Dora Dashboard
Last updated
Last updated
The DORA Dashboard is a tool to track and measure your team's DevOps performance using four key metrics. These metrics—Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Recovery (MTTR)—provide insights into the speed, quality, and resilience of your software delivery process. They are commonly used to assess how well your development and operations teams are working together to deliver software efficiently and reliably.
Understanding and optimizing these metrics can help your team improve performance, reduce downtime, and ensure a smoother, more efficient release process.
Definition: Deployment Frequency measures how often new code is successfully deployed to production. It indicates the agility and efficiency of your software delivery process. High Deployment Frequency means your team is delivering updates, new features, and bug fixes to end-users rapidly and frequently.
Why it matters: Frequent deployments allow your team to deliver value to users faster, incorporate feedback quickly, and reduce the time spent on each release. High deployment frequency is a sign of an efficient and agile development pipeline.
Benchmarks:
High: Multiple releases per day or more than one a week. Indicates a highly efficient and agile process, allowing teams to rapidly respond to user needs and continuously deliver value.
Medium: Deployments between once a week and once a month. Shows steady delivery but indicates there may be room to streamline processes or remove bottlenecks.
Low: Deployments less than once a month. Suggests slow and potentially risky release processes, with opportunities to speed up deployment by improving automation and reducing manual steps.
Definition: Lead Time for Changes measures the time it takes from when a code change is committed to when it’s successfully deployed to production. This metric reveals how quickly your team can move from development to delivery, which is key for responding to feedback and introducing improvements.
Why it matters: A shorter lead time means faster delivery of features, quicker resolution of bugs, and a more responsive development team. It also suggests that the processes between code commit and production—such as testing, approval, and deployment—are well optimized.
Benchmarks:
High: Code changes are deployed within one day to one week. Reflects an efficient and optimized pipeline, where code moves quickly from development to production.
Medium: Code changes are deployed within one week to one month. Indicates a moderate pace of delivery, with potential areas for improvement in testing, approval, or deployment processes.
Low: Code changes take between one month and six months to reach production. Suggests significant delays, often due to bottlenecks in the development or release process, or extensive manual steps.
Definition: Change Failure Rate (CFR) tracks the percentage of deployments that result in failures that require remediation, such as rollbacks, hotfixes, or patches. It represents the stability of your release process and the quality of your testing and validation.
Why it matters: A low Change Failure Rate indicates that most changes are deployed successfully without introducing issues, while a high rate suggests that there are gaps in testing, code quality, or deployment practices that may lead to downtime or bugs in production.
Benchmarks:
High: 0% to 15% of changes result in failures. Indicates strong code quality and reliable testing practices, with minimal disruptions after deployment.
Medium: 16% to 30% of changes require remediation. Points to some weaknesses in the testing process or code quality, with room for improvement in pre-deployment validation.
Low: 31% to 45% of changes result in failures. Highlights significant issues in testing, code quality, or deployment processes, requiring immediate attention to improve stability.
Definition: Mean Time to Recovery (MTTR) measures the average time it takes to recover from a failure in production. This metric reflects your team's ability to respond to incidents, troubleshoot issues, and restore service.
Why it matters: A low MTTR indicates that your team can quickly diagnose and fix problems, minimizing downtime and reducing the impact on users. It reflects the effectiveness of your incident response and recovery processes.
Benchmarks:
High: Incidents are resolved within one day. Indicates a fast, effective response process, ensuring minimal downtime and disruption to users.
Medium: Incidents are resolved between one day and one week. Reflects a moderate recovery speed, balancing quick fixes with more complex issues, though there may be opportunities to optimize processes.
Low: Incidents take between one week and one month to resolve. Suggests delays in incident response or troubleshooting, which can impact user experience and system reliability.
While each DORA metric is valuable on its own, they are most powerful when used together. Here's how they relate to one another:
Deployment Frequency and Lead Time for Changes reflect how quickly your team can deliver new features or fixes.
Change Failure Rate and Mean Time to Recovery (MTTR) measure how reliable your releases are and how effectively your team can recover from incidents.
By analyzing these metrics together, you can identify both the strengths and weaknesses of your DevOps process and prioritize improvements accordingly.
To start measuring your team’s DevOps performance using the Dora Dashboard, you’ll first need to connect your GitHub account to Scoutflo. This integration allows Scoutflo to pull in your repositories and generate valuable insights based on DORA metrics. Follow these steps to get set up:
Log in to Scoutflo
Visit Deploy.scoutflo.com and log in to your Scoutflo account.
Navigate to GitOps Settings
Once logged in, go to:
Account Settings > GitOps, or
Get Started > Step 1: Connect your Git.
Connect Git App
Click on the “+ Connect Git App” button to start the integration process.
Sign in to GitHub
You will be redirected to the GitHub sign-in page. If you have multiple GitHub accounts, select the one where you want to install the “Scoutflo GitHub App.”
Select Repositories
Choose the repositories you want Scoutflo to track:
You can select “All Repositories” (recommended for a comprehensive view) or select specific repositories.
After making your selection, click Install.
Successful Integration
You’ll be redirected back to the Scoutflo platform, where a message will confirm that your GitHub account has been successfully integrated.
Access the Dora Dashboard
After integration, Scoutflo will begin pulling data from your GitHub repositories. This can take up to 15 minutes.
To view your DORA metrics, go to the sidebar and select:
Dashboard > Dora Dashboard under the ‘Workspace’ dropdown.
Now that your GitHub integration is set up, you can start exploring the DORA metrics from your repositories.
Select Repositories At the top left corner of the Dora Dashboard, you’ll find a dropdown menu where you can select specific repositories from your organization’s GitHub account. By default, All Repositories are selected.
Demo Mode Scoutflo provides a Demo Mode for users who haven’t connected their GitHub account yet. Demo Mode allows you to see a preview of the Dora Dashboard and how it works.
Once you’ve connected your GitHub, you can disable Demo Mode using the toggle at the top left corner and switch to your actual GitHub data.
You can analyze your data over different time periods:
Predefined Time Windows You can view your DORA metrics for the last 7 days, 3 weeks, or 3 months.
Custom Date Range For a more specific analysis, use the calendar tool to select any custom date range and view metrics for that time interval.
