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Measure DevOps performance with a small set of delivery and reliability signals, then use them to improve the whole service—not to rank individuals. DORA’s 2021 framing groups four delivery measures around throughput and stability, and adds reliability as operational performance. The practical aim is to make delivery visible while keeping developers and operators jointly accountable for user-facing outcomes.
How do I measure DevOps performance?
Start with the outcome your users need, then connect it to the delivery system that produces and operates the software. DORA’s 2021 report presents delivery performance through throughput and stability measures, with reliability as a separate operational performance measure. It defines reliability as a team’s ability to keep promises and assertions about the software it operates.
The measures are useful signals, not a universal scorecard. Before comparing teams or periods, agree on the service boundary, what counts as a user-facing outcome, and how the organization records events. The source material does not prescribe universal formulas or reporting intervals; document local definitions and keep them consistent when interpreting trends.
Throughput: how quickly and often changes reach production
- Lead time for changes: the time from a change being committed to its release into production.
- Deployment frequency: how frequently the team deploys changes.
Read these together. A change that reaches production quickly is not automatically valuable if it creates instability or fails to improve the service.
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Stability: what happens when changes meet production
- Time to restore service: how long it takes to restore service after an incident.
- Change failure rate: how often changes cause failures or require corrective action, using the team’s clearly documented event definition.
These measures help teams see the operational consequences of delivery. Their usefulness depends on consistent boundaries and definitions; do not treat one locally chosen calculation as a universal DORA formula.
Operational performance: reliability against promises
The 2021 report identifies reliability as the primary measure of operational performance: whether a team meets or exceeds reliability targets for the software it operates. Unlike a delivery count, reliability makes the user-facing commitment explicit. Google Cloud’s 2021 DORA report describes this measure alongside the delivery metrics.
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Which DORA metrics should our team track?
For the 2021 report’s framework, track the four delivery measures and reliability together. The table summarizes what each signal helps answer; it is not a prescription for a particular formula, instrument, or review cadence.
| Measure | What it helps you understand | Framing in the 2021 report |
|---|---|---|
| Lead time for changes | How long a change takes to move from commit to production release | Throughput |
| Deployment frequency | How often the team deploys changes | Throughput |
| Time to restore service | How long service recovery takes after an incident | Stability |
| Change failure rate | How frequently changes result in failure, according to a defined local event boundary | Stability |
| Reliability | Whether the team meets or exceeds user-facing reliability targets | Operational performance |
Pick measures that illuminate a decision rather than collecting numbers for their own sake. For example, a team might examine a reliability shortfall alongside deployment and restoration trends to decide whether to invest in safer rollout practices, incident response, or reliability work earlier in delivery. Define the relevant event boundaries and reporting interval locally, write them down, and avoid changing them silently when comparing results.
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The framework is not a complete picture of organizational performance. Google Cloud’s 2024 DORA report announcement says DORA examines how delivery measures intersect with individual, workflow, team, and product performance. That wider view matters: a team’s delivery signals should be interpreted in the context of its workflow and the product and system outcomes they support.
How do we make teams accountable for reliability?
Accountability works best when it is attached to a service and a clear user-facing commitment. Teams need authority and practical ways to act on reliability, not just responsibility for a number they cannot influence. The 2021 report identifies several operational practices that support that approach.
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Set reliability targets users can understand
Define reliability in terms of the service users experience, then use service-level indicators (SLIs) to measure that experience and service-level objectives (SLOs) to express the target. The report describes using SLI/SLO measures and error budgets to prioritize work. An error budget makes the gap between observed service performance and the reliability target visible, helping teams weigh delivery work against reliability improvements.
Make developers and operators jointly responsible
Give developers and operators shared authority to contribute to the reliability of the software they build and run. The report says this shared-responsibility model predicts better reliability outcomes. In practice, clarify who owns the service outcome, how reliability targets are reviewed, and how delivery decisions affect the operated service. Do not turn a team-level signal into an individual performance rating: doing so can encourage people to protect their own numbers instead of improving the system.
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Build reliability into normal delivery and operations
- Automate repetitive manual work and reduce disruptive alerts so operators can focus on meaningful service risks.
- Define incident-response protocols so people know how to coordinate when service is affected.
- Run preparedness drills to practice the response before an incident occurs.
- Include reliability throughout the delivery lifecycle, rather than leaving it solely to an operations handoff after release.
The 2021 study reported data from more than 32,000 professionals worldwide. It found that organizations excelling in modern operational practices were 1.4 times more likely to report greater software delivery and operational performance, and 1.8 times more likely to report better business outcomes. These are associations reported by that study, not guarantees that a specific practice will cause the same result for every organization. The report also said 52% of respondents used SRE practices to some extent, with adoption depth varying.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can we use metrics without encouraging teams to optimize locally?
Use metrics to locate friction and prompt a shared conversation, not to set isolated targets that reward one team at another’s expense. A faster deployment rate, for example, is not a success if it undermines reliability for users. Likewise, a team should not be penalized for surfacing incidents or making failures visible; visibility is necessary for learning and recovery.
- Keep the service boundary stable. Agree which service and user outcome the measures describe before comparing periods or teams.
- Review the signals as a set. Consider throughput, stability, and reliability together so that improvement in one area does not conceal a worsening user outcome elsewhere.
- Pair measurement with action. Use trends to choose improvement work—such as automation, incident readiness, or reliability changes—then assess whether the service outcome improves.
- Make interpretation collaborative. Include the developers and operators who can explain delivery and operational context and who are empowered to improve the service.
- Be transparent about local definitions. Record what events count, what service is in scope, and the reporting interval. Treat changes to those definitions as changes to the measurement, not as a directly comparable trend.
DORA’s broader framing reinforces this caution. Its 2024 announcement describes delivery measures as intersecting with individual, workflow, team, and product performance, rather than existing in isolation. Google Cloud’s DevOps overview likewise describes DevOps as an organizational and cultural movement oriented around delivery velocity, service reliability, and shared ownership. Its capabilities guidance names continuous delivery, continuous integration, code maintainability, and cloud infrastructure as areas for improvement—not a prescribed scorecard.
What has changed since the 2021 DORA framing?
The five-measure grouping described here is specifically the 2021 report’s framework. Google Cloud’s publications index lists State of DevOps reports through 2024 and the 2025 State of AI-assisted Software Development. The available sources establish that DORA’s work continued, but do not provide a complete 2025–2026 definition set for these measures. Check the relevant newer DORA publication before presenting the 2021 definitions as the latest framework.
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