Pipeline reports
Automation streamlines delivery. Even so, true governance requires data visibility. Deployment Manager offers powerful reporting tools that provide end-to-end visibility across pipelines. From deployment success rates to quality adherence, approvals and manual interventions, teams can track every stage of their release process.
Automated reports help measure performance, identify trends, and uncover opportunities for improvement. With clear data and governance, teams can drive continuous improvement plans towards predictable and compliant releases.
Some effective ways to make use of these reports for enhanced control and collaboration are to:
- Use reports as gatekeepers to identify and block risky deployments before they reach production.
- Define quality thresholds for automated deployments, to ensure that test pass rates and compliance requirements are met before advancing the deployment to the next pipeline stage.
- Align stakeholders with reports that present unified insights into release progress, quality, and governance.
By embedding governance using reports, teams can transform data into decisions that ensure every deployment is compliant and confidently implemented.
Pipeline reports
Pipeline reports in Deployment Manager provide visibility into the frequency, duration, and success of your deployments. While these reports present KPIs, their true power lies in how you interpret and apply them.
Industry-standard DevOps Research and Assessment (DORA) metrics such as, Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Recovery, all serve as benchmarks for high-performing DevOps teams. By mapping pipeline reports to these metrics, you can transform deployment data into actionable insights and governance standards.
Check your knowledge with the following interaction:
Pipeline run reports help with capturing key metrics such as:
- Number of runs
- Deployment success/failure rates
- Average run time
- Stage-level performance insights
Every deployment is a reflection of your delivery process. By analyzing the above metrics from Pipeline reports, teams can:
- Detect patterns in failures or delays.
- Benchmark performance across applications or teams.
- Track compliance with release governance standards.
- Align outcomes to DevOps success metrics.
Check your knowledge with the following interaction:
Mapping Pipeline reports to DORA metrics
| DORA Metric
|
Corresponding Pipeline report metric
|
How to interpret
|
Governance |
|---|---|---|---|
| Deployment frequency
|
|
A higher count of runs indicates frequent releases. Low counts may signal that teams are holding back changes and creating risk buildup. As a best practice, the success rates and the frequency of deployments must be high. |
|
| Lead time for changes |
|
Long durations highlight bottlenecks, often in testing or approvals. Short lead times reflect efficient delivery. |
|
| Change failure rate
|
|
A high ratio of failures means the development cycle needs improvement to avoid bugs and issues. Trends by stage show where the issues are concentrated |
|
| Mean Time to Recovery (MTTR) |
|
Short MTTR = resilient processes Long MTTR = poor rollback or recovery practices |
|
The following figure shows the comprehensive view that the dashboard provides of the ManageSigning deployment pipeline's performance, displaying key metrics such as deployment success rate, pipeline completion frequency, failure rates, and average time taken across different stages:
Establishing governance with pipeline reports
Organizations can establish governance frameworks around their release process by:
- Defining KPIs: Establish clear, measurable targets to track deployment quality and reliability. For example: All teams must maintain a deployment failure rate of less than 5%.
- Benchmarking across teams: Compare pipelines for different applications to identify both high performers and areas needing improvement.
- Automating alerts: Configure notifications when failure rates or lead times exceed defined governance thresholds.
- Continuous improvement cycles: Use insights from each release to run retrospectives, focusing on failures, delays, and emerging trends.
Best practices while tracking deployment metrics:
- Analyze trends, not just snapshots - Compare patterns across time periods (for example, monthly or quarterly) rather than focusing on a single pipeline.
- Leverage reports for leadership reviews - Use reports to facilitate discussions on DevOps maturity during leadership meetings.
- Integrate multiple reports for a holistic view - Combine pipeline reports with deployment and application quality reports to achieve end-to-end governance view.
- Promote team ownership of metrics - Encourage teams to self-serve their data and take responsibility for driving improvements.
Check your knowledge with the following interaction:
This Topic is available in the following Module:
If you are having problems with your training, please review the Pega Academy Support FAQs.
Want to help us improve this content?