for banks and government agencies. The reality was anything but.

When thousands of users logged on near deadlines, the system crashed repeatedly. For people unfamiliar with theory lectures, this was the moment Chibuike learned scale is important.

Proper indexing, smart database design and efficient request handling were no longer academic but now business‑critical. If the system buckled, users couldn’t complete exams. Managers knew just how much a bug could cost careers.

That lesson impacted how he codes today, conscious, careful, customer‑aware engineering.

From there Chibuike moved into proptech platforms, finance technology stacks and telehealth systems. In each domain, the same question drove his work: can this system scale reliably when people depend on it?

Finding a Home in the Cloud

Cloud engineering didn’t appear on the radar of Chibuike Nwachukwu as a “career choice”. It crept in as a necessity.

Software has to run somewhere, and more, that somewhere is the cloud. AWS became his platform of choice because it was built for scale, global reach and reliability. Over time, the cloud moved from a deployment environment to the core of his professional identity.

It was around 2021 when Chibuike’s work started aligning with AWS’s services and philosophies. He joined AWS communities, absorbed real‑world architecture patterns and began giving back through open source contributions, articles and talks that go beyond buzzwords.

For him, AWS wasn’t just “where I deploy code”. It became the benchmark of scalable solutions.

Globally, AWS, Microsoft Azure and Google Cloud now take up most of the cloud market, with AWS leading at roughly 29% share in 2025.

The Discipline Behind Certification

Chibuike has earned every AWS certification, a commendable achievement he says is more about structure than badges. In his own words: “Certificates were just basically what I call a guide as to what to learn and how to learn them properly.”

What he discovered in those exams was a solid truth of engineering, real‑world solutions demand efficiency, cost‑optimised design and security by default.

Too often, he found that “your solution may work but be inefficient or costly, and AWS exams penalise that.”

Earning those credentials didn’t replace experience but complemented it. The faint pride after his fourth certification turned into a full‑blown drive to complete them all.

Build First, Then Talk

It’s easy to spot tech thought leaders who are all talk and no code. Chibuike isn’t one of them. From serverless voting systems designed to mitigate election fraud to AI‑driven education tools that summarise study materials, he builds first and explains later.

One such project explored applying serverless cloud principles to elections, capturing faces, mapping them to national IDs, and using serverless pipelines to verify and tally votes in real time.

The goal was to have an in-depth knowledge of how distributed, resilient systems behave under real traffic patterns, not just to create perfect political infrastructure.

Another project helped exam candidates upload PDFs, slides and video links to generate practice questions and context‑aware explanations, blending generative AI with AWS services. “It had to solve a real problem,” he says, emphasising utility over buzz.

This philosophy also boosted his public speaking. He didn’t start out as a natural presenter. In fact, he describes himself as quiet initially. But over the past few years, from virtual meetups to global conference stages across three continents, he’s used talks to discuss technical work, not inspirational-talk-based.

He stresses: “Focus more on having the skills, like really building solutions, as opposed to saying ‘how to get into tech’ with little substance.”

Tough Lessons, Real Consequences

The hardest moments for Chibuike Nwachukwu weren’t failures on tests or deployments in cloud engineering and other areas. Interestingly, they were the realisation that poor code can affect people’s lives.

“You’re not just building code. You’re affecting other people’s lives,” he told me.

A bug in an exam system could derail promotions. A failing API could cost doctors time with patients. And the stakes forced him to learn discipline, testing, communication and process matter as much as technical skill.

What Separates the World’s Best from the Rest?

For Chibuike, two things, hard work and homework. Not shortcuts.

He’s seen engineers with months of social media followers who struggle with even basic technical challenges when real systems break under load. In his view, those who grow globally are those who build solutions, solve pain points, and demonstrate depth.

Advice for African Engineers Eyeing Global Careers

1. Join communities. They’re gateways to opportunities, mentorship, credits, talks and collaboration.

2. Build real solutions. Projects are more important than profiles.

3. Write and share your work. Articles and open source contributions are the strongest personal portfolios there are.

For Chibuike, Africa is not a limitation but a vantage point. “We just need to build and push, and everyone can see your solution.”

What’s Next?

Though he’s candid about watching the evolution of AWS and AI closely, he sees promise in innovative cloud solutions more than in flavour‑of‑the‑month trends.

His goal now is to maintain and strengthen mastery, to build systems that matter, to simplify complexity for others and to keep solving problems that scale.

The announcements cover hardware, software, cloud services, and partnerships with companies like Lyft, Sony, and Visa.

The focus this year is on giving businesses better management over AI systems. AWS CEO Matt Garman spoke about how AI agents can drive tangible business results.

“AI assistants are starting to give way to AI agents that can perform tasks and automate on your behalf,” he said during the keynote. “This is where we’re starting to see material business returns from your AI investments.”

Powerful Chips and UltraServers

AWS introduced the Trainium3 chip and UltraServer systems, promising up to four times faster AI training and inference while using 40% less energy.

Trainium4, already in development, will be compatible with Nvidia’s chips, signalling AWS’s intent to bridge proprietary and third-party hardware ecosystems.

AI Agents Evolving

AWS also expanded its AgentCore platform. Features like Policy allow developers to set clear boundaries for agents, while new memory and evaluation capabilities let AI agents remember interactions and be tested against 13 prebuilt evaluation systems.

Among the new “Frontier agents,” the Kiro autonomous agent stands out, writing code and learning team workflows to operate independently for hours or even days. Additional agents focus on security and DevOps tasks, helping teams prevent errors and manage operations more efficiently.

Nova AI and Customisation

Amazon’s Nova family of AI models grows with four new releases, including three text-generation models and a multimodal model that handles text and images. Nova Forge introduces “open training,” enabling organisations to fine-tune pre-trained models with proprietary data.

Companies like Reddit and Hertz are already leveraging Nova to replace multiple specialised models or accelerate development velocity.

Real-World Applications

AWS customers demonstrated practical impacts. Lyft’s AI agent, built with Anthropic’s Claude model via Amazon Bedrock, now resolves driver and rider queries 87% faster and has increased driver adoption by 70%.

Christina Minardi from Amazon noted sustainability applications: “By working with Trane Technologies and the BrainBox AI team, we’re turning our buildings into intelligent systems that learn and adapt, helping us meet both our sustainability and performance goals in real time.”

Other partners showcased broad enterprise use cases. Sony is deploying AWS-powered AI platforms internally and through the Sony Engagement Platform, processing 760 terabytes of data daily to enhance fan experiences.

Nissan’s cloud-based software platform for vehicles has reduced testing time by 75%, while Visa and AWS are enabling AI agents to conduct secure, autonomous transactions.

Data Control and Sovereignty

AWS also introduced AI Factories, which allow companies and governments to run AWS AI in their own data centres. Combining Nvidia GPUs with Trainium3 chips, the system meets regulatory and data sovereignty requirements without sacrificing performance.

Cloud Services and Storage Upgrades

Several AWS services received significant updates. Amazon S3 now supports objects up to 50TB and scales to two billion vectors per index for AI search, while S3 Tables introduces automatic replication and cost-optimising Intelligent-Tiering.

CloudWatch unifies operational, security, and compliance logs for easier insights, and EMR Serverless eliminates local storage provisioning for Apache Spark jobs, cutting costs by up to 20%.

Enhanced Support and Security

AWS also announced upgraded support plans, combining faster AI-assisted responses with expert guidance. Amazon GuardDuty Extended Threat Detection now covers EC2 and ECS environments, while Security Hub offers near real-time risk analytics across multiple AWS services.

Expanding Partnerships

Adobe, Deepgram, BlackRock, and WRITER highlighted collaborative initiatives. Adobe is using AWS for AI-powered creative tools, Deepgram for enterprise voice solutions, BlackRock for Aladdin investment technology, and WRITER for securely scaling enterprise AI agents.

The announcements underline AWS’s strategy to embed AI across infrastructure, enterprise software, and real-world operations.

Starting from autonomous coding agents to sustainability-driven building systems, the AWS re:Invent 2025 conference revealed how businesses are starting to rely on AI agents not just as tools, but as autonomous collaborators.

With many companies looking for stronger safeguards after recent internet disruptions exposed weaknesses in single-cloud setups, the launch comes just in time.

Both firms said the service allows customers to build secure, high-capacity connections between Amazon Web Services (AWS) and Google Cloud in minutes. Before now, many organisations waited weeks to complete the same process due to the technical and approval delays tied to cross-cloud circuits.

Just over a month ago, AWS suffered a major outage on October 20 that spread through its US-East-1 region. A faulty update to DynamoDB’s API triggered DNS failures across the zone, breaking more than 113 AWS services and knocking out platforms such as Snapchat, Reddit, Coinbase and Alexa. 

Analysts estimate the disruption costs U.S. companies between $500 million and $650 million. For many firms, the incident revealed the risk of placing all operations on a single cloud provider.

In response, interest in multicloud resilience has grown. The new service blends AWS’ Interconnect–multicloud with Google Cloud’s Cross-Cloud Interconnect. The aim is to remove friction for organisations that want systems running across several clouds without slow setup cycles or unpredictable routing.

AWS vice president of network services, Robert Kennedy, said the development points to a major shift in how cloud platforms interact. “This collaboration between AWS and Google Cloud represents a fundamental shift in multicloud connectivity.”

Google Cloud also noted the benefit for companies moving large volumes of data between providers. Its vice president and general manager of cloud networking, Rob Enns, stated that the joint framework is meant to simplify workload mobility. Salesforce is one of the early adopters of the new model, according to Google.

Cloud competition is highly intense. AWS continues to top the global market with roughly 29–30% share, while Microsoft Azure holds about 20% and Google Cloud has climbed toward 13%. 

In the third quarter alone, the cloud infrastructure market was valued at around $107 billion, controlled largely by these three companies.

Heavy investment in infrastructure is expected to continue. Increasing demand for artificial intelligence is pushing cloud providers to expand data centres, improve capacity and strengthen network routes. 

AWS recently committed to a multi-year $38 billion partnership with OpenAI, offering access to large clusters of Nvidia GPUs. Google and Microsoft are making similar bets, as AI workloads remain one of the biggest drivers of cloud growth.

In working together on a cross-cloud standard, Amazon and Google have taken an unusual step. The two companies are long-standing competitors, but the new partnership shows a shared interest in reducing latency and making multicloud operations easier for enterprise customers. 

For large users like Salesforce, the ability to deploy cross-cloud links in minutes rather than weeks may prove decisive as businesses seek more resilient infrastructure after recent outages.