DORA Metrics Scorecard Example

DORA Metrics Overview

The DORA (DevOps Research and Assessment) metrics are a set of key performance indicators used to measure the efficiency and effectiveness of your engineering team’s delivery capabilities. These metrics help teams track their ability to deliver software quickly, with high quality, and to recover from issues swiftly. By implementing DORA metrics, organizations can reduce downtime, improve deployment speeds, and gain visibility into the software development lifecycle.

DORA metrics specifically focus on four main areas:

1. Deployment Frequency - How often your organization deploys changes.

2. Lead Time for Changes - The time it takes from code commit to release.

3. Mean Time to Recover (MTTR) - The average time it takes to recover from a failure.

4. Change Failure Rate - The percentage of deployments causing issues.

Each tier in the DORA metrics scorecard aligns with levels of performance for these metrics, helping your organization target best practices for continuous delivery.

Key Elements to Track for DORA Performance

Each performance level in the DORA framework corresponds to market benchmarks identified by the DORA team in their 2021 Accelerate State of DevOps report, representing the different levels of performance and their alignment with industry benchmarks: elite, high and medium performers.

🏅 Gold Tier - Elite Performers

• Deployment Frequency -> More than 20 deployments per month (multiple times per day).

• Lead Time for Changes -> Less than 24 hours to move changes from commit to production.

• Mean Time to Recover -> Incident resolution time averages less than one hour.

• Change Failure Rate -> Less than 5% of changes result in downtime or service degradation.

• Failed Deployment Recovery Time -> Time to recover from a failed deployment averages less than one hour.

🥈 Silver Tier - High Performers

• Deployment Frequency -> At least five deployments per month (around once a week).

• Lead Time for Changes -> Between one day and one week to move changes from commit to production.

• Mean Time to Recover -> Average resolution time of less than 24 hours.

• Change Failure Rate -> Less than 15% of changes lead to downtime or service degradation.

• Failed Deployment Recovery Time -> Recovery time from failed deployments averages less than one day.

🥉 Bronze Tier - Medium Performers

• Deployment Frequency -> At least one deployment per month.

• Lead Time for Changes -> Between one week and one month to move changes from commit to production.

• Mean Time to Recover -> Average resolution time of less than one week.

• Change Failure Rate -> Less than 30% of changes lead to downtime or service degradation.

• Failed Deployment Recovery Time -> Recovery time from failed deployments averages less than one week.

Example DORA metrics scorecard code definition

Example DORA metrics scorecard code definition

{
  "id": "team-dora-metrics-scorecard",
  "title": "Team DORA Metrics Benchmarks",
  "description": "DORA metrics remain the most asked about framework for measuring developer productivity. This scorecard is provided by Rely.io to help you assess how your team is faring against the benchmarks of 100s of other companies. After analyzing survey data from 31,000 software professionals worldwide collected over a period of six years, the DORA team identified four key metrics to help DevOps and engineering leaders better measure software delivery efficiency: Deployment frequency, Lead time for changes, Mean time to recovery (now Failed Deployment Recovery Time), Change failure rate.",
  "isActive": true,
  "blueprintId": "team",
  "ranks": [
    {
      "id": "bronze",
      "rules": [
        {
          "id": "deployment-frequency-medium-performers",
          "title": "At least one deployment this month?",
          "description": "Validates whether there has been at least one deployment in this service since the start of the month.",
          "conditions": [
            {
              "field": "data.calculationProperties.deploymentCountProd.1m.value",
              "operator": "gte",
              "value": 1
            }
          ]
        },
        {
          "id": "lead-time-for-change-medium-performers",
          "title": "Lead time for changes in prod is less than 1 month since the start of the month",
          "description": "Lead Time for Changes (LTC) is the amount of time between a commit and production. LTC indicates how agile your team is—it not only tells you how long it takes to implement changes, but how responsive your team is to the ever-evolving needs of end users.",
          "conditions": [
            {
              "field": "data.calculationProperties.leadTimeForChangesProd.1m.value",
              "operator": "lt",
              "value": 720
            }
          ]
        },
        {
          "id": "mean-time-to-resolve-medium-performers",
          "title": "Mean time to resolve is less than 1 week since the start of the month",
          "description": "Average time to resolve incidents that have been closed in the past 24 hours for a specific service, including unresolved incidents since their start.",
          "conditions": [
            {
              "field": "data.calculationProperties.meanTimeToResolve.1m.value",
              "operator": "lt",
              "value": 168
            }
          ]
        },
        {
          "id": "change-failure-rate-medium-performers",
          "title": "Change failure rate is less than 30% since the start of the month",
          "description": "Change Failure Rate (CFR) is the percentage of releases that result in downtime, degraded service, or rollbacks, which can tell you how effective your team is at implementing changes. This metric is also critical for business planning as repeated failure and fix cycles will delay launch of new product initiatives.",
          "conditions": [
            {
              "field": "data.calculationProperties.changeFailureRate.1m.value",
              "operator": "lt",
              "value": 30
            }
          ]
        },
        {
          "id": "failed-deployment-recovery-time-medium-performers",
          "title": "Failed deployment recovery time is less than 1 week since the start of the month",
          "description": "FDRT is the amount of time it takes your team to restore service when there’s a service disruption as a result of a failed deployment, like an outage. This metric offers a look into the stability of your software, as well as the agility of your team in the face of a challenge.",
          "conditions": [
            {
              "field": "data.calculationProperties.failedDeploymentRecoveryTime.1m.value",
              "operator": "lt",
              "value": 168
            }
          ]
        }
      ]
    },
    {
      "id": "silver",
      "rules": [
        {
          "id": "deployment-frequency-high-performers",
          "title": "Deployed at least 5 times to production since the start of the month",
          "description": "Deployment Frequency (DF) is how often you ship changes, how consistent your software delivery is. This enables your organization to better forecast delivery timelines for new features or enhancements to end user favorites.",
          "conditions": [
            {
              "field": "data.calculationProperties.deploymentCountProd.1m.value",
              "operator": "gte",
              "value": 5
            }
          ]
        },
        {
          "id": "lead-time-for-change-high-performers",
          "title": "Lead time for changes in prod is less than 1 week since the start of the month",
          "description": "Lead Time for Changes (LTC) is the amount of time between a commit and production. LTC indicates how agile your team is—it not only tells you how long it takes to implement changes, but how responsive your team is to the ever-evolving needs of end users.",
          "conditions": [
            {
              "field": "data.calculationProperties.leadTimeForChangesProd.1m.value",
              "operator": "lt",
              "value": 168
            }
          ]
        },
        {
          "id": "mean-time-to-resolve-high-performers",
          "title": "Mean time to resolve is less than 24 hours since the start of the month",
          "description": "Average time to resolve incidents that have been closed in the past 24 hours for a specific service, including unresolved incidents since their start.",
          "conditions": [
            {
              "field": "data.calculationProperties.meanTimeToResolve.1m.value",
              "operator": "lt",
              "value": 24
            }
          ]
        },
        {
          "id": "change-failure-rate-high-performers",
          "title": "Change failure rate is less than 15% since the start of the month",
          "description": "Change Failure Rate (CFR) is the percentage of releases that result in downtime, degraded service, or rollbacks, which can tell you how effective your team is at implementing changes. This metric is also critical for business planning as repeated failure and fix cycles will delay launch of new product initiatives.",
          "conditions": [
            {
              "field": "data.calculationProperties.changeFailureRate.1m.value",
              "operator": "lt",
              "value": 15
            }
          ]
        },
        {
          "id": "failed-deployment-recovery-time-high-performers",
          "title": "Failed deployment recovery time is less than 1 day since the start of the month",
          "description": "FDRT is the amount of time it takes your team to restore service when there’s a service disruption as a result of a failed deployment, like an outage. This metric offers a look into the stability of your software, as well as the agility of your team in the face of a challenge.",
          "conditions": [
            {
              "field": "data.calculationProperties.failedDeploymentRecoveryTime.1m.value",
              "operator": "lt",
              "value": 24
            }
          ]
        }
      ]
    },
    {
      "id": "gold",
      "rules": [
        {
          "id": "deployment-frequency-elite-performers",
          "title": "Deployed at least 30 times to production since the start of the month",
          "description": "Deployment Frequency (DF) is how often you ship changes, how consistent your software delivery is. This enables your organization to better forecast delivery timelines for new features or enhancements to end user favorites.",
          "conditions": [
            {
              "field": "data.calculationProperties.deploymentCountProd.1m.value",
              "operator": "gt",
              "value": 30
            }
          ]
        },
        {
          "id": "lead-time-for-change-elite-performers",
          "title": "Lead time for changes in prod is less than 24 hours since the start of the month",
          "description": "Lead Time for Changes (LTC) is the amount of time between a commit and production. LTC indicates how agile your team is—it not only tells you how long it takes to implement changes, but how responsive your team is to the ever-evolving needs of end users.",
          "conditions": [
            {
              "field": "data.calculationProperties.leadTimeForChangesProd.1m.value",
              "operator": "lt",
              "value": 24
            }
          ]
        },
        {
          "id": "mean-time-to-resolve-elite-performers",
          "title": "Mean time to resolve is less than 1 hours since the start of the month",
          "description": "Average time to resolve incidents that have been closed in the past 24 hours for a specific service, including unresolved incidents since their start.",
          "conditions": [
            {
              "field": "data.calculationProperties.meanTimeToResolve.1m.value",
              "operator": "lt",
              "value": 1
            }
          ]
        },
        {
          "id": "change-failure-rate-elite-performers",
          "title": "Change failure rate is less than 5% since the start of the month",
          "description": "Change Failure Rate (CFR) is the percentage of releases that result in downtime, degraded service, or rollbacks, which can tell you how effective your team is at implementing changes. This metric is also critical for business planning as repeated failure and fix cycles will delay launch of new product initiatives.",
          "conditions": [
            {
              "field": "data.calculationProperties.changeFailureRate.1m.value",
              "operator": "lt",
              "value": 5
            }
          ]
        },
        {
          "id": "failed-deployment-recovery-time-elite-performers",
          "title": "Failed deployment recovery time is less than 1 hour since the start of the month",
          "description": "FDRT is the amount of time it takes your team to restore service when there’s a service disruption as a result of a failed deployment, like an outage. This metric offers a look into the stability of your software, as well as the agility of your team in the face of a challenge.",
          "conditions": [
            {
              "field": "data.calculationProperties.failedDeploymentRecoveryTime.1m.value",
              "operator": "lt",
              "value": 1
            }
          ]
        }
      ]
    }
  ],
  "medianRank": "noRank"
}