Containers

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AI-powered EKS migration assessment with Amazon Bedrock AgentCore

AI-powered EKS migration assessment with Amazon Bedrock AgentCore

Learn how to build an AI-powered migration assessment agent using Amazon Bedrock AgentCore and the Strands Agents SDK. The agent reads application source code and container artifacts, scores Amazon EKS migration readiness, identifies blockers by severity, and generates an actionable migration plan with target architecture recommendations.

How athenahealth modernized healthcare workloads with Amazon EKS Hybrid Nodes

How athenahealth modernized healthcare workloads with Amazon EKS Hybrid Nodes

Learn how athenahealth used Amazon EKS Hybrid Nodes to modernize latency-sensitive healthcare workloads on premises, cutting response times in half, reducing hardware and operational costs by 50%, and maintaining a single Kubernetes operating model across its data center and the cloud while meeting HITRUST and data residency requirements.

Fix pod distribution drift in Amazon EKS with the Kubernetes descheduler

Fix pod distribution drift in Amazon EKS with the Kubernetes descheduler

A workload spread across three Availability Zones does not necessarily stay spread. This post explains why soft topology spread constraints drift after a node-availability gap, measures the cost, and shows how the Kubernetes descheduler restores even pod distribution on Amazon EKS without downtime and without forcing hard constraints.

One Amazon EKS, Many edges: How to choose your edge container strategy on AWS

One Amazon EKS, many edges: How to choose your edge container strategy on AWS

Choosing the right edge container strategy across many locations can fragment your fleet into dozens of special cases. This post shows how to avoid that by standardizing on Amazon EKS, then choosing a deployment model per site: gate on connectivity, then match to existing infrastructure, so every edge runs the same Kubernetes standard.

The operations gap between deploying an application and running it forever

This post features the new Cluster Mode deployment model in AWS Elastic Beanstalk that extends the operational promise of the service to containerized application portfolios. You bring your applications as source code, Dockerfiles, or container images, and Elastic Beanstalk takes ongoing operational responsibility for the production environment underneath.

Implement per-pod image pull permissions with ECR repository policies on Amazon EKS

Implement per-pod image pull permissions with ECR repository policies on Amazon EKS

Learn how to scope Amazon ECR image pull permissions to individual Kubernetes pods on a multi-tenant Amazon EKS cluster using KEP 4412 credential providers and ECR repository deny policies, so teams sharing the same nodes can pull only their own container images.

How Ramp runs GPU AI workloads at scale with ECS Managed Instances

How Ramp runs GPU AI workloads at scale with ECS Managed Instances

Ramp runs GPU-powered AI inference continuously on Amazon ECS. This post walks through how Ramp’s infrastructure team moved those GPU workloads onto Amazon ECS Managed Instances: the architecture pattern, Terraform implementation, and the lessons learned migrating 50 to 60 EC2 instances.

Fast model loading for AI inference on Amazon EKS

Fast model loading for AI inference on Amazon EKS

When you scale AI inference on Amazon EKS, every new pod must load model weights into GPU memory before serving traffic. We investigated where cold-start time goes and found two configuration-only changes to Run:ai Model Streamer that cut model startup time by 80-93% on subsequent launches, with no code changes.