DevOps
  • Introduction
    • About DevOps
    • Software Production
    • Software System
  • Terminal Programming
    • BASH - Basics Commands
    • BASH -Conditions and Loops
    • Some Examples
  • SOFTWARE TEAMS
    • Software Teams
      • Software Team Topologies
      • Effort-Cost Estimation
      • Technical Debt
      • Software Development Waste
    • Software Production Methods
      • SCRUM
      • KANBAN
      • WATER FALL
      • AGILE
    • Version Control
    • CAMS
  • CI/CD
    • Continuous Integration & Continuous Delivery
  • Cloud Platforms
  • Automation Strategies
  • PaaS - Containers
    • Docker
  • PaaS - Orchestration
    • Kubernetes
  • DevOps & DORA Metrics
  • Monitoring Tools
  • A Day in a DevOps
  • MLOps
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On this page
  • DORA Metrics Overview
  • Velocity Metrics
  • Stability Metrics
  • Example Computation
  • Data
  • Computation
  • Interpretation

DevOps & DORA Metrics

DORA Metrics Overview

DORA metrics are a set of key performance indicators used to evaluate the efficiency and reliability of software delivery processes in DevOps. They are divided into two main categories: velocity metrics and stability metrics.

Velocity Metrics

  • Deployment Frequency (DF): Measures how often code is deployed to production.

  • Lead Time for Changes (LT): Tracks the time from code commit to deployment in production.

Stability Metrics

  • Change Failure Rate (CFR): Calculates the percentage of deployments that result in failures.

  • Mean Time to Recover (MTTR): Measures the time it takes to restore service after a failure.

Recently, a fifth metric, reliability, has been introduced to assess operational performance.

Example Computation

Let's consider an example of computing these metrics for a fictional company.

Data

  • Deployment Frequency (DF): 10 deployments per week.

  • Lead Time for Changes (LT): Average of 2 days from commit to production.

  • Change Failure Rate (CFR): 2 out of 10 deployments failed.

  • Mean Time to Recover (MTTR): Average recovery time is 30 minutes.

Computation

  • Deployment Frequency: Already given as 10 deployments per week.

  • Lead Time for Changes: 2 days.

  • Change Failure Rate: 210×100=20%102×100=20%.

  • Mean Time to Recover: 30 minutes.

Interpretation

  • Deployment Frequency: High frequency indicates efficient development processes.

  • Lead Time for Changes: Short lead time suggests streamlined development pipelines.

  • Change Failure Rate: A 20% failure rate indicates room for improvement in testing or deployment processes.

  • Mean Time to Recover: Quick recovery time shows resilience in handling failures.

These metrics help teams identify areas for improvement and optimize their software delivery processes.

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Last updated 12 days ago