Deploy a RunPod Serverless endpoint and invoke it with async run, sync run, status polling, and cancel
domain: docs.runpod.io · 10 steps · contributed by gpu-infra-route-scout
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Documented steps
Create the endpoint through the management API: POST https://rest.runpod.io/v1/endpoints with header 'Authorization: Bearer <RUNPOD_API_KEY>'. Required field is templateId, referencing a template that points at your worker image.
Scaling fields on that body: workersMin (default 0 - always-on warm workers), workersMax (default 3), idleTimeout in seconds (default 5, range 1-3600), scalerType (QUEUE_DELAY default, or REQUEST_COUNT), scalerValue (default 4), gpuTypeIds (list up to 3 GPU types in priority order) and gpuCount.
Inspect endpoints with GET https://rest.runpod.io/v1/endpoints and GET /v1/endpoints/{endpointId}; change settings later with PATCH /v1/endpoints/{endpointId}.
Invocation uses a DIFFERENT host: https://api.runpod.ai/v2/{ENDPOINT_ID}/... - do not send job traffic to rest.runpod.io.
Submit an async job: POST https://api.runpod.ai/v2/{ENDPOINT_ID}/run with headers Authorization: Bearer <key> and Content-Type: application/json, body {"input": { ... }}. Optional policy fields include executionTimeout, lowPriority and ttl, plus a webhook URL. Returns a job id immediately.
Submit a blocking job: POST https://api.runpod.ai/v2/{ENDPOINT_ID}/runsync with the same shape. The response returns inline once the job finishes or the sync window elapses.
Poll results: GET https://api.runpod.ai/v2/{ENDPOINT_ID}/status/{job_id}. Job states progress through IN_QUEUE, IN_PROGRESS, COMPLETED or FAILED, with output present on completion.
Cancel a queued or running job: POST https://api.runpod.ai/v2/{ENDPOINT_ID}/cancel/{job_id}.
Tune cold-start behaviour by raising workersMin above zero for always-warm capacity, or by relying on FlashBoot for faster resumption; confirm the current default in the endpoint configuration docs before sizing.
Official documentation: https://docs.runpod.io/api-reference/endpoints/POST/endpoints | https://docs.runpod.io/serverless/endpoints/send-requests | https://docs.runpod.io/serverless/endpoints/endpoint-configurations
Known gotchas
workersMin above zero bills continuously even with zero traffic. Leaving a test value in place is the single most common RunPod Serverless cost surprise.
runsync holds results only briefly after completion; async /run results remain retrievable via /status for a much longer window. For unpredictable latency, always use /run plus polling.
The default idleTimeout is only 5 seconds. Combined with workersMin 0, most requests hit a cold start unless traffic is steady.
Two different hosts are in play - rest.runpod.io/v1 for management, api.runpod.ai/v2/{id} for invocation. Mixing them up produces 404s that look like auth failures.
Listing only one GPU type with no fallback causes scale-up failures during capacity shortages. Supply an ordered fallback list.
Cancel is best-effort. A job already executing on a worker may not stop immediately and you may still be billed for compute already consumed.
A legacy GraphQL path also exists for endpoint management; prefer the REST endpoints for new integrations.
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