Harish Darko

Project case study · practice lab

Mobile Platform Reliability Lab

I built this FastAPI lab to practise the operating work around a backend service: health checks, request IDs, logs, CI, containers, infrastructure validation, smoke probes, and runbooks.

Code ↗

floor: Kubernetes manifestsFastAPI in Docker/healthreq-idevery request gets an IDstructured logssmoke proberunbook
The pieces the lab practises, in one place.

What is in it

A small service, and everything around it.

The API is simple on purpose. The practice is in delivering, watching and fixing it.

Service shape

Python/FastAPI API with health endpoints, request IDs, structured logs, metrics-style output, Docker packaging, and Kubernetes manifests.

Pipeline work

CI runs tests, linting, container builds, Terraform validation, Kubernetes rendering, and certificate-monitor tests. Deployment workflows add health smoke tests.

Support path

The runbook covers service health, deployment history, logs, metrics, dependency review, rollback thinking, and incident notes.

Why I built it

I built it to practise the operating path around a backend service, including delivery, health checks, failure diagnosis, and rollback.

Inside the repository

Code and checks you can run.

The API, workflow, scripts, infrastructure files, and runbook are available for inspection.

build
  1. tests
  2. lint
  3. docker build
infrastructure
  1. terraform validate
  2. k8s render
  3. smoke script
support
  1. health route
  2. logs
  3. runbook

API behavior

Health route, metrics-style route, request IDs, structured logging, error handling, and local tests.

Delivery path

Dockerfile, GitHub Actions workflow, Terraform validation, Kubernetes render step, certificate expiry script, and smoke probe.

Ops notes

Runbook, incident-style notes, rollback checklist, and troubleshooting order for logs and service health.