Diagnostic view
The Diagnostic view provides detailed insights into delivery mechanics and engineering signals across SHIP-HATS systems.
It highlights indicators that influence how efficiently changes move from development to production, helping teams identify bottlenecks, delays, or operational friction within the delivery process.
This view is typically used after observing trends in the Operational view, when teams need to investigate factors affecting delivery cadence.
What it shows
The Diagnostic view surfaces indicators across several stages of the delivery process, including:
- Development workflow throughput
- CI/CD pipeline performance and stability
- Deployment lead time and change flow
- Engineering process quality signals
- Code and system quality indicators
These insights help teams identify where delivery friction occurs and determine what improvements may restore or sustain delivery flow.
Production deployment performance
This section provides insights into deployment activity in Production environments.
| Metric | Description |
|---|---|
| Number of production deployments | Total number of production deployments during the selected duration. |
These metrics help teams understand deployment activity levels during the selected time period.
Production deployment change performance
This section focuses on how quickly code changes move from development to Production deployment.
| Metric | Description |
|---|---|
| Production deployment change lead time | Time taken for a change to move from development to Production deployment. Lower values indicate faster delivery flow. |
This metric helps teams assess how efficiently changes are delivered to Production.
Merged MR performance
This section provides insights into development workflow throughput and merge request efficiency.
| Metric | Description |
|---|---|
| Number of merged MRs | Total number of merge requests successfully merged during the selected duration. |
| Merged MR cycle time | Time taken for a merge request to move from creation to merge. Lower values indicate faster development flow. |
These indicators help teams understand how efficiently development work moves through the merge process.
CI/CD pipeline performance
This section highlights the performance and reliability of pipelines triggered during development workflows.
| Metric | Description |
|---|---|
| Fast pipeline duration | Time taken for shorter pipelines to complete. |
| MR pipeline duration | Time taken for pipelines triggered by merge requests to complete. |
| Stabilised pipeline duration and flakiness | Indicators showing pipeline stability and reliability over time. |
Efficient and stable pipelines help reduce delays in validating and deploying code changes.
Process quality
The Process Quality section highlights indicators related to development workflow practices and delivery readiness.
| Metric | Description |
|---|---|
| User story acceptance rate | Indicates how consistently completed work meets acceptance criteria. |
| DevSecOps maturity score | Reflects adoption of DevSecOps practices across systems. |
These indicators provide context on how effectively teams follow development and delivery practices.
Code quality
The Code Quality section provides insights into issues detected during development or testing.
| Metric | Description |
|---|---|
| Open vulnerabilities | Security vulnerabilities identified in the codebase. |
| Open bugs | Functional defects detected during development or testing. |
These signals help teams understand issues that may affect release confidence.
System quality
The System Quality section highlights issues affecting deployed systems, such as:
- Functional bugs detected in production environments
- Bugs reported during UAT or post-release validation
These indicators help teams understand whether system-level issues may influence release decisions.
How teams typically use this view
Teams commonly use the Diagnostic view to analyse delivery performance and identify improvement opportunities.
A typical workflow includes:
Baseline key metrics
Ensure environments and projects are correctly tagged so that deployment and pipeline data can be accurately analysed.Review metrics regularly
Monitor the metrics periodically to track delivery performance trends and determine whether systems are meeting desired delivery targets.Investigate improvement opportunities
Use signals from sections such as Merged MR Performance, CI/CD Pipeline Performance, and Production Deployment Change Performance to identify areas where delivery flow can be improved (for example, reducing MR cycle time or improving deployment success rate).
When to use it
Use the Diagnostic view when you need to:
- Investigate changes in deployment cadence observed in the Operational view
- Identify bottlenecks in development or CI/CD workflows
- Analyse pipeline performance and delivery delays
- Understand quality signals that may affect release decisions
After identifying and addressing the root causes of delivery friction, teams can return to the Operational view to verify improvements in delivery cadence.
