Hatchet

Hatchet orchestrates background tasks, AI agents and durable workflows at scale. It removes the custom admin tooling teams end up writing around traditional queues, where a task vanishes from the broker once it finishes and leaves nothing to inspect, replay or debug.

Postgres is the durability layer for both the task runtime and the observability system, which is what makes the platform straightforward to self-host. SDKs cover Python, TypeScript, Go and Ruby, and a CLI brings up a local server on macOS, Linux or WSL with Docker installed.

The feature set spans queuing, orchestration and the operations around them.

• Durable tasks: recover from failure mid-run, with pause and resume conditions built from durable sleep and event waits.
• DAGs: express data pipelines and multi-step workflows as directed acyclic graphs.
• Retries and scheduling: cover configurable retry policies with exponential backoff, cron jobs and scheduled runs.
• Fair scheduling: applies concurrency policies, priorities, rate limits and worker slots so one workload cannot starve the rest.
• Task routing: assigns work by worker labels or weighted affinity rules.
• Observability: ships a real-time web UI with alerting and logging, plus OpenTelemetry and Prometheus metrics.

Hatchet is MIT licensed and has been load tested to 10,000 tasks per second, with the maintainers noting that durability costs more resources than a Redis or RabbitMQ queue reaching higher raw throughput. Instances are multi-tenant by default with users and roles, so one deployment can serve several teams.