151 posts tagged with "DevOps"

The moment a second person runs terraform apply on the same project, local state files become a disaster. One person's laptop has the truth, the other has a stale copy, and the next apply either duplicates resources or deletes them. Remote state fixes this by storing your state in a shared location with locking, so two people can never write to it simultaneously. For AWS teams, the S3 + DynamoDB pattern is the industry standard.

Your team pushes code to a repository, someone manually builds it, zips it up, and deploys it by dragging files into a portal. On Fridays. That workflow is a ticking time bomb. Azure DevOps Pipelines replaces the entire manual chain with automated, repeatable, auditable deployments — from git push to production with approvals, testing, and rollback built in.

Your CI pipeline builds a Docker image. Where does it go? Your Java app produces a JAR file. Where is it stored? Your Terraform module is versioned and shared across 12 teams. Where do they find it? If your answer to any of these is "somewhere on the build server" or "I just rebuild it," you have an artifact management problem. And it will bite you the first time you need to roll back a production deployment at 2 AM and cannot find the last known-good binary.

Your container is "running." The process has PID 1, Docker says status is Up 47 minutes, and everything looks fine. Except the application inside crashed 20 minutes ago, the event loop is deadlocked, or the database connection pool is exhausted. Traffic keeps flowing in. Users keep getting 502 errors. Docker has no idea anything is wrong because "running" and "healthy" are not the same thing.

The server was acting weird for 3 days before it crashed — the logs told the story all along. Logs are the black box of your servers. If you can read them effectively, you can prevent outages instead of just reacting to them.

You've Dockerized your app, and it runs perfectly on your laptop. Now you need to run it in production — with load balancing, auto scaling, rolling deployments, and health checks. AWS gives you three ways to do this: ECS, Fargate, and EKS. Choosing wrong means either over-engineering a simple app or under-engineering a complex one. Let's break down exactly when to use each.