'queues' 검색 결과

This skill should be used when the user asks to "set up Cloudflare Queues", "create a message queue", "implement queue consumer", "process background jobs", "configure queue retry logic", "publish messages to queue", "implement dead letter queue", or encountering "queue timeout", "message retry", "throughput exceeded", "queue backlog" errors.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

You are an expert in amqplib, the Node.js client for RabbitMQ and AMQP 0-9-1 protocol. You help developers implement reliable message queuing with work queues, pub/sub fanout, topic routing, RPC patterns, dead letter queues, and message acknowledgment — building decoupled microservices that communicate asynchronously through RabbitMQ.

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Use when an "enable observability" card asks for queues, or a worker's queue.backlog / consumer lag signals are unbound - which exporter or direct broker data source reads Kafka, RabbitMQ, NATS and Redis queues, the metric names the recipes expect, and the consumer-side metrics the developer adds

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Unified expert guide for async job queues & durable workflows: BullMQ v5 (Redis queues), Trigger.dev v3 (serverless tasks), Inngest, and Temporal.io (distributed sagas) / Panduan ahli terpadu untuk antrean job asinkron & workflow tahan-gagal: BullMQ v5, Trigger.dev v3, Inngest, dan Temporal.io.

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Cloudflare platform management via Wrangler CLI, Agents SDK (v0.13+), and Browser Rendering API. Deploy Pages, Workers, KV, R2, D1, Queues, Vectorize, Workflows, Hyperdrive. Build stateful AI agents with the full SDK stack — Agent, AIChatAgent, Think, Voice, sub-agents, fibers, HITL, scheduling, observability, Code Mode (Dynamic Worker sandboxes). Budget web scraping via cf_browser.py. Use when deploying to Cloudflare, managing CF infrastructure, configuring wrangler.toml/wrangler.jsonc, building AI agents or chat agents on Workers, adding voice, orchestrating sub-agents, or for cheap web scraping. Triggers: Cloudflare, wrangler, Pages, KV, R2, D1, Workers, Vectorize, Queues, Workflows, Hyperdrive, cf_browser, Browser Rendering, Agents SDK, Code Mode, codemode, MCP, Think, AIChatAgent, Voice agent, sub-agents, fibers, HITL, Dynamic Workers.

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Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding instead).

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Configuring Salesforce lead management and conversion in Setup: lead settings, web-to-lead, conversion field mapping, lead queues, auto-response rules, lead processes. Trigger keywords: web-to-lead, lead conversion, lead field mapping, lead settings, lead process, lead queue, lead auto-response. NOT for Apex that controls what conversion creates - use apex/lead-conversion-customization. NOT for lead assignment rule logic - use admin/assignment-rules. NOT for duplicate rule configuration - use admin/duplicate-management. Also covers: LeadConvertSettings objectMapping XML, LeadConfigSettings, LeadStatus StandardValueSet converted flag, lead process BusinessProcess, Database.convertLead bulk conversion limits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

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Use when designing a background-job system, choosing between BullMQ / Sidekiq / RQ / Temporal / SQS, deciding queue-vs-workflow, sizing concurrency vs rate limits, building dead-letter queues, or making handlers idempotent. Triggers: jobs running twice on retry, lost jobs after worker crash, DLQ filling up, Redis OOM from job backlog, exactly-once requested, "do we need Temporal?", visibility timeout / lockDuration confusion, exponential backoff vs jitter, fan-out fan-in workflows. NOT for outbound webhook publishing (different concerns), receiver-side webhook handling (different concerns), event-streaming/Kafka topology, or in-process async (event loop only).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Auto-activate for litestar_saq, SAQPlugin, SAQConfig, QueueConfig, TaskQueues, CronJob, litestar workers run, background jobs, schedules, or SAQ UI. Not for litestar-queues, Celery, RQ, or Dramatiq.

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Cloudflare Workers CLIでWorkers、KV、R2、D1、Vectorize、Hyperdrive、Workers AI、Containers、Queues、Workflows、Pipelines、Secrets Storeを開発・デプロイ・管理する。Wranglerコマンドを実行する前に使用し、最新の公式ドキュメントに基づく構文と安全規則を確認する。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when designing a background-job system, choosing between BullMQ / Sidekiq / RQ / Temporal / SQS, deciding queue-vs-workflow, sizing concurrency vs rate limits, building dead-letter queues, or making handlers idempotent. Triggers: jobs running twice on retry, lost jobs after worker crash, DLQ filling up, Redis OOM from job backlog, exactly-once requested, "do we need Temporal?", visibility timeout / lockDuration confusion, exponential backoff vs jitter, fan-out fan-in workflows. NOT for outbound webhook publishing (different concerns), receiver-side webhook handling (different concerns), event-streaming/Kafka topology, or in-process async (event loop only).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

대규모 기능의 설계 제안을 의존 관계와 통과 기준이 있는 작업으로 나눕니다. 여러 에이전트의 조사, 구현, 테스트, 검토부터 통합과 최종 검증까지 정리합니다.

• 큰 설계 제안을 검증 가능한 작업으로 나눕니다
• 여러 에이전트에 의존 관계가 있는 일을 배정합니다
• 변경 브랜치를 검토하고 순서대로 통합합니다

Laravel 프로젝트의 환경, 코드 검사, 테스트, 의존성 취약점, 데이터베이스 변경과 큐를 순서대로 확인해 병합이나 배포 전 문제를 점검합니다.

• Laravel 풀 리퀘스트 전 점검
• 대규모 리팩터링이나 의존성 갱신 후 검증
• 스테이징 및 운영 환경 배포 전 점검

PHPUnit 또는 Pest로 Laravel 기능을 테스트부터 구현합니다. 모델, API, 인증과 권한을 검증하고 외부 서비스를 모의 처리하며 테스트가 실행한 코드 범위를 확인합니다.

• Laravel 기능을 테스트부터 구현합니다
• API 인증과 권한을 검증합니다
• 결제, 메일과 큐를 모의 처리합니다

Claude Code의 기억, 정기 실행, 작업 대기열을 결합해 지속적인 작업을 설계합니다. 외부 실행 환경과 화면 조작 연동 설정도 안내합니다.

• 풀 리퀘스트를 정기적으로 확인할 때
• 매일 조사 결과를 모아 요약할 때
• 기억한 맥락으로 회의를 준비할 때

Coordinate groups of AI agents in the cloud with Flow Nexus. Assign research or development tasks, automate workflows triggered by events or schedules, and monitor execution, queues, and agent capacity through the platform's tools.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Split research and analysis across multiple agents
• Coordinate development across repositories
• Automate testing, builds, and deployment

Build Python applications that keep other tasks moving while waiting for network, database, or file operations. Guides the choice of asyncio patterns, with timeouts, cancellation, error handling, and testing for asynchronous code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an asynchronous web API
• Fetch multiple web pages concurrently
• Develop a WebSocket server or chat system

Trace queued jobs from submission to their eventual effects in a CTF sandbox. Compare request-time and worker-time settings, follow retries and failed-message handling, and document the smallest sequence that explains a worker-specific result.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Trace a queued payload to its eventual downstream effect
• Compare request-time settings with worker runtime state
• Investigate retries and dead-letter queue handling

Create shareable links that open specific Arize resources, including traces, datasets, and evaluators. Use IDs from logs or exported data, with suitable time ranges, to direct teammates to the relevant view.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Share a trace with teammates
• Open an Arize view from IDs in logs
• Link directly to a dataset or evaluator

Investigate SGLang serving failures by collecting server state, preserving failing requests, and replaying them on a clean target. Summarize evidence and likely causes, then choose the next debugging tool for crashes, stalls, or performance regressions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate failed health checks and growing queues
• Reproduce request-specific timeouts or crashes
• Investigate output changes after deployment

Build Python applications that keep other tasks moving while waiting for network, file, or database operations. The skill guides asyncio patterns, task cancellation, timeouts, workload limits, and testing for asynchronous APIs, scrapers, and background processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building asynchronous web APIs
• Sending concurrent requests in web scrapers
• Designing background tasks and queues

Coordinates specialist agents in Claude Code to work from product requirements through design, implementation, testing, deployment, and operations. Includes task queues, saved progress, parallel reviews, and recovery workflows for managing extended development work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning product requirements into development tasks
• Coordinating implementation, testing, and reviews
• Resuming extended work from saved progress