Temporal

Temporal addresses a hard part of building reliable software: making long-running, multi-step processes survive failures. Developers write workflows in an ordinary programming language such as Go, Java, Python, or TypeScript, and Temporal records each step and its state, so if a server crashes or a network call fails, the workflow continues from where it stopped without losing progress. Retries, timeouts, and timers are built in.

That makes it suitable for processes that take minutes to months, such as payment flows, order fulfillment, customer onboarding, infrastructure provisioning, and data processing. Increasingly, teams use it to orchestrate AI agents, where tasks call models and tools over long durations and need reliability and observability. Temporal Cloud provides a managed service, and the open-source server can be self-hosted.

Temporal is free and open source under the MIT license, and Temporal Cloud is priced by usage. Its model has a learning curve, and teams must run or pay for the service. Alternatives include AWS Step Functions, Apache Airflow for data workflows, Inngest, Restate, Camunda, and queues like Celery. Temporal suits engineering teams building critical, long-running processes.