AWS DevOps & Developer Productivity Blog

Migrating a production database is a high-risk operational event. AWS DMS is a cloud service that migrates relational databases, data warehouses, and other data stores into the AWS Cloud or between environments. It moves the rows reliably, but the failures that page an on-call engineer rarely happen during the data copy. They occur in the […]

Introduction Continuous improvement depends on experimentation. Teams know that the fastest path to better outcomes is to test changes against real user behavior, measure results, and iterate. In practice, sustaining that cycle is slow and costly because the overhead compounds with each attempt. Three barriers slow teams down: 1. Planning cost — Turning a proposed […]

AWS Health Planned Lifecycle Events signal when a managed service version is nearing end of standard support. Learn how to automate these upgrades end to end with AWS DevOps Agent and Kiro: detect the event, investigate the upgrade path, apply validated code changes, and open a pull request for human review.

Introduction Running workloads on Amazon Elastic Kubernetes Service (Amazon EKS) can involve managing failures like OOMKilled or IP exhaustion. Engineers must repeatedly collect pod logs, trace events, and check node logs—a process that slows at night/weekends, with critical data lost when pods are deleted or nodes become unhealthy. This collection phase is pure overhead on […]

Introduction Development velocity has reached new heights with AI-driven development tools and practices. Organizations are generating code faster than ever before. But that speed carries risk. Researchers Anderson, Parker, and Tan warned in MIT Sloan Management Review, “Legacy systems tend to carry hidden debt; layering AI-generated code on top of them creates additional tangled dependencies.” […]

This post was co-written with Michael Stephan, Senior Principal Product Manager, and Christian Kreuzberger, Principal Software Engineer, at Dynatrace. AI-driven software delivery changes how code gets written, but not what production demands of it. A generated change still has to fit the traffic your service receives, the dependencies it calls, and the capacity limits it […]

AWS environments that have grown organically over time often share a common characteristic: infrastructure provisioned through the AWS Management Console, SDKs, or CLI without corresponding Infrastructure as Code (IaC) templates. This practice is commonly referred to as “ClickOps,” a term describing any infrastructure change made outside of a codified, version-controlled workflow. Whether changes happen through […]

Introduction When CI/CD deployment failures occur for GitHub hosted applications,  AWS DevOps Agent reduces the hours that Development and Site Reliability Engineering (SRE) teams typically spend manually investigating across multiple AWS services, logs, and pipeline stages. This process delays critical deployments and impacts software delivery velocity. This is especially true when teams need to correlate data between GitHub commit histories, AWS CodePipeline execution logs, and Amazon […]

Automating migration pipelines shifts valuable resources toward innovation. In this post, we will help you learn how to extend AWS Transform custom with Model Context Protocol (MCP) server integrations that connect project management, automated testing, and source control. You will discover how turning a code transformation tool into an automated migration pipeline can take you […]

Introduction Large-scale machine learning workloads: training, fine-tuning, and inference run on clusters of hundreds to thousands of GPU instances for days or weeks at a stretch. Keeping operational visibility across a fleet of this size is a constant challenge: hardware health events, node lifecycle transitions, capacity fluctuations, and workload-level issues appear in the event stream around […]