25 verified briefings on Cloud Computing. Each story includes a plain-English summary, why it matters, and the concrete action engineering teams should take.
Google Cloud has launched "CPU startup boost" for its Kubernetes Engine (GKE). The feature temporarily provides extra CPU power to applications as they start, speeding up launch times without forcing you to pay for underutilized resources long-term.
The US is investing $5.25 billion to upgrade its national power grid, directly addressing the massive energy needs of new AI data centers. This move aims to prevent power shortages and support the growing AI industry.
Companies are moving beyond AWS and Azure, adopting alternative cloud providers for specialized tasks. This shift helps them cut costs, avoid vendor lock-in, and gain access to better infrastructure for AI and edge workloads.
Google Cloud's 'fluid compute' strategy helps teams avoid AI hardware shortages. It lets developers design workloads that can flexibly run on different available accelerators, like GPUs or TPUs, preventing costly project delays.
Amazon is reportedly trying to rehire workers it recently laid off, especially for key AI and cloud positions. This move signals a potential strategic error and highlights the fierce, ongoing competition for specialized technical talent.
AWS Lambda functions can now run for up to 90 minutes, a sixfold increase from the previous 15-minute limit. This major update opens up serverless computing for long-running data processing, machine learning, and other intensive workloads.
AWS has released new T8i instances, offering up to 30% better price-performance than older T3 instances. Powered by custom Intel chips, they are designed for common workloads like microservices and development environments, providing a low-cost option.
Amazon Web Services is massively expanding its AI infrastructure, planning to add two million more Nvidia GPUs by 2028. This move signals the immense, ongoing demand for AI computing power among cloud customers.
Amazon EC2, the service that launched the public cloud, just turned twenty. It started with a single server type in one location and has since become the foundation for millions of applications and businesses worldwide.
Oracle co-founder Larry Ellison lost $104 billion in two months as the company's stock fell 54%. The drop reflects market uncertainty over Oracle's high-stakes, capital-intensive strategy to compete in the AI infrastructure race.
Oracle is installing a Quantinuum quantum computer directly into its cloud infrastructure. The move aims to give enterprise customers on-demand access to quantum power for demanding AI and high-performance computing workloads, simplifying a complex technology.
AI startup Mirendil is spending over $100 million on Google Cloud to build self-improving AI systems. The deal highlights the massive computing power now required for next-generation AI research aimed at accelerating scientific discovery.
Vercel has significantly increased the capacity of its Sandbox feature for Pro and Enterprise users. The update allows for 10,000 concurrent sandboxes and a tenfold increase in CPU allocation, enabling more complex, large-scale applications like AI tools.
AI workloads are demanding so much power that traditional data centers can't keep up. This is forcing a complete rethinking of infrastructure, from energy supply to cooling, impacting future cloud costs and availability for everyone.
AWS Lambda no longer enforces its 75 GB per-region code storage quota for functions stored in your own S3 bucket. This change helps large organizations scale their serverless applications without hitting a previously restrictive account-wide limit.
AWS has launched a new managed service called FinOps Agent. It automatically investigates cost spikes, finds the cause, and sends alerts to the right teams through tools like Slack and Jira to help control cloud spending.
AWS is now the first cloud provider to offer servers with PCIe 6.0, beating rivals like Intel and AMD to the milestone. The new Graviton5 instances provide significantly faster data transfer for demanding workloads.
A data center firm is spending $500M to convert 15 former crypto mining sites into AI cloud facilities. The deal highlights the intense competition for the massive power and infrastructure needed to fuel the AI boom.
Microsoft has updated its Azure Kubernetes Service with new features for AI, bare metal servers, and managing multiple clusters. This helps teams run more demanding applications and simplifies large-scale operations on the cloud.
Google and UC San Diego are building a private cloud using 2,000 retired Pixel phones. This project explores a sustainable, low-cost way to create computing infrastructure and reduce electronic waste from discarded smartphones.
Azure Functions now has a serverless agents runtime in public preview. It lets developers build AI-powered automations without the usual cold start delays or extra costs on the Flex Consumption plan.
Google has made its long-hidden flight simulator, a feature of the desktop Google Earth app since 2007, available directly in web browsers. This makes the powerful tool accessible to anyone without needing a separate download or installation.
Microsoft Azure now offers sandboxes to safely run untrusted code from AI agents. The isolated environments start in under a second, scale massively, and cost nothing when idle, making AI experimentation much safer for developers.
xAI has signed a multi-billion dollar deal to provide its competitor, Anthropic, with large-scale AI computing services. The agreement, worth about $1.25 billion per month until May 2029, signals a major shift where specialized AI compute is emerging as a standalone business, challenging traditional cloud providers.
Generative AI media platform fal has named AWS its preferred cloud provider. The partnership aims to address the significant infrastructure and compute demands required for real-time AI media generation, supporting fal's 2.5 million developer users and simplifying GPU management.