Category: Containers

In this post we demonstrate how using GitLab Runners on EKS Auto Mode, combined with Amazon Elastic Compute Cloud (Amazon EC2) Spot Instances, can deliver enterprise-scale CI/CD capabilities while achieving up to 90% cost reduction when compared to traditional deployment models. This approach not only optimizes operational expenses, but also provides resilient, scalable pipeline execution.

In this post, we focus on observing and scaling ML operations (MLOps) infrastructure on Kubernetes. MLOps platforms running on Amazon EKS provide powerful built-in capabilities for logging, monitoring, and alerting that are essential for maintaining healthy ML systems at scale.

This post looks at various options for container image caching, model training, and inferencing workloads. This post also discusses various storage options such as Amazon Simple Storage Service (Amazon S3), FSx for lustre, S3 Express One Zone, and Amazon S3 Connector for PyTorch.

Amazon Web Services (AWS) announced the availability of DNS-based and Admin network policies for Amazon Elastic Kubernetes Service (EKS) Auto mode and Admin network policies for both EKS Auto mode and EKS on Amazon Elastic Compute Cloud (EC2), providing enhanced capabilities to secure network traffic both within your clusters and to external endpoints. In this post, we explore practical use cases that demonstrate how these policies solve real-world challenges and remove the need to rely on third-party software across different deployment scenarios, from securing access to external services to hybrid cloud integration and multi-tenant environments.

In this blog post, we’ll walk through how to build an automated thread dump analysis pipeline that uses Prometheus for monitoring, Grafana for alerting, AWS Lambda for orchestration, and Amazon Bedrock for AI‑powered analysis. The solution works on both Amazon Elastic Container Services (Amazon ECS) and Amazon Elastic Kubernetes Service (Amazon EKS), helping teams go from raw thread dumps to actionable insights within seconds of detecting an issue.

Amazon Elastic Container Service (Amazon ECS) Managed Instances is a fully managed compute option that eliminates infrastructure management overhead while providing customers access to a broad suite of Amazon Elastic Compute Cloud (Amazon EC2) capabilities, including the flexibility to select instance types, access reserved capacity, and leverage advanced security and observability configurations. By offloading operations […]

In this post, we explore how KubeArmor, an open source container-aware security enforcement system, enhances the security posture of containerized workloads running on EKS Auto Mode clusters. Although EKS Auto Mode significantly streamlines cluster management by automating control plane and node operations, securing the workloads running within the cluster remains a critical user responsibility.

In this post, we explore how Amazon ECS’s native support for blue/green deployments can be extended using lifecycle hooks to integrate test suites, manual approvals, and metrics into deployment pipelines.

In this post, we explore advanced implementation patterns for building highly available services on Amazon ECS, including idempotency, resilience to transient failures, static stability across Availability Zones, deployment safety, and chaos engineering techniques. The post provides detailed guidance on how these patterns can be implemented when deploying applications on Amazon ECS to ensure maximum resilience and availability.

In this post, we dive deep into cluster networking configurations for Amazon EKS Hybrid Nodes, exploring different Container Network Interface (CNI) options and load balancing solutions to meet various networking requirements. The post demonstrates how to implement BGP routing with Cilium CNI, static routing with Calico CNI, and set up both on-premises load balancing using MetalLB and external load balancing using AWS Load Balancer Controller.