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DORA: maturity of practices influencing delivery performance

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A self-assessment of delivery and operations maturity inspired by DORA. This template combines factual questions about key delivery metrics with questions about the practices that influence those outcomes; the technical foundations block should be interpreted separately from the DORA metrics themselves.

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Blocks
5
Questions
29
Answer types
Single choice Scale
What this preview shows
This is a read-only preview of the template structure. After copying it, you can edit the questions, adjust wording, and launch the survey for your own teams.

1. Deployment Frequency

Block weight: 1
6
1.1 How often does the team deploy changes to production?
Single choice 5
5. Several times a day
4. About once a day
3. Several times a week
2. Once a week
1. Once a month or less
1.2 The team deploys to production regularly and frequently.
Scale Scale: 1–5
1.3 Deployments are automated and require minimal manual effort.
Scale Scale: 1–5
1.4 The team can deploy on demand without depending on a fixed release schedule.
Scale Scale: 1–5
1.5 Changes are shipped to production in small, incremental batches rather than large releases.
Scale Scale: 1–5
1.6 The deployment pipeline is fast enough that it does not block daily delivery.
Scale Scale: 1–5

2. Lead Time for Changes

Block weight: 1
6
2.1 How much time does it usually take from merge or commit to production?
Single choice 5
5. Up to 1 hour
4. Within the same day
3. 1-3 days
2. Up to 1 week
1. More than 1 week
2.2 From the moment code is committed, it reaches production quickly.
Scale Scale: 1–5
2.3 The CI/CD pipeline runs automatically on every commit and completes in a reasonable time.
Scale Scale: 1–5
2.4 Code review and approval processes do not create significant bottlenecks.
Scale Scale: 1–5
2.5 The team uses trunk-based development or short-lived branches merged frequently.
Scale Scale: 1–5
2.6 Manual testing or approval gates before production are minimal and targeted.
Scale Scale: 1–5

3. Change Failure Rate

Block weight: 1
6
3.1 What percentage of production deployments usually leads to an incident, rollback, or urgent fix?
Single choice 5
5. Almost never or very rarely
4. Rarely, but it happens
3. Sometimes
2. Regularly
1. Frequently
3.2 Most deployments to production complete without causing incidents or requiring rollbacks.
Scale Scale: 1–5
3.3 Automated tests catch most defects before changes reach production.
Scale Scale: 1–5
3.4 The team has a clear and practiced rollback or forward-fix strategy.
Scale Scale: 1–5
3.5 Code and configuration changes go through structured review before every deployment.
Scale Scale: 1–5
3.6 Test coverage is sufficient to give the team confidence to deploy at any time.
Scale Scale: 1–5

4. Recovery After a Failed Change

Block weight: 1
6
4.1 How long does it usually take to recover after a failed change or deployment that required intervention?
Single choice 5
5. Up to 1 hour
4. Within the same working day
3. Up to 1 day
2. 1-3 days
1. More than 3 days
4.2 After a problematic change, the team detects the issue quickly and starts responding right away.
Scale Scale: 1–5
4.3 Monitoring and alerting are in place and provide early warning of post-deployment issues.
Scale Scale: 1–5
4.4 The team has documented runbooks or playbooks for common deployment-related incidents.
Scale Scale: 1–5
4.5 Postmortems for failed changes are conducted regularly and lead to concrete improvements.
Scale Scale: 1–5
4.6 On-call responsibilities are clearly defined and distributed without overloading individuals.
Scale Scale: 1–5

5. Technical Foundations and Capability Practices

Block weight: 1
5
5.1 All code and infrastructure configuration is stored in version control.
Scale Scale: 1–5
5.2 The team uses feature flags or similar techniques to decouple deployment from release.
Scale Scale: 1–5
5.3 All environments are consistent, and infrastructure is managed as code.
Scale Scale: 1–5
5.4 Database schema changes are automated and part of the deployment pipeline.
Scale Scale: 1–5
5.5 Security and compliance checks are built into the pipeline rather than handled manually.
Scale Scale: 1–5