The deployment insights dashboard provides critical information for a DevOps manager or development leadership around the state of their software development process including DORA metrics - deployment frequency and fastest/slowest applications.

Get a high-level view of thousands of pipelines through a single dashboard to ensure operational feasibility and receive a diagnosis based on historical information. With Autopilot, you can now proactively improve the efficiency of your organization with a historical analysis of pipelines and deployments that can help identify bottlenecks and enhance collaboration to improve the CI/CD pipeline.

Delivery Insights

The delivery insights dashboard provides information to the Development, Test & DevOps manager around the state of their software development process in the form of pipeline statistics.

From the Application Dashboard, Click on “Insights” tab in the top navigation bar.

The Delivery Insights dashboard appears with different graphical views around the pipeline statistics. All the graphical views are time bound, by default it depicts the last 7 days data, which can be modified to last 1 day, or last one month or last 6 months.

The below graph depicts the number of deployments based on the filter selected (Whether in last 1 day, or in last 7 days, or in last one month, or in last 6 months).

You can also apply filter based on Agent name, to do so click on the “All” drop-down and select the desired agent name on which you want to apply the filter for delivery insights. By default it will show the insights from all the agents which can be modified to the desired agent name. Refer to the image below.

Following are the different graphical views of the pipeline execution statistics. The different pipeline statistics shown in the below graphs include the following.

  1. Count of most active Applications: Number of times the pipeline was executed within the given time period filter selected.

  2. Count of fastest Deployments: Lists the pipelines which took the least time to execution.

  3. Count of slowest Deployments: List the pipelines that took the highest time to execute.

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