Testing & Verification
Relevant source files
The following files were used as context for generating this wiki page:
The Testing & Verification framework for ClassMate ensures the operational integrity of a complex, multi-service AI architecture. It spans automated deployment verification, health monitoring across containerized services, and manual testing procedures for the mobile and backend components.
The scope of verification includes the FastAPI backend, Celery workers, PostgreSQL database connectivity, and the Traefik API gateway. Verification is critical for managing the system's scalability, which is designed to support 100k+ users through horizontal scaling of AI workers.
Sources: README.md:3-10, infra/README.md:7-15, PROJECT_STRUCTURE.md:120-130
## Automated Deployment Verification
The project provides a dedicated script, verify_deployment.sh, to perform an automated health check of the production-grade stack. This script validates the status of Docker containers, the responsiveness of the API, and the accessibility of the management dashboards.
The diagram above illustrates the sequential checks performed by the automated verification script to ensure the environment is ready for operation.
### Verification Components
The following checks are executed to confirm system readiness:
| Check Type | Target | Success Criteria |
|---|---|---|
| Container Status | Docker Compose | Containers must report status "Up" |
| Backend Health | http://localhost:80/api/v1/public/health | HTTP Status 200 OK |
| Gateway Status | http://localhost:8080/dashboard/ | HTTP Status 200 OK |
| Database Logs | Backend logs | Entry for "Database tables created" |
Sources: scripts/verify_deployment.sh:5-35, README.md:110-120
## Health Checks & Infrastructure Monitoring
Verification extends beyond deployment to continuous monitoring. The system utilizes health check endpoints to validate the connectivity between the API, the database, and the message broker (Redis).
### Service-Specific Health Commands
Developers can manually verify specific service layers using internal container commands:
- API Health:
curl http://localhost:8000/health - Database Connection:
docker exec postgres psql -U classmate -d classmate -c "SELECT 1;" - Redis Connectivity:
docker exec redis redis-cli ping
Sources: infra/README.md:155-165, scripts/launch.sh:105-125
### Observability Stack
For production-grade verification, ClassMate integrates several monitoring tools:
- Grafana: Accessible at
http://localhost:3001(or3000depending on environment) for visual metrics. - Jaeger: Accessible at
http://localhost:16686for distributed tracing of requests through the AI pipeline. - Loki: Used for centralized log aggregation from the FastAPI backend and Celery workers.
Sources: README.md:55-65, scripts/launch.sh:45-55
## Testing Strategies
The project defines a multi-tier testing strategy to cover all components of the monorepo.
### Backend & Worker Testing
Backend testing focuses on API endpoints and the AI processing pipeline. This involves unit tests for the transcription and notes generation logic, as well as load testing for horizontal scaling.
The sequence above shows the manual verification flow using the hybrid launcher to observe service health and logs in real-time.
### Manual Verification Procedures
The documentation suggests three primary manual tests for system validation:
- Authentication: Log in via the Flutter app and verify user synchronization into the PostgreSQL
userstable. - Transcription Pipeline: Record audio on the mobile app and monitor Grafana logs to verify that the transcript appears in the database.
- Horizontal Scaling: Execute
docker-compose up --scale worker=3to verify the system's ability to distribute AI workloads across multiple worker instances.
Sources: PROJECT_STRUCTURE.md:175-190, README.md:122-130
## Verification Gaps and Implementation Risks
Current analysis identifies critical gaps in the testing and verification of the mobile application and backend data integrity.
- Audio Pipeline: The
RecordingServicehas been identified as a stub, meaning the core audio capture requires verification after actual implementation. - Upload Queue Integrity: The
UploadQueueServicecurrently lacks persistent serialization, posing a risk of data loss on app restarts that is not yet covered by automated tests. - Security Verification: There is a known critical risk where API key validation may return the first active key instead of the specific key submitted, requiring immediate security verification and remediation.
Sources: GAPS_IMPLEMENTATION_SUMMARY.md:10-25, GAPS_IMPLEMENTATION_SUMMARY.md:140-155
## Summary
Testing & Verification in ClassMate is a hybrid process involving automated scripts for deployment readiness and manual observability through a specialized monitoring stack. While the infrastructure provides robust verification tools like Jaeger and Grafana, critical gaps in the implementation of core features and security validation remain the primary focus for future verification cycles.