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Found 25 Skills
Expert Celery distributed task queue engineer specializing in async task processing, workflow orchestration, broker configuration (Redis/RabbitMQ), Celery Beat scheduling, and production monitoring. Deep expertise in task patterns (chains, groups, chords), retries, rate limiting, Flower monitoring, and security best practices. Use when designing distributed task systems, implementing background job processing, building workflow orchestration, or optimizing task queue performance.
Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
Advanced Celery patterns including canvas workflows, priority queues, rate limiting, multi-queue routing, and production monitoring. Use when implementing complex task orchestration, task prioritization, or enterprise-grade background processing.
Distributed task queue system for Python enabling asynchronous execution of background jobs, scheduled tasks, and workflows across multiple workers with Django, Flask, and FastAPI integration.
Expert Django and Celery guidance for asynchronous task processing. Use when designing background tasks, configuring workers, handling retries and errors, optimizing task performance, implementing periodic tasks, or setting up production monitoring. Follows Celery best practices with Django integration patterns.
Celery task patterns including task definition, retry strategies, periodic tasks, and best practices. Use when implementing background tasks, scheduled jobs, or async processing.
Testing patterns for Prowler API: JSON:API, Celery tasks, RLS isolation, RBAC. Trigger: When writing tests for api/ (JSON:API requests/assertions, cross-tenant isolation, RBAC, Celery tasks, viewsets/serializers).
RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.
Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, report generation, batch operations. Activate on "background job", "async task", "queue", "worker", "BullMQ", "Celery". NOT for real-time WebSocket communication, synchronous API calls, or simple setTimeout operations.
Prowler API patterns: RLS, RBAC, providers, Celery tasks. Trigger: When working in api/ on models/serializers/viewsets/filters/tasks involving tenant isolation (RLS), RBAC, or provider lifecycle.
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.
Backend de mensajería para Celery con baja latencia