Testing Strategy
The tooling for chaos engineering is the easy part. Chaos Monkey, Gremlin, LitmusChaos — all documented, all installable in an afternoon. The hard part is the culture. Specifically: convincing a team to deliberately break things they spent months building, in an environment where incidents are stressful and blame is common. Most
Testing Strategy
Chaos engineering for stateless services is relatively forgiving. Kill a pod, another one starts. The state lives elsewhere. Stateful services are different. When you chaos-test a database, a message queue, or a distributed cache, you're working with data that can be corrupted, lost, or inconsistent. The blast
Testing Strategy
The most common reason teams never start chaos engineering: they're afraid of breaking production. The second most common reason: they start chaos engineering and actually break production. Both outcomes are avoidable. Rolling out chaos engineering safely is an engineering problem, not a bravery contest. The Prerequisite Checklist Before
Chaos Engineering
Chaos engineering is the practice of deliberately introducing failures into a system to find weaknesses before they cause incidents. The core idea: if you run controlled experiments that break things on purpose, you discover fragility in a controlled way rather than during a real outage. Netflix popularized it with Chaos
Testing Strategy
Single-cloud chaos engineering is hard enough. Multi-cloud and hybrid environments add layers that make failure modes more complex, blast radius harder to control, and recovery paths less obvious. The upside: multi-cloud architectures are supposed to provide resilience through redundancy. Chaos engineering tells you whether that redundancy actually
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