Can I use this for monitoring production workers?

Yes, it includes configurations for the Flower dashboard and implementation patterns for custom signal-based monitoring for real-time observability.

How does this skill handle rate limiting?

It provides patterns for both static per-task rate limits and dynamic token-bucket implementations to ensure your workers don't exceed external API quotas.

What are Celery canvas workflows?

Canvas workflows are tools like chains, groups, and chords that allow you to define complex dependencies between tasks, such as sequential execution or parallel fan-in aggregation.

Does it help prevent worker deadlocks?

Yes, it specifically enforces anti-patterns such as avoiding blocking on results (result.get()) inside tasks, which is the leading cause of worker deadlocks.

Advanced Celery Orchestration

Name: Advanced Celery Orchestration
Author: yonatangross

byyonatangross

•

API 开发

Implements sophisticated Celery task patterns including complex workflows, priority queuing, and enterprise-grade monitoring.

This skill equips Claude with expert-level knowledge of advanced Celery features, enabling the design and implementation of complex asynchronous architectures. It covers canvas workflows like chains and chords for multi-step ETL pipelines, fine-grained rate limiting for external API integrations, and multi-queue routing for resource optimization. By incorporating production-ready monitoring patterns and strictly enforcing safety anti-patterns, this skill ensures that background processing systems are scalable, observable, and resilient against common pitfalls like worker deadlocks and data duplication.

主要功能

01Multi-level priority queue configuration and dynamic task routing

0269 GitHub stars

03Advanced Canvas workflows including Chains, Groups, Chords, and Starmaps

04Production monitoring patterns using Flower and custom event signals

05Granular rate limiting and token bucket implementation for API protection

06Enterprise safety patterns to prevent worker deadlocks and ensure idempotency

使用场景

01Building multi-stage ETL pipelines with complex sequential and parallel dependencies

02Prioritizing real-time premium user requests over background analytics in high-load environments

03Managing strict API rate limits across distributed workers for high-volume external integrations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add yonatangross/orchestkit celery-advanced

For use in Claude.ai and ChatGPT

Download Skill