Status: Planned - Not yet implemented
This example will demonstrate how to instrument and monitor Resonate server deployments with industry-standard observability tools.
- Promise creation/resolution rates
- Workflow execution duration
- Error rates by workflow type
- Queue depth and processing lag
- Resource utilization (CPU, memory, connections)
- Distributed tracing across workflow steps
- RPC call tracking between workers
- End-to-end latency visualization
- Span relationships and context propagation
- Structured logging with context
- Log aggregation and search
- Error tracking and alerting
- Audit trails for promise lifecycle
- Pre-built dashboard templates
- Real-time workflow monitoring
- SLA tracking and alerting
- Capacity planning views
- Metrics: Prometheus + Grafana
- Tracing: OpenTelemetry + Jaeger/Tempo
- Logging: Loki or ELK stack
- Deployment: Docker Compose for local dev
Observability is critical for production Resonate deployments:
- Debug failures: Trace workflow execution paths
- Monitor performance: Identify slow operations and bottlenecks
- Ensure reliability: Alert on error spikes and SLA violations
- Capacity planning: Track growth and resource needs
- Incident response: Quickly diagnose and resolve issues
This example is planned but not yet implemented. If you're interested in contributing, please:
- Open an issue to discuss the approach
- Reference production observability best practices
- Consider multi-cloud deployment scenarios
- Include sample dashboards and alert rules
Want to see this example built? Open an issue or reach out on Discord.