Pipeline Insights Field Reference
Pipeline Insights offers a comprehensive set of data fields that organizations can use to construct sophisticated dashboards, generate detailed reports, and perform advanced analytics on their CI/CD pipeline metrics.
Overview
note
The Step Executions explore has been deprecated. Please use Step Executions v2 instead.
Dashboards using the old Step Executions explore will continue to function; however, we strongly recommend switching to Step Executions v2, which displays all executed steps rather than only six selected steps.
Pipeline Insights provides three main data explores:
- Pipeline Executions: High-level pipeline run data
- Stage Executions: Individual stage performance within pipelines
- Step Executions v2: Granular step-level execution details
Each explore contains Dimensions (attributes for grouping and filtering) and Measures (calculated metrics for analysis).
Pipeline Executions
Track overall pipeline performance, success rates, and execution patterns.
Dimensions
| Field | Description |
|---|---|
| Duration | Total time taken for the pipeline execution |
| End Time | When the pipeline finished (available as date, month, quarter, time, year, week) |
| Error Message | Error details for failed pipeline runs |
| Execution ID | Unique identifier for each pipeline execution |
| Name | Pipeline name |
| Pipeline ID | Unique identifier for the pipeline definition |
| Pipeline URL | Direct link to the pipeline in Harness UI |
| Start Time | When the pipeline run began (available as date, month, quarter, time, year, week) |
| Status | Execution outcome (Success, Failed, etc.) |
Measures
| Field | Description |
|---|---|
| Duration | Statistical analysis of execution times (Average, 10th, 25th, 75th, 80th, 90th, 95th percentiles) |
| Execution Count | Total number of pipeline executions in the selected time period |
| Failure Rate | Percentage of executions that failed (includes Failed, Aborted, Rejected, Error, Expired, Discontinuing statuses) |
| Last Execution Time | Most recent execution timestamp for the pipeline |
| Success Rate | Percentage of executions that completed successfully |
Stage Executions
Analyze individual stage performance within your pipelines.
Dimensions
| Field | Description |
|---|---|
| Duration | Time taken for the stage execution |
| End Time | When the stage completed (available as date, month, quarter, time, year, week) |
| Execution ID | Unique identifier for the stage execution |
| Is Evaluated | Whether conditional evaluation was performed (Yes/No) |
| Is Input Configured | Whether the stage had configured input parameters (Yes/No) |
| Is Rollback | Whether this is a rollback stage (Yes/No) |
| Name | Stage display name |
| Pipeline ID | Parent pipeline identifier |
| Pipeline Status | Status of the parent pipeline after this stage |
| Stage ID | Unique identifier for the stage definition |
| Start Time | When the stage began execution (available as date, month, quarter, time, year, week) |
| Status | Stage execution outcome (Succeeded, Failed, etc.) |
| Type | Stage category (Approval, Deployment, Custom, etc.) |
| When Condition | Conditional logic that determined if the stage should run |
Measures
| Field | Description |
|---|---|
| Duration | Statistical analysis of stage execution times (Average, 10th, 25th, 75th, 80th, 90th, 95th percentiles) |
| Execution Count | Total number of stage executions |
| Failure Rate | Percentage of stage executions that failed (includes Failed, Aborted, Rejected, Error, Expired, Discontinuing statuses) |
| Last Execution Time | Most recent stage execution timestamp |
| Stage Count | Number of stages across all pipeline runs in the selected scope |
| Success Rate | Percentage of stage executions that completed successfully |
| Total Pipeline Runs | Total pipeline executions in the selected scope (useful for context and normalization) |
Step Executions
Examine detailed step-level execution data for granular analysis.
Dimensions
| Field | Description |
|---|---|
| Duration | Time taken for the individual step execution |
| End Time | When the step completed (available as date, month, quarter, time, year, week) |
| Execution ID | Unique identifier for the step execution |
| Name | Step display name |
| Pipeline ID | Parent pipeline identifier (for tracing back to pipeline level) |
| Stage Execution ID | Parent stage execution identifier |
| Start Time | When the step began execution (available as date, month, quarter, time, year, week) |
| Status | Step execution outcome (Success, Failed, Skipped, etc.) |
| Step ID | Unique identifier for the step definition |
| Type | Step category (script, plugin, approval, etc.) |
Measures
| Field | Description |
|---|---|
| Duration | Statistical analysis of step execution times (Average, 10th, 25th, 75th, 80th, 90th, 95th percentiles) |
| Execution Count | Total number of step executions in the selected scope |
| Failure Rate | Percentage of step executions that failed (includes Failed, Aborted, Rejected, Error, Expired, Discontinuing statuses) |
| Last Execution Time | Most recent step execution timestamp |
| Step Count | Total number of steps across all pipelines (useful for aggregate analysis) |
| Success Rate | Percentage of step executions that completed successfully |
Account Context Fields
These fields provide organizational context and are available across all explores.
| Field | Description |
|---|---|
| Account ID | Your Harness account identifier |
| Organization ID | Organization identifier within your account |
| Project ID | Project identifier for scoping data |
Usage Tips
- Time-based Analysis: Use Start Time and End Time dimensions with different granularities (date, week, month, quarter, year) for trend analysis
- Performance Monitoring: Combine Duration measures with percentile breakdowns to identify performance outliers
- Success Tracking: Use Success Rate and Failure Rate measures to monitor pipeline reliability
- Hierarchical Analysis: Link Pipeline ID → Stage Execution ID → Step Execution ID to drill down from high-level trends to specific issues
- Filtering: Use Status dimensions to focus on specific execution outcomes
- Comparative Analysis: Use Execution Count measures to understand volume patterns across different time periods