Containers

Category: Learning Levels

Beyond metrics: Extracting actionable insights from Amazon EKS with Amazon Q Business

In this post, we demonstrate a solution that uses Amazon Data Firehose to aggregate logs from the Amazon EKS control plane and data plane, and send them to Amazon Simple Storage Service (Amazon S3). Finally, we use Amazon Q Business and its Amazon S3 connector to synchronize the logs, index the log data in Amazon S3, and enable a chat experience powered by the generative AI capabilities of Amazon Q Business.

Simplify Kubernetes cluster management using ACK, kro and Amazon EKS

In this blog post, we show how to create and manage a fleet of Amazon Elastic Kubernetes Service (Amazon EKS) clusters using Kube Resource Orchestrator (kro), AWS Controllers for Kubernetes (ACK), and Argo CD. These tools allow you to implement a GitOps-based cluster management solution to increase productivity and improve consistency and standardization by using the Kubernetes API for end-to-end operations.

Monitor Amazon ECS Events with Amazon EventBridge Filtering

In this post, we demonstrate how to capture specific Amazon ECS events using EventBridge rules for enhanced monitoring and troubleshooting of your containerized applications. We show you how to customize EventBridge filtering patterns to capture the specific Amazon ECS events that matter for your troubleshooting and monitoring needs.

Part 2: Observing and scaling MLOps infrastructure on Amazon EKS 

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.

Deep dive: Streamlining GitOps with Amazon EKS capability for Argo CD

In this deep dive, we explore advanced scenarios with Argo CD including hub-and-spoke multi-cluster deployments, native AWS service integrations, multi-tenancy implementation, scaling with advanced Argo CD configurations and integration with CI/CD pipeline.

Automate java performance troubleshooting with AI-Powered thread dump analysis on Amazon ECS and EKS

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.