Upstream Source
This page is part of Truthound Orchestration 3.x.
Source repository: seadonggyun4/truthound-orchestration
Upstream docs path: docs/common/observability-resilience.md
Edit upstream page: Edit in orchestration
Observability And Resilience¶
The shared runtime also owns the operational helpers that keep long-lived workflow integrations predictable: logging, retries, circuit breakers, health checks, metrics, rate limiting, caching, and structured observability events.
Why These Helpers Are Shared¶
All host platforms hit the same production problems:
- flaky upstream data access
- expensive validation on large datasets
- intermittent secret or connection failures
- repeated checks that should not overwhelm shared systems
- workflows that need auditable execution metadata
Keeping those helpers shared prevents each host from growing its own incompatible operational policy layer.
Core Areas¶
| Area | Shared Responsibility |
|---|---|
| Logging | structured, masked logging with consistent context keys |
| Retry | bounded retry policies and backoff strategies |
| Circuit Breaker | protecting repeated failures from cascading into the host |
| Health | surface-level health checks for runtime readiness |
| Metrics | counters, gauges, histograms, and platform-neutral metric emission |
| Rate Limiting | keeping data access or validation throughput bounded |
| Caching | avoiding repeated expensive setup or lookup operations |
| Observability Events | lifecycle events for execution and lineage |
OpenLineage And Shared Observability¶
The runtime exposes structured observability config instead of making each host implement its own lineage emitter from scratch. That gives you:
- a consistent backend model
- shared producer metadata
- execution context attached to the same runtime event types
- fewer platform-specific observability gaps
Operational Defaults¶
The defaults remain conservative:
- zero-config should stay easy to debug
- retries should not hide systemic misconfiguration
- circuit breakers should fail clearly when a dependency is unhealthy
- logging should help operators without leaking sensitive data
When To Make Behavior Explicit¶
Move from defaults to explicit policies when:
- workflows are shared across teams
- external rate limits matter
- downstream alerting depends on stable thresholds
- you need deterministic escalation or SLA enforcement
- the host UI is not enough and you need external observability backends