celery

Add a specific feature to an existing Celery project. Features include task, beat, workflow, monitoring, deploy.

**Project Name:** `$0`

Configure result backends (Redis, Database, RPC)

Configure periodic task scheduling with Celery Beat

Configure message brokers (RabbitMQ, Redis, Amazon SQS)

Initialize Celery in projects with framework detection, broker selection, and configuration

Production deployment configurations (Docker, K8s, systemd)

Integrate Celery with Django projects

Integrate Celery with FastAPI with async support

Integrate Celery with Flask applications

Set up Flower monitoring and observability with event tracking and Prometheus

Create production-ready Celery tasks with retries and validation

Design worker configurations and pool management

Design and implement task workflows (chains, groups, chords)

Periodic task scheduling patterns with Celery Beat (crontab, interval, solar). Use when configuring periodic tasks, setting up task schedules, implementing recurring jobs, configuring django-celery-beat, or creating dynamic schedules.

Message broker setup patterns (Redis, RabbitMQ, SQS) for Celery including connection strings, SSL configuration, high availability, and production best practices. Use when configuring message brokers, setting up Redis/RabbitMQ/SQS, troubleshooting broker connections, implementing HA/failover, securing broker communications with SSL, or when user mentions broker setup, connection issues, sentinel, quorum queues, or AWS SQS integration.

Celery configuration templates for all frameworks (Django, Flask, FastAPI, standalone). Use when configuring Celery, setting up task queues, creating Celery apps, integrating with frameworks, or when user mentions Celery configuration, task queue setup, broker configuration, or framework integration.

Production deployment configurations for Celery workers and beat schedulers across Docker, Kubernetes, and systemd environments. Use when deploying Celery to production, containerizing workers, orchestrating with Kubernetes, setting up systemd services, configuring health checks, implementing graceful shutdowns, or when user mentions deployment, Docker, Kubernetes, systemd, production setup, or worker containerization.

Django, Flask, FastAPI integration patterns for Celery. Use when integrating Celery with Django, Flask, or FastAPI, setting up framework-specific configurations, handling application contexts, managing database transactions with tasks, configuring async workers, or when user mentions Django Celery, Flask Celery, FastAPI background tasks, framework integration, or web framework task queues.

Flower monitoring setup and configuration for Celery including real-time monitoring, authentication, custom dashboards, and Prometheus metrics integration. Use when setting up Celery monitoring, configuring Flower web UI, implementing authentication, creating custom dashboards, integrating with Prometheus, or when user mentions Flower, Celery monitoring, task monitoring, worker monitoring, or real-time metrics.

Result backend configuration patterns for Celery including Redis, Database, and RPC backends with serialization, expiration policies, and performance optimization. Use when configuring result storage, troubleshooting result persistence, implementing custom serializers, migrating between backends, optimizing result expiration, or when user mentions result backends, task results, Redis backend, PostgreSQL results, result serialization, or backend migration.

Task routing and queue management patterns for Celery including priority queues, topic exchanges, worker-specific routing, and advanced queue configurations. Use when configuring task routing, managing queues, setting up priority queues, implementing worker routing, configuring topic exchanges, or when user mentions task routing, queue management, Celery routing, worker assignments, or message broker routing.

Production-ready Celery task templates with error handling, retries, rate limiting, time limits, and custom task classes. Use when creating Celery tasks, implementing retry logic, adding rate limiting, setting time limits, building custom task classes, validating task inputs with Pydantic, handling database operations, making API calls, or when user mentions task patterns, retry mechanisms, task templates, error handling, task best practices.

Celery canvas patterns for workflow composition including chains, groups, chords, signatures, error handling, and nested workflows. Use when building complex task workflows, parallel execution patterns, task synchronization, callback handling, or when user mentions canvas primitives, workflow composition, task chains, parallel processing, or chord patterns.

0 hooks across 6 events