OperationsAgent systems topic

Deployment and operations

Operating agents in production requires durable run identities, bounded time and cost, resumable state, safe retries, versioned dependencies, rollback, observability, and ownership. Deployment is a change to a live decision system, not merely a code upload.

Apply the lifecycleReview sources

Questions to answer

Resolve these before adding tools, frameworks, or automation.

  • Which model, prompt, tool, Skill, and policy versions produced a run?
  • How are long-running, interrupted, duplicated, or abandoned runs recovered?
  • What signals trigger rollback, throttling, disabling, or human intervention?

Implementation lifecycle

Build the evidence in this order

  1. 01

    Release

    Version models, instructions, tools, schemas, policies, and migrations together.

  2. 02

    Control

    Set budgets, concurrency, deadlines, retries, circuit breakers, and approval boundaries.

  3. 03

    Recover

    Test rollback, resume, replay protection, degraded mode, and incident ownership.

Artifacts to maintain

  • release manifest
  • run budget
  • rollback procedure
  • operations dashboard

Continue through AgentAtlas

Evidence ledger

Primary documentation behind this guide

OpenAI

Running agents

Run execution, limits, state and conversation strategies, streaming, errors, and lifecycle behavior.

OpenAI

OpenAI Agents SDK tracing

Production workflow tracing, grouping, processors, sensitive data, and operational diagnosis.

Next topic

Safety and permissions