151 posts tagged with "DevOps"

In December 2020, attackers compromised SolarWinds' build pipeline and injected malicious code into a routine software update. 18,000 organizations — including the US Treasury, Department of Homeland Security, and Fortune 500 companies — installed the backdoored update without suspicion. The software was legitimately signed, passed all checks, and came through official channels. This is why supply chain security matters.

Here is a number that should make you uncomfortable: the average Kubernetes cluster runs at 20-35% resource utilization. That means you are paying for three nodes but only using one node's worth of compute. Multiply that across dev, staging, and production clusters, and you are burning thousands of dollars a month on idle capacity. The good news — most of this waste is fixable with the right tools and a few YAML changes.

You write perfect Terraform code. You apply it. Your infrastructure matches your configuration exactly. Then, two weeks later, someone logs into the AWS Console and changes a security group rule because "it was faster." Now your code says port 443 only, but reality says ports 443 and 8080. This gap between your Terraform code and actual cloud state is drift, and it is the silent killer of infrastructure as code.

Every request to your microservices needs authentication, rate limiting, logging, and routing — but implementing these in every service creates massive duplication and inconsistency. An API gateway centralizes these cross-cutting concerns into a single entry point, letting your services focus on business logic.

"Docker Compose is only for development." You hear this constantly, but it is not universally true. Compose is not the right choice for a 200-service microservices platform, but for a team running 5-15 services on a single server or small cluster, Compose provides everything you need: restart policies, health-based dependency ordering, resource limits, logging, and deployment configuration. The question is not whether Compose can run in production — it is whether your use case fits.

Your microservices architecture has grown to forty services. You need mutual TLS between all of them, but implementing certificate management in every service is a nightmare. You need traffic splitting for canary deployments, but your Ingress controller only handles north-south traffic. You need to answer "why is service A slow when calling service B?" but your application has no distributed tracing. A service mesh handles all of this at the infrastructure level, without changing a single line of application code.