Do I need to change my programming language or framework?

No. You use native SDKs (Go, Java, Python, TypeScript, etc.) to write your logic as Temporal Workflows and Activities in the language you already know.

What happens when my workflow code has a bug or needs an update?

Temporal uses 'Worker Versioning' to pin workflows to a specific version and 'Replay' to test new code against real execution histories, enabling safe deployments.

How does Temporal handle failures in external services or APIs?

You wrap external calls in Temporal 'Activities'. Temporal automatically retries them with configurable backoff and timeouts, and you can implement saga compensation.

Can I run workflows that sleep for months or years?

Yes. Workflows use durable timers that persist their state, allowing them to sleep for extended periods without consuming resources, and resume exactly when needed.

Is Temporal really free to use?

Yes. The core Temporal Server is 100% open-source under the MIT license. You can self-host it for free or use the managed Temporal Cloud service.

What does 'Durable Execution' mean in technical terms?

It's an execution model where the full state and call stack of a workflow is automatically captured and persisted after every step, enabling deterministic replay for recovery.

Directory/Coding/Development/Temporal

Temporal

Temporal is an open-source platform for building and running fault-tolerant, long-running applications. It provides durable workflow orchestration that automatically persists state at every step, allowing applications to resume exactly where they left off after any failure—crashes, network issues, or infrastructure outages. This eliminates the need for developers to write custom reconciliation or recovery logic. Key capabilities include native SDKs for multiple languages (Go, Java, Python, TypeScript, .NET, PHP, Ruby, Rust), built-in retries, timers, and saga compensation patterns. It's designed for mission-critical processes like order fulfillment, payment processing, AI agent pipelines, and CI/CD. Users range from platform engineers and backend developers building distributed systems to startups and enterprises needing reliable, long-running workflows.

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Sep 21, 2026

Durable WorkflowsAutomatic RetriesMulti-Language SDKsOpen Source (MIT)Cloud & Self-HostEvent Sourcing99.999% Uptime

Product information

Everything worth knowing about Temporal

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Durable Workflow Orchestration

Write business logic as code. Workflows automatically capture state and can survive crashes, deploys, and infrastructure outages, picking up exactly where they left off.

Automatic Failure Handling

Built-in retries with backoff, multiple timeout classes, heartbeating, and saga compensation patterns. No more brittle state machines.

Long-Running & Scheduled Processes

Run workflows for days, weeks, or months. Includes durable timers that can sleep, cron schedules with backfill, and Continue-as-New for infinite execution.

Live Interaction with Workflows

Use Signals, Queries, and Updates to read and modify a workflow's state mid-flight. Includes Workflow Streams for real-time data.

Multi-Language SDKs

Native SDKs for Go, Java, Python, TypeScript, .NET, PHP, Ruby, and Rust. Write business logic in the language you already use.

Technical capabilities

Open Source & MIT Licensed

100% open-source. Self-host the Temporal Service yourself or use the managed Temporal Cloud. Code is never visible to the vendor.

Event-Driven Architecture

Core service persists workflow state and uses task queues, signals, and timers for reliable, replayable execution.

Must watch videos

4:53

Tutorial4:53

Build an AI Agent with Temporal

Join Sr. Staff Solutions Architect Steve Androulakis as he builds a durable AI agent using Temporal. The agent is first given a description of the goal and the tools it has at its disposal. The agent uses the LLM to decide which tool to use. If the LLM gives a "bad" response at any point, Temporal will help the agent 'self-heal' by retrying the LLM until it succeeds. The agent allows for amending of parameters such as flight dates using natural language. The agent is not hard-coded to this use case. The Workflow supports dynamic agent goals and tool definitions, so it can essentially work toward any goal so long as the correct tools and goals are provided. Temporal handles the human-in-the-loop confirmation steps via signals. The React JS UI simply queries the Temporal Workflow to display the conversation history. The workflow is coded using Temporal’s Python SDK. Source: https://github.com/temporal-community/temporal-ai-agent Connect with Steve: https://www.linkedin.com/in/steveandroulakis/ --- Temporal is the simple, scalable, open source way to write and run reliable cloud applications. Learn more Blog: https://temporal.io/blog How Temporal Works: https://temporal.io/how-temporal-works Community Slack: https://temporal.io/slack Developer resources Docs: https://docs.temporal.io Courses: https://learn.temporal.io/courses Support forum: https://community.temporal.io

2:00

Tutorial2:00

Temporal in two minutes

Millions of developers are wasting time every day reinventing one of the most reinvented wheels, reliability boilerplate code. Current approaches for working with microservices simply do not reflect the reliability and scalability requirements of modern applications. Temporal on the other hand was explicitly built for a connected world. It seamlessly integrates into languages (Go, Java, Python, TypeScript/JavaScript, .NET, PHP, and Ruby) and provides reliability out of the box so developers spend time inventing and not reinventing. Temporal does for the application layer what Docker Kubernetes and serverless did for infrastructure. Get updates via Temporal Newsletter: http://eepurl.com/hhcaaX Github: https://github.com/temporalio/temporal Support forums: https://community.temporal.io/ Twitter: https://twitter.com/temporaltech

Temporal + OpenAI Agents SDK Demo: Build Production-Ready Agents, Fast

13:20

Tutorial13:20

Temporal + OpenAI Agents SDK Demo: Build Production-Ready Agents, Fast

Rate-limiting? Brittle tools? Rapid iteration? We’ve got it handled. OpenAI Agents SDK + Temporal means your agents now remember state, bounce back from crashes, and survive real-world chaos without you writing error-handling and orchestration code. Explore more here: https://t.mp/agents-sdk-blog View the repo here: https://github.com/temporal-community/openai-agents-demos Written tutorial for how to build this: https://learn.temporal.io/tutorials/ai/deep-research/ Build a Deep Research Agent video tutorial: https://youtu.be/eyLf4Kqd6lg Chapters 0:00 OpenAI Agents SDK release 0:43 The Challenges 1:18 The Solution 2:28 Demo 3:05 Temporal Workers 3:23 Temporal Activities 3:43 Deep Research 5:01 Event History 5:30 Automatic Retries 6:21 Scaling with Temporal 6:48 Cutting Network Access 8:02 Adding Workers 8:29 Multi-Agent Deep Research 12:20 Durable Execution --- Temporal is the scalable, open source way to write and run reliable cloud applications. Learn more Blog: https://temporal.io/blog How Temporal Works: https://temporal.io/how-temporal-works Community Slack: https://temporal.io/slack Developer resources Docs: https://docs.temporal.io Courses: https://learn.temporal.io/courses Support forum: https://community.temporal.io

Who uses it

Real use cases, no hype

AI Agent Orchestration

Build durable, long-running AI agents and pipelines that survive failures and coordinate LLM/tool calls reliably.

Order & Payment Processing

Manage complex, multi-step transactions with automatic retries and compensation logic if a step fails.

Infrastructure & CI/CD Pipelines

Orchestrate cloud deployments, rollbacks, and complex DAGs with clean retries and full visibility.

Customer Onboarding & Lifecycle

Coordinate long-running processes like user signup, account provisioning, and subscription management without dropping steps.

Financial Reconciliation & Ledgers

Track and process financial transactions with precise, durable state management down to the cent.

Human-in-the-Loop Workflows

Design processes that pause for external input (approval, data entry) and resume seamlessly without timeout errors.

Long-Running Batch Jobs

Execute data processing, ETL, or ML training jobs that run for days or months without progress loss.

What's great

Automatic workflow state persistence and recovery from any failure.
Write business logic as plain code in 8+ mainstream languages.
Massive adoption by major tech (OpenAI, NVIDIA, Salesforce).
Fully open-source (MIT license) with a thriving community.
100% pay-as-you-go cloud pricing with no feature gates.

Technical strengths

Durable Execution model eliminates custom state management code.
Native support for complex patterns: Sagas, timers, signals, child workflows.

Where it falls short

Steeper learning curve than traditional request/response APIs.
Requires a mindset shift to workflow-based programming.
Cloud pricing can escalate with high action/storage volume.
Vendor lock-in risk if using proprietary Temporal Cloud features.

Technical limitations

Replaying workflows requires deterministic code; side effects must be in Activities.
Event history storage can grow large for very long-running workflows.

For technical folks