Testing
Property-based tests find bugs that example-based tests miss, but they have different CI requirements: they're statistically driven, they need reproducible failures, and they can be slow if misconfigured. This guide covers CI integration patterns for the major property-based testing frameworks across Python (Hypothesis), JavaScript (fast-
Testing Strategy
Financial services organizations need chaos engineering more than almost anyone. Payment processing, trading systems, and banking infrastructure have strict availability requirements — and the failure modes, when they happen, can be catastrophic. They also face constraints that make chaos engineering harder: regulatory requirements, change management processes, audit trails, and risk frameworks
Deployment Testing
Progressive delivery is the practice of releasing software incrementally—starting with a small percentage of users and gradually expanding based on observed outcomes. It combines the best of canary deployments, feature flags, and A/B testing into a coherent strategy for reducing deployment risk. Testing progressive delivery requires a different
Testing
CDK for Terraform (CDKTF) lets you define infrastructure in TypeScript, Python, Go, or Java and synthesize it to Terraform JSON. This brings software testing practices to infrastructure: unit test your constructs, snapshot test synthesized output, and run integration tests against real cloud resources. This guide covers CDKTF testing from construct-
AWS CDK
Writing CDK constructs that deploy working infrastructure is the easy part. Writing CDK constructs that deploy secure infrastructure — that's where teams struggle. CDK Nag is a static analysis tool that checks your CDK stacks against security and compliance rules before a single resource is deployed. This post covers
Monitoring
Catchpoint is most valuable when it's woven into your deployment process — not just running as a passive monitor. By integrating Catchpoint with your CI/CD pipeline, you can enforce performance budgets, trigger post-deploy validation, and automatically roll back when new code degrades user experience. This guide covers
Canary Releases
Canary releases are the deployment strategy that lets you ship to 1% of users and know whether it's safe before the other 99% see it. When done right, a bad deploy affects a tiny slice of traffic and rolls back in minutes. When done wrong, you find out
Deployment Testing
Canary deployments let you ship new code to a small percentage of users before rolling it out to everyone. When something goes wrong—and in production, something always eventually goes wrong—only a fraction of your users are affected, and you can roll back quickly. But canary deployments only work
Testing
Podman is a daemonless, rootless container engine that's fully compatible with Docker CLI syntax. For testing pipelines, this means you can run containers without a Docker daemon, without root privileges, and without the security concerns that come with a socket-exposed daemon. This guide covers how to use
Testing
Managing Protobuf schemas across multiple services is painful without tooling. Proto files drift from naming conventions, breaking changes slip in without warning, and protoc invocations become unmaintainable shell scripts. buf is the modern solution: a CLI that handles linting, breaking change detection, and code generation with a single buf.yaml.
Deployment Testing
Blue-green deployment is one of the simplest and most reliable deployment strategies. You run two identical production environments—blue and green—and switch traffic between them during deployments. The environment not serving traffic is updated, validated, and switched on. Rollback is instantaneous: just switch traffic back. The strategy is
Test Automation
Bazel is a build and test tool originally developed at Google to handle monorepos at extreme scale.