render-background-workers

✓ Official★ 4,081

by openai · part of openai/plugins

Sets up and configures background workers on Render for queue-based job processing. Use when the user needs to process async jobs, consume from a queue, run Celery/Sidekiq/BullMQ/Asynq/Oban workers, handle graceful shutdown with SIGTERM, wire a worker to Key Value (Redis), or choose between workers and cron jobs for background work. Trigger terms: background worker, async jobs, queue consumer, Celery, Sidekiq, BullMQ, Asynq, Oban, job processing, SIGTERM, graceful shutdown.

🧩 One of 7 skills in the openai/plugins package — works on its own, and pairs well with its siblings.

This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.

Render Background Workers

This skill explains worker services on Render: processes that consume jobs from a queue instead of serving HTTP. Pair with render-blueprints, render-env-vars, and render-networking when wiring render.yaml and private connectivity.

When to Use

Designing or debugging queue-backed workers (Celery, Sidekiq, BullMQ, Asynq, etc.)
Choosing between a worker, Cron Job, or Workflow for background work
Configuring Render Key Value as a broker (not a cache) with correct eviction policy
Implementing graceful shutdown so in-flight jobs are not lost on deploy

Per-framework setup and signal-handling detail: references/queue-framework-setup.md, references/graceful-shutdown.md.

How Workers Work

Long-running services with no inbound (HTTP) traffic. Render does not expose a public URL or internal hostname for workers the way it does for web or private services—workers cannot receive private network traffic directed at them.
The typical pattern is a poll loop: the process connects to a queue backend (often Render Key Value, Redis-compatible Valkey 8) and pulls jobs.
Workers can initiate outbound connections on the private network—to PostgreSQL, Key Value, private services, web services (internal URLs), and the public internet—subject to your plan and firewall rules.

Queue Framework Overview

Framework	Language	Queue backend	Notes
Celery	Python	Redis / Key Value	Most common Python task queue
Sidekiq	Ruby	Redis / Key Value	Standard for Rails
BullMQ	Node.js	Redis / Key Value	Modern Node queue (Redis-based)
Asynq	Go	Redis / Key Value	Go async task processing
Oban	Elixir	Postgres (not Redis)	Queue stored in the database

Pairing with Key Value

Use Render Key Value as the job broker when your framework expects Redis.
Set maxmemory policy to noeviction. allkeys-lru and similar policies are for caches; evicting queue keys drops jobs.
Wire REDIS_URL (or your framework’s equivalent) via fromService with type: keyvalue and property: connectionString in the Blueprint.
Blueprints require ipAllowList on Key Value—include the CIDRs that should reach the instance (often [] for private-network-only access; see render-blueprints / Key Value field reference).

See references/queue-framework-setup.md for minimal app + YAML examples.

Worker vs Cron vs Workflow

Need	Use	Why
Always-on queue consumer	Background Worker	Polls continuously; long-lived process
Periodic scheduled task	Cron Job	Runs on a schedule, exits; 12h max per run
Distributed parallel compute	Workflow	Each run gets its own instance; fan-out patterns
High-volume or bursty jobs	Workflow	Scales per run; no idle instance cost between runs

Graceful Shutdown

Before stopping an instance, Render sends SIGTERM, then waits up to maxShutdownDelaySeconds (1–300, default 30) before SIGKILL.
Workers should: (1) stop accepting new jobs, (2) finish the current job or checkpoint progress, (3) close connections, (4) exit 0.
Set maxShutdownDelaySeconds to at least your longest safe job duration (see Dashboard or Blueprint).

Language- and framework-specific handlers: references/graceful-shutdown.md.

References

Topic	File
Celery, Sidekiq, BullMQ, Asynq, Oban setup + YAML	`references/queue-framework-setup.md`
SIGTERM, `maxShutdownDelaySeconds`, per-language patterns	`references/graceful-shutdown.md`

render-deploy — First deploy, CLI, service creation
render-blueprints — Full render.yaml schema, fromService, projects
render-networking — Private URLs, what can call what
render-scaling — Worker plans, instance counts, limits

Copy & paste — that's it

npx skills add https://github.com/openai/plugins --skill render-background-workers

Run this in your project — your agent picks the skill up automatically.

Blueprint Configuration

Minimal pattern: type: worker, runtime, buildCommand, startCommand, and envVars wired from Key Value.

services:
  - type: keyvalue
    name: jobs
    plan: starter
    region: oregon
    ipAllowList: []

  - type: worker
    name: task-worker
    runtime: python
    region: oregon
    plan: starter
    buildCommand: pip install -r requirements.txt
    startCommand: celery -A tasks worker --loglevel=info
    envVars:
      - key: REDIS_URL
        fromService:
          name: jobs
          type: keyvalue
          property: connectionString

Optional: maxShutdownDelaySeconds on the worker service for longer draining jobs.