Loading...
Loading...
Found 18 Skills
Inspects and redrives jobs that exhausted all retries. Use when handling failed queue jobs, debugging processing errors, or implementing retry strategies.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
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.
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.
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.
Expert in background jobs and message queues using Gravito Quasar. Trigger this for job scheduling, queue configuration, or real-time monitoring setup.
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.
Selects how functions are invoked — synchronous calls that return results, fire-and-forget void dispatches, or durable enqueue through named queues with retries. Use when deciding between blocking RPC calls, background job dispatch, async workers, or reliable message delivery with acknowledgement.
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.
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".
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.