Best Practices
Principles and strategies for building production-grade AI agents that are reliable, scalable, observable, and safe to operate.
Security and Access
Scope every API key
Issue separate keys per environment and service boundary so a single compromise does not widen blast radius.
Rotate on schedule
Set a fixed rotation cadence and rotate immediately after role changes or suspicious activity.
Keep secrets out of code
Inject credentials at runtime and ensure logs, traces, and screenshots never expose secret material.
Reliability
Retry with backoff and jitter
Handle 408, 429, and transient 5xx responses without amplifying load or causing synchronized retries.
Prefer idempotent writes
Protect workflows from duplicate mutation effects when retries or webhook replays occur.
Queue high-volume work
Absorb spikes with bounded concurrency and explicit backpressure instead of bursting straight into upstream limits.
Observability
Log request IDs
Persist ServoAgent request IDs and your own correlation IDs so incidents can be traced end-to-end.
Measure latency percentiles
Track p50, p95, and p99 latency by endpoint and connector, not just average response time.
Trace webhook lineage
Tie incoming and outgoing events back to runs, users, and downstream side effects for auditability.
Production Readiness Checklist
Design
- Single-purpose agents
- Defined success metrics
- Planned fallback and rollback paths
Security
- Scoped API keys
- Secret injection at runtime
- PII and log redaction validated
Monitoring
- Latency and error SLOs
- Request ID correlation
- Alerting on 429/5xx patterns
Validation
- Staging smoke tests
- Replay-safe webhook handling
- Release checklist signed off