Source: Durable Execution Engines for AI ITSM

Sources: Temporal workflows, Trigger.dev tasks, Hatchet durable tasks, Inngest durable execution

What It Covers

This source compares durable execution engines that can run IT automations across retries, crashes, long waits, approvals, and external events.

Temporal defines workflows as code-backed executions that can run for seconds or years, recovering from failures by replaying event history under deterministic constraints.
Trigger.dev is an open-source TypeScript background jobs framework for long-running AI tasks, retries, queues, cron, human-in-loop wait tokens, realtime status, and observability.
Hatchet durable tasks checkpoint waits and child task spawns to a durable event log, making them useful for agentic loops, runtime-selected workflows, long waits, and human approval flows.
Inngest uses step-based durable execution: step.run, step.sleep, step.waitForEvent, and step.invoke persist step results and resume without redoing completed work.
Temporal emphasizes deterministic replay; Inngest emphasizes standard-language step memoization; Hatchet emphasizes durable tasks with child spawning and event waits; Trigger.dev emphasizes developer experience for TypeScript background tasks and AI agents.

AI ITSM needs durable execution because access requests, onboarding, device remediation, compliance evidence, and approval flows can span minutes, days, or weeks.
The runtime should treat each external side effect as a typed, logged, idempotent step. Agents can choose or draft actions, but the execution substrate must handle retries, dedupe, and audit.
For a founder-speed prototype, Trigger.dev, Inngest, or Hatchet may be faster to adopt than running a Temporal cluster. For high-scale enterprise workflow infrastructure, Temporal remains the reference architecture to understand. ^[inferred]

Durable execution engines do not themselves provide IT policy, credential scoping, least-privilege checks, or evidence collection.
Some vendor comparisons are self-positioned and should be validated with implementation tests before architectural commitment.