Overview
The Tasks API manages the work task queue for asynchronous operations like pipeline execution, ML training, and digital twin updates. These endpoints require authentication whenWORKER_AUTH_TOKEN is configured.
List Work Tasks
Returns the current queue length.Response
Current number of tasks in the queue
Submit Work Task
Submits a new work task to the queue.Request Body
Task type:
pipeline_execution, ml_training, ml_inference, or digital_twin_updateTask priority (higher = higher priority, defaults to 1)
Project ID
Task-specific parameters
Resource requirements
Data access configuration
Response
Work task ID
Task type
Current status:
queued, scheduled, spawned, executing, completed, failed, timeout, or cancelledTask priority
ISO 8601 timestamp
ISO 8601 timestamp (if started)
ISO 8601 timestamp (if completed)
Project ID
Task-specific parameters
Resource requirements
Data access configuration
Error message (if failed)
Kubernetes job name (if spawned)
Cluster task was dispatched to
Number of retry attempts
Maximum retry attempts
Reason for retry
Get Work Task
Returns a single work task by ID.Path Parameters
Work task ID
Response
Returns the work task object (see Submit Work Task for schema).Update Work Task Status
Updates the status of a work task. Called by worker jobs to report progress.Path Parameters
Work task ID
Request Body
Work task ID (must match path parameter)
New status:
executing, completed, failed, timeout, or cancelledOutput location (for completed tasks)
Additional metadata
Error message (for failed tasks)
Response
Automatic Retry
The system automatically retries tasks with transient errors (OOMKilled, Evicted, DeadlineExceeded). Tasks are requeued with incremented retry count up to the maximum retry limit.Get Metrics
Returns queue and task metrics.Response
Queue metrics
Task counts grouped by status
Task counts grouped by type
ISO 8601 timestamp of metrics snapshot