AWS IoT Jobs Data Plane

Name: AWS IoT Jobs Data Plane API
Brand: AWS IoT Jobs Data Plane
Availability: InStock

★ Only Publicly Available SpecIOTDevice Managementhmac4 EndpointsREST

For Agents

Allow devices and device-side automation to fetch pending IoT Jobs, start the next pending execution, and update job execution status as work progresses on the device.

Quickstart

Get started with AWS IoT Jobs Data Plane in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"start the next pending aws iot job"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with AWS IoT Jobs Data Plane API.

List pending and in-progress job executions for a specific thing

Start the next pending job execution on a thing and atomically mark it IN_PROGRESS

Describe a specific job execution to fetch its job document and current status

Update a job execution's status to IN_PROGRESS, SUCCEEDED, FAILED, REJECTED, or REMOVED

GET STARTED

Start building with AWS IoT Jobs Data Plane API

Explore with Jentic

View OpenAPI Spec

Jentic publishes the only available OpenAPI specification for AWS IoT Jobs Data Plane, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for AWS IoT Jobs Data Plane, keeping it validated and agent-ready. AWS IoT Jobs are remote operations — firmware updates, reboots, certificate rotations, configuration pushes — sent to one or more devices connected to AWS IoT. The Jobs Data Plane is the device-facing runtime API that lets devices fetch their pending job executions, mark them in progress, and report success or failure. It is a small 4-endpoint surface focused entirely on the device side of the job lifecycle.

Use Cases

Patterns agents use AWS IoT Jobs Data Plane API for, with concrete tasks.

★ Over-the-Air Firmware Rollout

Devices pick up firmware update jobs by calling StartNextPendingJobExecution at boot or on a schedule. The job document points at a signed firmware artifact in S3; once the device installs it, UpdateJobExecution reports SUCCEEDED. Failed installs report FAILED with statusDetails so the fleet operator can roll back or retry.

Call PUT /things/thing-42/jobs/$next with statusDetails={} to claim the next pending job, install the artifact, then call POST /things/thing-42/jobs/{jobId} with status=SUCCEEDED

Certificate Rotation Workflow

Use IoT Jobs to coordinate scheduled certificate rotation across a fleet. The device fetches the rotation job, generates a new key pair, requests a fresh certificate via the control plane, and reports back via UpdateJobExecution. Status details allow it to pass back the new certificate ID for audit and reconciliation.

Call DescribeJobExecution to read the rotation job document, then UpdateJobExecution with status=SUCCEEDED and statusDetails containing the new certificate ID once rotation completes

Configuration Push with Progress Reporting

For multi-step configuration jobs, devices report incremental progress by repeatedly calling UpdateJobExecution with status=IN_PROGRESS and a fresh statusDetails map. The fleet operator sees step-level state in the IoT Jobs console without the device leaking telemetry through MQTT topics.

Call POST /things/thing-42/jobs/{jobId} with status=IN_PROGRESS and statusDetails={"step":"download_complete","percent":"50"}

AI Agent Edge Job Operations

Through Jentic, an AI agent embedded in or alongside a device runtime can drive the job lifecycle on the device side — claiming the next pending job, executing the work, and reporting status. Jentic exposes the 4 Jobs Data Plane operations as discoverable tools so the agent picks the right call from intent.

Search Jentic for 'start next aws iot job', load the StartNextPendingJobExecution schema, and execute it for the relevant thingName

Key Endpoints

4 endpoints — jentic publishes the only available openapi specification for aws iot jobs data plane, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/things/{thingName}/jobs

GetPendingJobExecutions — list pending and in-progress executions for a thing

PUT

/things/{thingName}/jobs/$next

StartNextPendingJobExecution — claim the next pending job and mark it IN_PROGRESS

GET

/things/{thingName}/jobs/{jobId}

DescribeJobExecution — fetch a specific job execution and its job document

POST

/things/{thingName}/jobs/{jobId}

UpdateJobExecution — update status and statusDetails on a job execution

GET

/things/{thingName}/jobs

GetPendingJobExecutions — list pending and in-progress executions for a thing

PUT

/things/{thingName}/jobs/$next

StartNextPendingJobExecution — claim the next pending job and mark it IN_PROGRESS

GET

/things/{thingName}/jobs/{jobId}

DescribeJobExecution — fetch a specific job execution and its job document

POST

/things/{thingName}/jobs/{jobId}

UpdateJobExecution — update status and statusDetails on a job execution

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

AWS access keys for IoT Jobs Data Plane are stored encrypted in the Jentic vault. Agents never see the raw credentials — Jentic signs each request with SigV4 server-side.

Intent-based discovery

Agents search Jentic with intents like 'start next aws iot job' or 'update job execution status' and get back the matching operation with its input schema.

Time to first call

Direct integration: half a day to wire up SigV4 signing and the small set of job lifecycle calls. Through Jentic: under 15 minutes.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

AWS IoT Data Plane

Companion data-plane API for MQTT publish and device shadow operations

Use IoT Data Plane for shadow updates and topic publish; use IoT Jobs Data Plane specifically for the job execution lifecycle.

Complementary

AWS Greengrass

Edge runtime that can host job-handling logic close to the device

Use Greengrass to run job handler code at the edge; use IoT Jobs Data Plane to fetch and update the job state itself.

Complementary

AWS IoT Events

Detector models that can react when job executions enter specific states

Use IoT Events to alert on patterns of job failures; use IoT Jobs Data Plane to drive the underlying execution lifecycle.

FAQs

Specific to using AWS IoT Jobs Data Plane API through Jentic.

Why is there no official OpenAPI spec for AWS IoT Jobs Data Plane?

AWS does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call AWS IoT Jobs Data Plane via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the AWS IoT Jobs Data Plane API use?

The API uses AWS Signature Version 4 (HMAC) request signing. Devices typically authenticate via certificate-based MQTT, but the HTTPS endpoint covered by this spec uses SigV4 with an AWS access key. Through Jentic, requests are signed server-side.

Can I claim the next pending job for a thing through the API?

Yes. Call PUT /things/{thingName}/jobs/$next with an optional statusDetails and stepTimeoutInMinutes. The response returns the job document and execution metadata, and the execution is atomically transitioned to IN_PROGRESS so other clients cannot claim the same job.

What are the rate limits for the AWS IoT Jobs Data Plane API?

AWS applies per-account, per-region request quotas to Jobs Data Plane operations and these vary by call. UpdateJobExecution has lower throughput than GetPendingJobExecutions. Check AWS Service Quotas for current limits.

How do I report a job as completed through Jentic?

Search Jentic for 'update aws iot job execution', load the UpdateJobExecution schema, and execute with thingName, jobId, and status=SUCCEEDED. Optionally include statusDetails to record outcome metadata for audit.

What is the difference between this API and the IoT Jobs control plane?

This data-plane API is what devices and device-side agents use at runtime to fetch and report on jobs. The control plane (part of the IoT Core API) is what fleet operators use to create, target, and cancel jobs. The two surfaces share the same JobExecution resource.