Temporal is an open-source durable execution platform that enables developers to build reliable distributed applications and long-running workflows using familiar programming languages. Unlike traditional workflow engines that use DSLs or visual editors, Temporal allows developers to write workflow logic as ordinary code in Go, Java, TypeScript, Python, or .NET. The platform guarantees that workflow code will run to completion despite infrastructure failures, process crashes, or network outages through its durable execution model, which transparently persists the state of every function call.

Temporal’s architecture consists of the Temporal Server (a scalable, multi-tenant orchestration service) and Worker processes (application code that executes workflow and activity logic). Workflows define the overall orchestration logic and are deterministic, while Activities perform the actual work (API calls, database operations, computations) and can be retried with configurable policies. The platform provides features including workflow timeouts, activity retries with exponential backoff, signal handling for external events, query handling for workflow state inspection, child workflows for composition, saga patterns for compensation logic, and cron scheduling. Temporal Server uses Cassandra, MySQL, or PostgreSQL for persistence and supports horizontal scaling to handle millions of concurrent workflows.

Temporal is used by companies including Netflix, Snap, Stripe, Datadog, and HashiCorp for use cases spanning payment processing, order fulfillment, infrastructure provisioning, CI/CD pipelines, and data processing. Its code-first approach and strong reliability guarantees have made it a popular choice for critical business processes that span multiple services and require transactional consistency.

Key Capabilities

  • Durable Execution - Transparent state persistence that guarantees workflow completion despite arbitrary infrastructure failures
  • Multi-Language SDKs - Write workflows in Go, Java, TypeScript, Python, and .NET using native language constructs and debugging tools; Temporal also documents SDKs for PHP, Ruby, and Rust
  • Activity Retries - Configurable retry policies with exponential backoff, maximum attempts, timeouts, and heartbeating for long-running activities
  • Visibility and Observability - Searchable workflow execution history, real-time state queries, and integration with standard observability tools

Cloud Equivalents

Temporal is the open-source alternative to AWS Step Functions, Azure Durable Functions, and Google Cloud Workflows. Cloud workflow services use declarative state machines (JSON/YAML), while Temporal allows writing workflows as imperative code with full language features. This code-first approach is more expressive but requires running Temporal Server infrastructure.

Durable Execution for AI Agents

An AI agent’s own process is not a safe place to hold multi-step state. If the agent crashes, is killed for a context-window limit, or the host process dies mid-task, whatever it was doing is normally gone with no recovery. Temporal’s Event History mechanism - every step, decision, and outcome persisted so a new Worker can replay up to the last known point and continue - solves this independent of the agent’s own lifetime, the same way it does for any other long-running workflow.

Temporal shipped an official OpenAI Agents SDK integration for exactly this. Announced in Public Preview on 30 July 2025, it reached General Availability on 23 March 2026 for the Python SDK. The orchestration logic - the agent loop, tool selection, and handoffs - runs inside a Temporal Workflow; each individual model call executes as a Temporal Activity. Because Activity results are recorded in Event History as part of Temporal’s normal mechanism, a Worker restart does not re-invoke the model for steps already completed - it resumes from the last recorded Activity result, the same guarantee any Temporal Activity gets. An OpenAI Agents SDK sandbox integration entered its own Public Preview on 16 April 2026, extending the pattern to sandboxed tool execution.

This does not replace a simpler mechanism like a Backstage scaffolder template (see Backstage as an agent interface ) for a short, deterministic operation. It matters specifically for agent tasks that must survive minutes-to-days of real time, across process restarts, deployments, and rate-limit waits. See durable execution for agent workflows for the full pattern, including when you need this and when you don’t.

Origins and History

Temporal was created by Maxim Fateev and Samar Abbas, who previously built Uber’s Cadence workflow engine. They founded Temporal Technologies in 2019 to create an improved, open-source version of Cadence. The Temporal Server is licensed under the MIT License, and SDKs are under the Apache License 2.0. Temporal Technologies announced a $550 million Series E at a $12.55 billion valuation on 14 September 2026, co-led by Lightspeed, citing demand for durable execution of long-running AI agents. Temporal Cloud, a managed SaaS offering, launched in 2022. The system’s intellectual lineage traces back through Cadence (Uber), Amazon Simple Workflow Service (SWF), and Microsoft’s Durable Task Framework.

Sources

  1. https://temporal.io/
  2. https://github.com/temporalio/temporal
  3. https://temporal.io/blog/announcing-openai-agents-sdk-integration
  4. https://docs.temporal.io/develop/typescript/integrations/openai-agents
  5. https://temporal.io/changelog/openai-agents-sdk-sandbox-integration-public-preview
  6. Temporal, “Temporal raises $550M at a $12.55B valuation as demand grows for reliable AI infrastructure” (14 September 2026): https://temporal.io/blog/temporal-raises-usd550m-series-e-at-usd12-55b-valuation-ai
  7. Temporal documentation index (SDK developer guides): https://docs.temporal.io/llms.txt