# sponsor-aws-marketplace Published articles for sponsor-aws-marketplace. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust DevFeed: [How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust]() Original publisher: [Read original article]() Author: Prashant Kumar Singh Published: 2026-09-11T12:00:00Z Content type: article Language: en Sources: [The New Stack]() Topics: [AWS Lambda](), [Architecture & Design](), [SIEM, Security, Observability](), [telemetry](), [Amazon EC2](), [Amazon S3](), [VPC]() Tags: [architecture](), [aws](), [aws-lambda](), [aws-marketplace](), [compliance](), [ebpf](), [firecracker](), [incident](), [incident-response](), [logs](), [monitoring](), [observability](), [post-contributed](), [rust](), [s3](), [scale](), [security](), [server](), [serverless](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [vpc]() ### AI overview AWS Lambda describes replacing an aging network-capture system with an eBPF and Rust pipeline that records network flows across short-lived, tenant-isolated microVMs. The system prioritizes complete, correctly attributed records with minimal overhead for security investigation, metering, audit, observability, and monitoring. ### Source excerpt On any compute platform, when a security alert fires, the question is always the same. Which workload talked to that The post How AWS Lambda logs every flow across thousands of microVMs per host with eBPF and Rust appeared first on The New Stack. ## Cut GPU inference cold start from 8 minutes to less than a minute DevFeed: [Cut GPU inference cold start from 8 minutes to less than a minute]() Original publisher: [Read original article]() Author: Sajjan Gundapuneedi Published: 2026-09-03T18:30:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [GPU](), [Inference](), [model-deployment](), [Amazon Elastic Kubernetes Service](), [CUDA](), [Optimization](), [Amazon S3](), [Kubernetes]() Tags: [ai-infrastructure](), [amazon-eks](), [aws-marketplace](), [cpu](), [cuda](), [gpu](), [inference](), [kubernetes](), [large-language-models](), [optimization](), [post-contributed](), [s3](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview The article measures GPU model startup from pod creation to the first inference response and identifies six sequential phases. It reports that CUDA kernel recompilation dominates startup for a 64 GB model, while S3 weight downloads dominate for a 203 GB model. Configuration and platform changes reduced warm-node startup times by 80-93%, with additional cold-node improvements requiring Amazon EKS Auto Mode. ### Source excerpt We instrumented the full path from pod creation to first inference response on a GPU node running a 70B-class model. The post Cut GPU inference cold start from 8 minutes to less than a minute appeared first on The New Stack. ## Pulling multi-gigabyte container images in seconds on Amazon EKS DevFeed: [Pulling multi-gigabyte container images in seconds on Amazon EKS]() Original publisher: [Read original article]() Author: Sri Saran Balaji Vellore Rajakumar Published: 2026-08-10T16:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon Elastic Kubernetes Service](), [container images](), [Machine learning](), [autoscaling](), [CUDA]() Tags: [ai-infrastructure](), [amazon-eks](), [autoscaling](), [aws-marketplace](), [container](), [container-images](), [containers](), [cuda](), [kubernetes](), [machine-learning](), [post-contributed](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview This article explains how a production ML platform on Amazon EKS reduced multi-minute pulls of roughly 30 GB container images to seconds. Profiling found that software use of available hardware, rather than network bandwidth or the registry, was the main constraint; the resulting changes are available by default in EKS Auto Mode and were contributed upstream to containerd and the SOCI snapshotter. ### Source excerpt When the image is the bottleneck: Machine learning changed what a container image looks like. A typical application ships in The post Pulling multi-gigabyte container images in seconds on Amazon EKS appeared first on The New Stack. ## How EKS is simplifying Kubernetes cluster lifecycle management DevFeed: [How EKS is simplifying Kubernetes cluster lifecycle management]() Original publisher: [Read original article]() Author: Spyros Angelopoulos Published: 2026-08-01T15:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon Elastic Kubernetes Service](), [Kubernetes](), [Availability](), [Deployment]() Tags: [availability](), [aws-marketplace](), [cloud-services](), [deployment](), [devops](), [kubernetes](), [lifecycle](), [post-contributed](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [upgrades]() ### AI overview The article describes the operational challenges of Kubernetes upgrades and EKS efforts to make cluster lifecycle management easier. It highlights Extended Support, which broadens the availability of each Kubernetes version to 26 months, giving organizations more time to validate and schedule upgrades. ### Source excerpt Kubernetes moves at a pace of three minor version releases per year, and staying current is not optional if you The post Kubernetes upgrades don't have to break things: How EKS is making cluster lifecycle management simpler and safer appeared first on The New Stack. ## Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent DevFeed: [Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent]() Original publisher: [Read original article]() Author: Sajjan Gundapuneedi Published: 2026-07-19T13:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Kubernetes](), [Amazon EKS](), [GPU](), [Monitoring]() Tags: [ai-infrastructure](), [amazon-eks](), [aws-marketplace](), [gpu](), [kubernetes](), [monitoring](), [open-source](), [pcie](), [post-contributed](), [self-healing](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview The article describes how the EKS Node Monitoring Agent detects Kubernetes node failures, writes NodeConditions, and works with Karpenter to replace affected nodes. It explains design lessons from operating automatic repair at GPU scale and places the agent within EKS Auto Mode. ### Source excerpt When you run Kubernetes at the scale we do on Amazon EKS, nodes break constantly. GPUs fall off the PCIe The post Self-healing GPU nodes in Kubernetes: What we learned building the EKS node monitoring agent appeared first on The New Stack. ## From intent to enforcement: Lessons from operating Kubernetes controllers at scale DevFeed: [From intent to enforcement: Lessons from operating Kubernetes controllers at scale]() Original publisher: [Read original article]() Author: Sri Saran Balaji Vellore Rajakumar Published: 2026-07-17T12:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Kubernetes](), [Amazon Elastic Kubernetes Service](), [VPC]() Tags: [amazon-eks](), [aws-marketplace](), [clusters](), [controllers](), [declarative](), [kubernetes](), [networking](), [platform-engineering](), [policy-controller](), [post-contributed](), [reconciliation](), [scale](), [security](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [vpc]() ### AI overview This article explains lessons from operating Kubernetes controllers at scale in Amazon EKS. It focuses on how the Network Policy Controller and VPC Resource Controller reconcile declared intent with changing cluster state to enforce network traffic and AWS resource access policies. ### Source excerpt Kubernetes controllers are what make the platform's declarative model real. They observe the state, reconcile toward the intent, and keep The post From intent to enforcement: Lessons from operating Kubernetes controllers at scale appeared first on The New Stack. ## What running Kubernetes across millions of clusters taught AWS about zonal failures DevFeed: [What running Kubernetes across millions of clusters taught AWS about zonal failures]() Original publisher: [Read original article]() Author: Raghav Tripathi Published: 2026-07-10T15:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [Amazon Web Services](), [Resilience](), [Availability]() Tags: [amazon-eks](), [api](), [availability](), [aws](), [aws-marketplace](), [cloud-services](), [health-checks](), [kubectl](), [kubernetes](), [networking](), [operations](), [outage](), [post-contributed](), [resilience](), [sponsor-aws-marketplace](), [sponsored-post-contributed]() ### AI overview AWS describes how years of engineering on Amazon EKS addressed zonal failures, including gray failures where a zone is degraded but still passes some health checks. The approach emphasizes static stability, preserving capacity, and routing around the impaired Availability Zone. ### Source excerpt Handling the obvious failures is the easy part: a server goes down, you spin up another. The failures that actually The post What running Kubernetes across millions of clusters taught AWS about zonal failures appeared first on The New Stack. ## Operating Kubernetes at scale: a few stories from running Amazon EKS DevFeed: [Operating Kubernetes at scale: a few stories from running Amazon EKS]() Original publisher: [Read original article]() Author: Neelendra Bhandari Published: 2026-06-30T13:00:00Z Content type: article Language: en Sources: [Kubernetes Overview, News and Trends | The New Stack]() Topics: [Amazon EKS](), [Kubernetes](), [Availability](), [systems](), [Apache Spark](), [AI Platform]() Tags: [agentic-ai](), [ai-infrastructure](), [amazon-eks](), [apache-spark](), [availability](), [aws-marketplace](), [cloud-services](), [data](), [gpu](), [kubernetes](), [post-contributed](), [real-time](), [sponsor-aws-marketplace](), [sponsored-post-contributed](), [systems]() ### AI overview This article describes how operating Amazon EKS at very large scale shaped approaches to Kubernetes control-plane resilience. It argues that availability problems often arise when components amplify faults, and explains how changing workload patterns--including foundation-model training, real-time inference, Apache Spark analytics, and agentic AI--create extremely rapid state transitions that challenge traditional Kubernetes operating assumptions. ### Source excerpt Amazon EKS runs hundreds of thousands of Kubernetes clusters across more than thirty AWS regions. Operating at that scale has The post Operating Kubernetes at scale: a few stories from running Amazon EKS appeared first on The New Stack.