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Found 18 Skills
Event-driven architecture patterns including message queues, pub/sub, event sourcing, CQRS, and sagas. Use when implementing async messaging, distributed transactions, event stores, command query separation, domain events, integration events, data streaming, choreography, orchestration, or integrating with RabbitMQ, Kafka, Apache Pulsar, AWS SQS, AWS SNS, NATS, event buses, or message brokers.
Expert in background jobs and message queues using Gravito Quasar. Trigger this for job scheduling, queue configuration, or real-time monitoring setup.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
Hookdeck Event Gateway — webhook infrastructure that replaces your queue. Use when receiving webhooks and need guaranteed delivery, automatic retries, replay, rate limiting, filtering, or observability. Eliminates the need for your own message queue for webhook processing.
Implement webhook systems for event-driven integration with retry logic, signature verification, and delivery guarantees. Use when creating event notification systems, integrating with external services, or building event-driven architectures.
Upstash QStash expert for serverless message queues, scheduled jobs, and reliable HTTP-based task delivery without managing infrastructure. Use when: qstash, upstash queue, serverless cron, scheduled http, message queue serverless.
AWS SQS message queue service for decoupled architectures. Use when creating queues, configuring dead-letter queues, managing visibility timeouts, implementing FIFO ordering, or integrating with Lambda.
Backend de mensajería para Celery con baja latencia
Enqueues jobs, configures retry policies, sets concurrency limits, and orders messages via named standard or FIFO queues. Use when building background job workers, task queues, message queues, async pipelines, or any pattern needing guaranteed delivery with exponential backoff and dead-letter handling.
Asynchronous message queues for reliable background processing. Load when offloading background tasks, batch processing messages, implementing retry logic with dead letter queues, rate limiting upstream APIs, or decoupling producers from consumers.
Implement Customer.io load testing and scaling. Use when preparing for high traffic, load testing, or scaling integrations for enterprise workloads. Trigger with phrases like "customer.io load test", "customer.io scale", "customer.io high volume", "customer.io performance test".
Best practices and guidelines for RabbitMQ message queue development with AMQP protocol