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FastAPI + Celery . Self-hosted . Open source

FastAPI Celery Dashboard

Run Celery inside a FastAPI app and you have working background jobs. Run Celery with z4j and you also have a dashboard, persistent history, the task controls this adapter can execute safely, scheduler integration, RBAC with invitations, and a tamper-evident audit log. z4j is one container or one Python process; the agent is one pip extra in your existing FastAPI venv.

Running Celery from FastAPI is unusual but legitimate; the most common reason is a sync-heavy workload that would not benefit from arq or taskiq, or a team migrating off Django. z4j supports it the same way it supports the Django + Celery stack: install z4j-fastapi[celery], wire the lifespan hook, point at z4j, done.

Install z4j FastAPI integration details Celery adapter details
install

Install z4j alongside FastAPI + Celery

1. Install the brain

bash 
pip install z4j && z4j serve

First boot prints a setup URL to stderr. Open it, create the first admin, and mint a token + HMAC secret for this agent.

2. Add the agent to your FastAPI venv

bash 
pip install z4j-fastapi[celery]

3. Wire it into FastAPI

python 
from fastapi import FastAPI
from z4j_fastapi import z4j_lifespan

app = FastAPI(lifespan=z4j_lifespan())

What you get

  • Persistent Celery task history in Postgres or SQLite
  • Adapter-advertised controls: submit_task, retry_task, cancel_task, bulk_retry, purge_queue, restart_worker, pool_grow / pool_shrink, add_consumer / cancel_consumer, rate_limit
  • Scheduler integration via celery beat; available controls depend on that scheduler adapter
  • RBAC with invitations and password reset
  • HMAC-chained tamper-evident audit log
  • Notifications: email, Slack, Telegram, webhook
License

z4j-fastapi and z4j-celery are Apache 2.0. Importing them into your FastAPI app does not affect your application's licensing. z4j is AGPL-3.0-or-later, isolated in its own process.

Celery actions exposed

What the dashboard can actually do

Native actions

  • submit_task
  • retry_task
  • cancel_task
  • bulk_retry
  • purge_queue
  • restart_worker
  • pool_grow / pool_shrink
  • add_consumer / cancel_consumer
  • rate_limit

Event capture

Signals (in-process) + broker-events monitoring (fanout). Auto-switches based on worker pool type.

Reconciliation

celery.result.AsyncResult, authoritative; covers every backend (redis, rpc, db, etc.).

other FastAPI stacks

FastAPI with a different engine

FastAPI +

FastAPI RQ Dashboard

Lightweight Redis queue, fully instrumented.
FastAPI +

FastAPI Dramatiq Dashboard

Middleware-driven Dramatiq observability.
FastAPI +

FastAPI Huey Dashboard

Lightweight Redis/SQLite queue, first-class.
FastAPI +

FastAPI arq Dashboard

Async Redis queue for FastAPI-era Python.
FastAPI +

FastAPI taskiq Dashboard

Broker-agnostic async task framework.
Celery on other frameworks

Same engine, different framework

+ Celery

Django Celery Dashboard

Django AppConfig integration, zero boilerplate.
+ Celery

Flask Celery Dashboard

Flask extension pattern. One line to install.

Start using FastAPI Celery Dashboard

Self-hosted, open source, no SaaS, no telemetry. z4j runs anywhere Python or Docker runs.

Install z4j Read the docs