Update a serverless endpoint
Partially updates a serverless endpoint. This is a PATCH: only the
fields present in the body are changed; omitted fields are left
untouched. See UpdateEndpointRequest for the full body.
Mutable fields: name, gpu, cpu, workers (min/max),
scaling (type/value/idleTimeout), dataCenterIds,
networkVolumes, timeout, flashboot, and the container settings
(image, args, disk, ports, env, registry).
Omitted compute preserves the current selection. cpu completely
replaces a CPU endpoint’s selection; compute family is immutable.
gpu on CPU, cpu on GPU, or both fields returns 400.
Returns 200 with the full updated endpoint. Effect timing differs
by field: scaling and worker-bound settings (workers, scaling,
timeout) are applied to the autoscaler promptly, while
container-affecting changes (e.g. image, env) create a new
endpoint release that rolls out as workers cycle — in-flight workers
keep the previous version until they are replaced. Track rollout via
listEndpointReleases.
Authorizations
Runpod API key authentication. Generate an API key in the Runpod console and send it in the Authorization header as Bearer <api_key>. Keys are scoped to the permissions granted when created; requests may return 403 when a valid key lacks access to the requested resource or action.
Path Parameters
Serverless endpoint identifier
Body
Only provided fields are changed.
Arguments passed to the container entrypoint
""
Container disk in GB (ephemeral, wiped on restart)
x >= 150
Environment variables as key-value pairs
Docker image reference
"runpod/pytorch:1.0.2-cu1281-torch280-ubuntu2404"
Exposed ports, formatted as port/protocol
Container registry credential ID (for private images)
null
Complete replacement CPU selection. Valid only for an existing CPU endpoint; endpoint compute family cannot be changed.
1Preferred data centers for placement. Omit or pass an empty array to let the scheduler choose.
FlashBoot cold-start acceleration mode.
OFF— disabledFLASHBOOT— enabledPRIORITY_FLASHBOOT— enabled with priority capacity
OFF, FLASHBOOT, PRIORITY_FLASHBOOT Partial GPU update — every field is optional and an omitted one is left
unchanged. Unlike create, pools is optional, so changing only a CUDA
constraint does not require resending the pool list.
excludedTypes requires pools, because the two are one selection and
only a supplied pools replaces it — an exclusion on its own would
otherwise be silently dropped.
1Autoscaling signal — a discriminated union on type: QUEUE_DELAY
(queue-based endpoints only) or REQUEST_COUNT. The scaler is chosen
independently of the endpoint's routing type and can be switched on
update.
- Option 1
- Option 2
ID of a serverless template whose container settings are
applied as if they were provided in this PATCH body (image,
args, disk, ports, env, registry). Explicit body fields
override the template's; env merges template and body per
key (body wins) and, per PATCH semantics, replaces the
endpoint's env. One-time application — no link to the
template is retained. Must be one of your templates or a
public template (unknown or inaccessible ID → 404); must be
a serverless template (→ 422).
"30zmvf89kd"
Response
OK
Reusable container configuration shared across templates, pods, and serverless endpoints. Adding a field here automatically propagates to all three resources.
"ep_abc123"
"my-inference"
Autoscaling signal — a discriminated union on type: QUEUE_DELAY
(queue-based endpoints only) or REQUEST_COUNT. The scaler is chosen
independently of the endpoint's routing type and can be switched on
update.
- Option 1
- Option 2
Per-request execution timeout in milliseconds
300000
FlashBoot cold-start acceleration mode.
OFF— disabledFLASHBOOT— enabledPRIORITY_FLASHBOOT— enabled with priority capacity
OFF, FLASHBOOT, PRIORITY_FLASHBOOT "2026-03-13T20:00:00Z"
Arguments passed to the container entrypoint
""
Container disk in GB (ephemeral, wiped on restart)
x >= 150
Environment variables as key-value pairs
Docker image reference
"runpod/pytorch:1.0.2-cu1281-torch280-ubuntu2404"
Exposed ports, formatted as port/protocol
Container registry credential ID (for private images)
null
Request-routing semantics for a modern serverless endpoint.
QUEUE— submit asynchronous or synchronous jobs through the managed queue.LOAD_BALANCER— send requests directly to worker-defined HTTP paths. Configure viaenv:PORT(server port, default 80),PORT_HEALTH(health-check port, default 80), andHEALTH_CHECK_PATH(path the load balancer polls for worker health, default/ping).
QUEUE, LOAD_BALANCER Request URLs appropriate to the endpoint's top-level type.
Queue-based endpoints provide job submission and management URLs;
load-balancing endpoints provide base and health because their
remaining paths are worker-defined.
- Option 1
- Option 2
Eligible CPU configurations for each worker, in the order they were submitted. Present for CPU endpoints and omitted for GPU endpoints. Memory is derived from the selected flavor's catalog RAM multiplier.
1