feat(observability): utilize Cloudflare observability features in dtvem

[CalvinAllen]

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

• Cloudflare Analytics
• Cloudflare Logs
• Workers Analytics Engine

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?