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Appendix: Workspace deletion procedure - Amazon IoT SiteWise
Step 1: Cancel or wait for enrichment jobs to finishStep 2: Wait for bulk import jobs to finishStep 3: Delete pipeline executions, pipelines, and tasksStep 4: Delete curated datasetsStep 5: Delete session datasetsStep 6: Delete time seriesStep 7: Delete the applicationStep 8: Delete the workspacePost-deletion behavior
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Appendix: Workspace deletion procedure

Important

Deleting a workspace and its associated resources is irreversible. Before starting, confirm that you no longer need the datasets, imported and enriched data, pipeline executions, pipelines, tasks, application, or time series.

Delete all resources within the workspace before deleting the workspace itself. For every List* operation, paginate through all results before proceeding to the next step.

Step 1: Cancel or wait for enrichment jobs to finish

  1. Call ListEnrichmentJobs for each dataset in the workspace.

  2. For every ongoing enrichment job, call CancelEnrichmentJob.

  3. Use DescribeEnrichmentJob to verify that each job reaches a terminal state (COMPLETED, FAILED, TIMED_OUT, or CANCELLED).

Step 2: Wait for bulk import jobs to finish

  1. Call ListBulkImportJobs for each dataset in the workspace.

  2. Bulk import jobs do not have a cancellation operation. Wait for every ongoing bulk import job to reach a terminal state before continuing.

  3. Use DescribeBulkImportJob to check job status when needed.

Step 3: Delete pipeline executions, pipelines, and tasks

  1. Call ListPipelineExecutions to identify pipeline executions in the workspace.

  2. Delete each pipeline execution by calling DeletePipelineExecution.

  3. Call ListPipelines, and delete each pipeline by calling DeletePipeline.

  4. Call ListTasks, and delete each task by calling DeleteTask.

Step 4: Delete curated datasets

  1. Call ListDatasets to identify Curated Datasets.

  2. For each Curated Dataset, call ListDatasetDataSegments.

  3. Remove the data-segment associations by calling BatchDisassociateDataSegmentsFromDataset.

  4. Delete the Curated Dataset by calling DeleteDataset.

Step 5: Delete session datasets

  1. Call ListDatasets to identify the remaining Session Datasets.

  2. Verify that no ongoing enrichment or bulk import jobs reference each Session Dataset.

  3. Delete each Session Dataset by calling DeleteDataset.

Step 6: Delete time series

  1. Call ListTimeSeries to identify time series in the workspace.

  2. Remove any resource associations that prevent deletion.

  3. Delete each time series by calling DeleteTimeSeries.

Step 7: Delete the application

Each workspace currently supports at most one application. Delete the application by calling DeleteApplication.

Step 8: Delete the workspace

  1. Optionally, call ListWorkspaces to verify the workspace you want to delete.

  2. Call DeleteWorkspace only after all associated resources have been deleted.

Post-deletion behavior

DeleteWorkspace is asynchronous. During the deletion workflow, the service automatically removes workspace-owned metadata and applied tags — no separate cleanup API is required. After the deletion workflow completes, the workspace no longer counts against the workspace quota for your account and Amazon Region.