feat(observability): utilize Cloudflare observability features in dtvem #174
Description
Summary
Add observability capabilities to dtvem using Cloudflare's observability features to gain insights into usage patterns, errors, and performance.
Motivation
Understanding how dtvem is used in the real world would help:
- Identify which commands are most/least used
- Track download success/failure rates from R2
- Monitor error patterns and common issues
- Make data-driven decisions about feature development
- Detect and respond to issues proactively
Potential Features
Analytics (opt-in)
- Command usage statistics
- Runtime provider popularity (Python vs Node.js usage)
- Version installation patterns
- Geographic distribution of users
Error Tracking
- Capture and report errors (with user consent)
- Track common failure modes (download failures, version resolution issues)
- Alert on error rate spikes
Performance Monitoring
- Command execution times
- Download speeds and success rates
- Shim resolution latency
Implementation Considerations
- Privacy first: All telemetry must be opt-in with clear disclosure
- Minimal overhead: Should not impact CLI performance
- Offline support: Queue events when offline, send when connected
- Configuration: Allow users to enable/disable specific telemetry categories
Cloudflare Services to Evaluate
Tasks
- Research Cloudflare observability options and pricing
- Design opt-in telemetry system with privacy controls
- Implement telemetry client in Go
- Add configuration options (
dtvem config telemetry enable/disable) - Document what data is collected and how it's used
- Set up Cloudflare dashboards for monitoring
Open Questions
- Which Cloudflare observability products are most suitable for a CLI tool?
- What specific metrics would be most valuable?
- How to handle GDPR/privacy compliance?