telemetry-observability

Structured logging for CLI tools is achieved by writing JSON diagnostic output to stderr, which keeps stdout clean for data. This approach ensures machine-readable logs without interfering with command pipelines.

Persistent telemetry records every command's event, duration, success status, and metadata in a queryable store like SQLite. You can query historical telemetry to pinpoint regressions and identify affected code paths using trace IDs.

Yes, SQLite can be used as a persistent telemetry store to capture event, duration, success, and metadata for each CLI operation. This enables queryable performance analytics and MTTR tracking.

The best way to implement trace IDs is to generate unique identifiers for each operation and pass them through structured JSON logs to stderr and persistent telemetry storage. This correlates logs, telemetry, and events across operations.

Machine-readable JSON logging is needed because it enables automated parsing, structured telemetry capture, and efficient debugging. Plain text lacks the structured fields required for trace ID correlation and queryable performance analytics.

Track command duration and success status by instrumenting CLI commands with persistent telemetry that records event metadata in a SQLite store. This captures timing and success metrics for each operation to enable performance analytics.