Inspiration
To build a project that proves reliability under pressure, not just in demos.
How we built it
We designed the project as a full reliability-focused stack:
- A backend API for health checks, URL handling, and user/event flows.
- A frontend interface for interaction and visibility.
- A monitoring layer with metrics, logs, and traces to understand behavior in real time.
- Load-testing workflows to validate performance at increasing traffic levels.
- Chaos and failure testing to verify graceful recovery and fault tolerance.
Challenges we ran into
Keeping test results reproducible while experimenting with multiple configuration options. Documenting procedures and outputs.
Accomplishments that we're proud of
Unit tests Observability dashboard that can be setup with a single compose file
What we learned
Reliability is a feature, not an afterthought. Building health checks, clear error handling, and graceful failure paths early saved us from bigger issues later. Load testing reveals reality. What works with a few users can fail under pressure, so testing at scale helped us find bottlenecks before deployment. Observability speeds up debugging. Metrics, logs, and traces gave us visibility into system behavior and made root-cause analysis much faster. Performance tuning is iterative. Every improvement uncovered the next constraint, so optimization became a cycle of measure, adjust, and re-test. Distributed systems require strong teamwork. Clear communication, shared testing practices, and good documentation were essential for moving quickly and safely.
What's next for Purrduction Engineers
Deploy this onto actual infrastructure and setup github actions to automate deployment on push.
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