...a reverse proxy that acts as an intermediary between your apps and the API of your Feature Flag SaaS Tool, reducing costs by centralizing feature flag evaluations and avoiding vendor lock-in.

Feature Flags Proxy

• Feature Flag Evaluation: Exposes an endpoint to check the status of a feature flag.

  • Example: curl "http://localhost:8080/feature/feat1?microserviceId=curlcommand"
  • Response: Returns True or False based on the feature flag status for the feature nammed feat1 on your feature flag tool (unleash, launchdarkly etc).

• Vendor Lock-in Avoidance: This project abstracts the feature flag evaluation logic through a proxy, making it easier to switch between feature flag tools (e.g., from Unleash to another service) without making significant changes to your underlying codebase. This helps prevent vendor lock-in and provides flexibility in choosing or changing feature flag providers.

• Caching: Implements a caching layer for feature flag results with a default Time-to-Live (TTL) of 2 minutes, configurable via environment variables.

• Logging: Logs request details including:

  • The IP address of the requestor.
  • Custom source information (e.g., label myapp-prod) passed through the request for traceability.

• Context Support (In Progress): Planned support for passing user-specific data (contexts) to the underlying feature flag tool. This will be crucial for enabling A/B testing, as it allows the flag status to differ based on the user or client context.

• Stack: Built in Java and Dockerized, self-hostable

Commands to run and test the app locally

docker build -t feature-flags-proxy .
docker run --rm -d -p 8080:8080 \
  -e LAUNCHDARKLY_SDK_KEY="sdk-XXXX" \
  -e CACHE_TTL_MINUTES=1 \
  --name feature-flags-proxy-container \
  feature-flags-proxy
curl "http://localhost:8080/feature/feat1?microserviceId=curlcommand"
curl -f http://localhost:8080/actuator/health

TODO

Can be considered as production ready, but here is a todo of improvements:

• Implement multi-context support for A/B testing (allow different flag states based on user data). The best way to implement this seems to be by passing a JSON payload to the reverse proxy that contains the relevant data.
• Implement the SDK of your given feature flagging SaaS tool!
• Implement CI/CD pipelines for Docker image building and deployment.
• Optimize caching mechanism? (event-driven cache invalidation, distributed caching, fine-grained caching strategy, LRU?, LFU?)
• Improve logging and tracing.s
• High availabilty
• IP rotation - proxy pooling
• Throttle requests
• Randomizing headers and user contexts for each request
• Improve security posture (docker, TLS etc)

Screenshot