Workflow orchestration for agents: state, retries, idempotence, human approvals, scheduling, and SLA management.

Orchestration

Overview

Orchestration turns AI capability into operational workflows. It manages multi-step execution, state, concurrency, retries, approvals, and timeouts so that agents can run reliably in real environments.

Without orchestration, systems tend to be fragile: long-running tasks fail silently, side effects are duplicated, and teams cannot enforce service-level objectives or audit requirements.

Workflow model

Terranoha orchestration treats each agent run as a stateful workflow. Common states include Pending, Running, Waiting (for an external event or human approval), Retry, Completed, and Failed.

State transitions are persisted with correlation IDs so every run is replayable and debuggable end-to-end.

Retries, backoff, and error taxonomy

Not all errors should be retried. Transient failures (timeouts, rate limits, temporary outages) can be retried with exponential backoff and jitter. Permanent failures (schema violations, invalid parameters) should fail fast with actionable diagnostics.

Business-rule failures are handled explicitly: the workflow can branch to alternative strategies, request additional inputs, or escalate to a human reviewer.

Idempotence and side effects

Any write action must be idempotent by design. Orchestration supports idempotency keys, de-duplication, and two-step execution where the agent prepares an intended change set before committing.

This is essential when retries occur, when users repeat requests, or when the same event is processed more than once in an event-driven system.

 

Human-in-the-loop checkpoints

Approvals and reviews are first-class steps in the workflow. You can require approval before critical writes, enforce four-eyes control for compliance, or route low-confidence outputs to expert validation.

Waiting steps include reminders, expirations, and SLA tracking so the system remains operable at scale.

Scheduling and concurrency control

Orchestration can be triggered by chat requests, API calls, scheduled jobs, or events (webhooks, message buses). It controls concurrency per tenant and per tool, which prevents rate-limit cascades and limits blast radius.

Priority queues and budgets help guarantee resources for latency-sensitive workflows while keeping costs predictable.

Operational visibility

Each workflow exposes a timeline of steps and durations, including tool-call payloads and results (subject to redaction policies). Key metrics include run success rate, average time to completion, cost per run, and escalation rate.

This visibility enables SRE-style operations: alerting on failure spikes, investigating regressions, and enforcing guardrails when external systems degrade.