Hello. If the Platform Maturity Model I previously organized shows ‘how prepared an organization is,’ then DORA Metrics are a powerful tool to prove ‘what performance that platform is actually achieving.’ I will detail this in a blog post format.
Today, we will delve deeply into DORA Metrics, which are essential to know when you want to numerically prove the value of a platform in the cloud-native ecosystem. π
π― What are DORA Metrics?
DORA (DevOps Research and Assessment) is a Google Cloud research team that, over 6 years, surveyed more than 30,000 global experts to identify the four “key indicators that define high-performing organizations.” The core idea is not simply “working hard,” but measuring “how efficiently and stably value is delivered.”
1οΈβ£ Two Metrics for Measuring Velocity ποΈ
High-performing organizations deliver features to users faster and more frequently.
- Deployment Frequency
- Definition: How often an organization successfully releases code to production.
- Goal: As platform maturity increases, it should evolve from ‘weekly’ to ‘daily’ and further to ‘on-demand’ deployments.
- Meaning: High deployment frequency means smaller batch sizes, which implies a narrower impact scope and easier fixes in case of failure.
- Lead Time for Changes
- Definition: The time it takes from code commit to deployment in production.
- Goal: This time should be shortened by minimizing manual intervention through automated testing and CI/CD pipelines.
- Meaning: Represents the speed at which ideas are transformed into actual value (business outcomes).
2οΈβ£ Two Metrics for Measuring Stability π‘οΈ
Being fast alone is not enough. Systems must be stable.
- Time to Restore Service
- Definition: The time it takes to resolve an incident in a production environment and restore normal service.
- Goal: Minimize the time from incident detection to resolution through observability tools and automated recovery processes.
- Meaning: Failures are inevitable, but high-performing teams prove their capability by how quickly they recover from them.
- Change Failure Rate
- Definition: The percentage of deployments that resulted in a failure, rollback, or hotfix.
- Goal: Increase deployment success rates by applying standardized platform templates and ‘Secure by Default’ policies.
- Meaning: A checkpoint that shows whether speed is being increased without compromising quality.
π Organizational Levels as Seen Through DORA Metrics
According to DORA research, organizations are categorized into four levels based on performance: Elite, High, Medium, Low.
| Metric | Elite Group | Low Group |
| — | — | — |
| Deployment Frequency | On-demand (multiple times a day) | Once a month ~ Once every 6 months |
| Lead Time for Changes | Less than 1 hour | 1 month ~ 6 months |
| Time to Restore Service | Less than 1 hour | 1 week ~ More than 1 month |
| Change Failure Rate | 0-15% | 46-60% |
—
π‘ Connection to Platform Engineering
Each stage of the Maturity Model you just studied is directly linked to DORA metric improvement.
- L1-L2 Stages: Manual tasks are numerous, leading to long lead times and high failure rates.
- L3-L4 Stages: With self-service and automation in place, lead times are dramatically reduced, and change failure rates decrease due to standardized environments.
β οΈ Caution: Goodhart’s Law
As mentioned in the Maturity Model document, don’t forget: “When a measure becomes a target, it ceases to be a good measure.” For example, repeatedly making small, meaningless deployments just to inflate the deployment frequency number does not help the business. Metrics should be interpreted alongside qualitative user feedback to provide true insights.
π Conclusion
DORA Metrics are a common language that proves what tangible value our platform team is providing to the organization. In the CNPA exam you are preparing for, connecting these metrics as a means of ‘performance measurement’ for the platform will be a key question.
I hope the content organized today will be of great help to your technical growth and certification acquisition! π
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