Temporal
Open-source durable-execution platform whose Workflows survive crashes, restarts, and infrastructure outages by replaying an event-sourced history; increasingly adopted as the substrate for long-running AI agents.
Description
Temporal is a durable-execution platform originating as a fork of Uber's Cadence and built by Temporal Technologies. The server (Go) coordinates workflows and activities; SDKs in Go, Java, Python, TypeScript, .NET, PHP, and Ruby let developers write Workflow Definitions (deterministic functions) that invoke Activities (idempotent side-effecting functions). The Temporal Service persists every command and event in a per-workflow Event History; when a Worker crashes or restarts, Temporal replays the history to reconstruct in-memory state and continues from the last unfinished step. Signals, Queries, Updates, Schedules, Retry Policies, and the Saga compensation pattern are first-class primitives. Agent frameworks adopt Temporal to make agent loops crash-proof.
Solution
Workflow-as-code with deterministic replay. The agent loop is written as a Workflow Definition; each model call, tool call, or side effect runs as an Activity with built-in retries and timeouts. The Workflow's Event History is the source of truth: on Worker restart Temporal replays history step by step to rebuild the in-memory state, then resumes execution. Signals drive asynchronous inputs (user messages, approvals); Updates handle synchronous request/response; Queries inspect state without changing it; Schedules trigger periodic runs; Saga lists of compensating Activities roll back on failure.
Primary use cases
- durable workflows for long-running, fault-tolerant business processes
- AI-agent backbones with crash-proof tool loops
- saga / compensation across distributed services
- scheduled and signal-driven recurring jobs
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