temporal
Temporal is a durable execution platform. You write workflows as ordinary code in one of Temporal's supported languages, and the Temporal server executes them resiliently: progress is persisted, intermittent failures are handled, failed operations are retried, and a workflow can resume exactly where it left off after a crash or restart. Temporal originated as a fork of Uber's Cadence and is developed by Temporal Technologies, founded by Cadence's creators.
For AI developers, durable execution solves a practical problem: agents that run for minutes or hours, call many tools and wait for humans should not lose their state when a process dies or an API times out. Agent frameworks are starting to build on it; for example, Pydantic AI can run agents inside Temporal workflows. Beyond AI, Temporal is widely used for order processing, payments, data pipelines and other business-critical workflows. This repository contains the server; workflows, activities and workers are written with the language SDKs.
Getting started: install the CLI with `brew install temporal`, start a local development server with `temporal server start-dev`, open the web UI at http://localhost:8233, and run one of the Go or Java samples.
Features
Why choose it
Trade-offs
Maintenance check
- Last commit
- 2026-10-24
- Commits, last 90 days
- 100+
- Releases, last 90 days
- 6
- Latest release
- v1.31.4 (2026-10-12)
- Open issues
- 1087
- Recent issues with at least one comment
- 3/5
Oldest week on the left; the latest four weeks are orange. Source: GitHub commit activity.
Status rule: archived on GitHub = Archived; last commit within 90 days = Active; 91 to 365 days = Slowing; older = Stale. All figures come from the GitHub API on the date shown.
Most discussed open issues
- #1507 Provide priority task queues27 comments · 2021-04-29
- #3006 Workflow Pause / Unpause21 comments · 2022-06-17
- #328 Try to run temporal on top of Amazon Keyspaces18 comments · 2020-04-25
- #7930 Replace "github.com/olivere/elastic/v7" with the official client "github.com/elastic/go-elasticsearch"17 comments · 2025-06-18
- #6323 Frontend Service - goroutine (CPU & Memory) Leak16 comments · 2024-07-22
Issue titles are quoted from GitHub. Open the link to check whether a problem still applies to the version you use.
Who it fits
- You need battle-tested durable execution in plain code (Python, TypeScript, Go, Java, .NET) where state survives crashes and retries automatically.
- You are running long-lived AI agents or human-in-the-loop pipelines (including via Pydantic AI's Temporal integration).
- You want a drag-and-drop visual automation builder with 1,000+ SaaS connectors; n8n or Activepieces are built for that.
- You want Temporal's durability in Python without learning Temporal's determinism rules and SDK boilerplate; AutoKitteh wraps Temporal for simpler Python scripts.
How it differs
vs conductor★ 32.4kTemporal defines workflows directly as deterministic code in your programming language (MIT). Conductor defines workflows as JSON graphs orchestrated by a Java 21+ server (Apache-2.0) with built-in LLM and MCP task types.
vs autokitteh★ 1.1kTemporal is the underlying durable execution engine used across massive distributed systems. AutoKitteh builds on top of Temporal so developers can write vanilla Python scripts and use built-in SaaS integrations without managing Temporal worker boilerplate.
Compatibility
Quick start
Use cases
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