Testing
Infrastructure-as-Code introduced a new class of bug: the infrastructure configuration error. A missing variable, a wrong CIDR block, or an IAM permission misconfiguration can take down a service just as effectively as a software bug. Testing your Terraform code prevents these failures. This guide covers the full Terraform testing stack:
Testing
Policy-as-code turns compliance requirements into machine-checkable rules. Instead of "all S3 buckets must have versioning enabled" living only in a wiki, it lives in code that runs in your CI pipeline and blocks non-compliant deployments automatically. Open Policy Agent (OPA) is the most widely adopted policy-as-code engine. conftest
Testing
Pulumi brings real programming languages to infrastructure — TypeScript, Python, Go, C#. With that comes a genuine testing story: unit tests that mock the cloud provider and integration tests that deploy to a real environment. Pulumi's Testing Model Pulumi provides two distinct testing approaches: Unit testing — uses the Pulumi
Testing
GitOps treats infrastructure like application code: changes go through pull requests, get reviewed, pass CI, and deploy automatically. But infrastructure PRs need different validation than application PRs. A bad dependency upgrade might break a test; a bad Terraform change might delete your database. This guide covers how to build CI/
Testing
AWS CDK (Cloud Development Kit) lets you define AWS infrastructure with TypeScript, Python, Java, or Go. Because CDK produces CloudFormation templates, testing means asserting on the generated template — and CDK provides a first-class testing library for exactly this. CDK Testing Philosophy CDK tests don't deploy real infrastructure during
Testing
Integration tests that run against a shared staging environment are a liability. Two PRs land simultaneously, one migrates the database schema, and suddenly the other PR's test suite is failing against an incompatible schema it didn't create. Teams work around this with test locks, serialized merge
Testing
Infrastructure code breaks. An S3 bucket gets configured with public ACLs. A security group rule opens port 22 to the world. A load balancer misconfiguration sends traffic to the wrong target group. These aren't hypothetical — they are the kinds of bugs that make it to production because the
Testing
Every engineering team has experienced the same painful scenario: a test suite passes flawlessly on one developer's laptop, fails on another's, and produces yet different results in CI. The root cause is almost always environment drift — different Node versions, mismatched library versions, missing system dependencies, or
Docker
Shipping a Docker image without testing it is like deploying code without tests — the problems show up in production. Docker containers need their own testing layer: build tests, container smoke tests, integration tests, and security scans. Here's how to build that layer. Key Takeaways Test at four levels:
Testing Strategy
Netflix's infrastructure team had a problem in 2010: they couldn't be sure their systems would survive an AWS outage. Their solution — a tool that randomly terminates production instances — became Chaos Monkey, and the discipline around it became chaos engineering. The core idea: instead of hoping your
Testing Tools
Gremlin is a commercial chaos engineering platform that simplifies running controlled failure experiments at scale. Where open-source tools like Chaos Mesh require Kubernetes expertise to operate, Gremlin provides a web UI, pre-built attack scenarios, and team collaboration features. This tutorial covers setup, running your first experiments, and building a chaos
Performance Testing
k6 is known as a load testing tool. What's less known is that it's also effective for chaos testing — simulating fault conditions, injecting failures at the application layer, and validating resilience under degraded conditions. This guide covers k6's chaos capabilities: the k6 Disruptor extension,