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Found 10 Skills
Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
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.
Build async message queues with Cloudflare Queues for background processing. Use when: handling async tasks, batch processing, implementing retries, configuring dead letter queues, managing consumer concurrency, or troubleshooting queue timeout, batch retry, message loss, or throughput exceeded. Prevents 13 documented errors including multi-dev limitations, remote binding conflicts, and DLQ issues.
Expert in background jobs and message queues using Gravito Quasar. Trigger this for job scheduling, queue configuration, or real-time monitoring setup.
Architecture async-first avec messaging et queues (Symfony Messenger, Laravel Queue, Ecotone). Use when working with async processing, queues, workers, background jobs.
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.
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.
Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
This skill should be used when the user designs a "message queue", reaches for "Kafka", "RabbitMQ", "SQS", "Kinesis", "pub/sub", or "event-driven" architecture, asks about "async processing", "background jobs", "stream processing", or wrestles with "exactly-once vs at-least-once", "delivery guarantees", "message ordering", "duplicate handling / dedup", "dead letter queue", "backpressure", "saga orchestration", or "durable workflow". Use it whenever a slow or spiky operation should move off the request path, or two services must be decoupled, even if the user doesn't say "queue".
Event-driven architecture patterns including message queues, pub/sub, event sourcing, CQRS, and sagas. Use for async messaging, distributed transactions, event stores, domain/integration events, data streaming, choreography/orchestration, or integrating with Kafka, RabbitMQ, Pulsar, SQS/SNS, or NATS.