Back to blog

DORA Metrics: Transforming Your DevOps Team into High Performers


11 min read

Many companies have successfully implemented DevOps practices in their software development cycle. DashDevs is no exception. Thanks to DevOps, we conduct an efficient development process and ensure the software works smoothly in production.

DevOps eliminates such cases as “it works locally for me, and I don’t know why you cannot launch it in production.” This is because the operations and development staff work closely at all stages of the SDLC and address any issues promptly.

Undoubtedly, DevOps is a powerful tool for effective releases, reduced time to market, and cost-effective development. However, the mere fact of having DevOps does not mean that your “development-production” cycle works like clockwork.

So, how to measure the effectiveness of a DevOps team? DORA metrics can help.

What Is DORA? What Are DORA Metrics?

DORA acronym stands for DevOps Research and Assessment. This is a Google program aimed at improving organizational performance of software development and delivery.

DORA metrics are KPIs used to measure the performance of DevOps teams.

Initially, there were four key metrics of Google DORA:

  1. Deployment frequency (DF) - how often new releases come into production
  2. Lead time for changes (LTC) - the time between code commit and code running in production
  3. Change failure rate (CFR) - the percentage of changes that result in a failure in production
  4. Time to restore service (TTS) - time to recover from a failure in production.

Later, in 2021, Google introduced the fifth DORA metric called Reliability (R).

  1. Reliability (R)  - the ability of the DevOps team to meet expectations about the effectiveness of SDLC.

Note that reliability is a qualitative indicator rather than a quantitative one. It shows the team’s ability to meet expectations regarding the organization of the DevOps process on the project. Google does not provide a formula for calculating this indicator, so we will not dwell on it in detail.

DORA metrics

How DORA Metrics Measure DevOps Success

DORA metrics provide you with an opportunity to measure the efficiency of your DevOps cycle in quantitative terms. With these metrics, you can get a big picture of how well your development, deployment, and release processes are set up and identify areas for improvement.

The table below presents the quantitative indicators of the DORA metrics Google and their association with the performance level of the engineering teams.

Performance levelDeployment frequencyLead time for changesChange failure rateTime to restore service
EliteOn demandLess than 1 day5%Less than 1 hour
HighFrom once a day to once a weekFrom 1 day to 1 week10%Less than 1 day
MediumFrom once a week to once a monthFrom 1 week to 1 month15%From 1 day and 1 week
LowFrom once a week to once a monthFrom 1 week to 1 month64%From 1 month to 6 months

Why Is It Important To Strive For Elite Performance?

Why do DORA metrics DevOps matter? How is one release per day worse than two releases per day? What will happen if you do not immediately commit code changes? Let’s find out.

Higher deployment frequency - better market adaptability

Frequent deployments indicate a mature, agile process where the team can deliver updates and new features rapidly. This helps in responding to customer needs and market changes more effectively.

Ideally, you should have so many automated tests that they can fully cover your particular feature check. This will help you promptly release every build that passes the automated test check.

In practice, the situation is often different. Before the release, the software requires manual testing, which can take several days. This means that you will not be able to release the update earlier than these several days.

Delays in releases can lead to 

  • unhappy customers
  • lost business opportunities
  • damaged сompany reputation

If you aim to provide excellent user experience and adapt quickly to market demands, you should be ready to do on-demand deployment. Ability to make many deployments per day qualifies to elite DORA deployment frequency metric. This ensures that your software processes are highly agile and that you can evolve along with a changing market.

Shorter lead time for changes - faster response to customer needs

Short lead times reflect efficient workflows and a streamlined process from development to deployment. This enables faster iteration, quicker feedback loops, and more responsive development practices.

Imagine that your team is developing a product feature, for example, an intuitive dashboard in your admin panel. The feature development cycle looks as follows: a developer takes it into a sprint, implements it, and opens a merge request. After the feature is tested, it lands in master.

The time from code commit to master to code release to production is the lead time for changes. If it is too long you risk 

  • increasing conflicts and errors in the code
  • stretching time-to-market
  • facing customer dissatisfaction

According to DORA metrics definition, elite teams spend no more than one day to release committed changes into production. Thanks to this speed, it can quickly receive feedback from real customers and make changes in time if needed.

Lower change failure rate - better software reliability

A lower change failure rate indicates higher quality code and more effective testing processes. This metric highlights the reliability of the deployment process and the effectiveness of the team in maintaining production stability.

Any project may experience errors after release for various reasons. For example, the integration environment may differ from the production environment, or the team may not have accounted for certain edge cases.

The percentage of deployments that lead to problems in production is the change failure rate. A high change failure rate indicates:

  • insufficient testing before release
  • weak automation of software check processes
  • incomplete code coverage with tests

In an ideal world, the change failure rate should be 0%. In a near-ideal world, it should be no more than 5%. By maintaining your LCF between 0 and 5% you achieve elite status according to DORA DevOps metrics.

A low change failure rate helps you maintain high customer satisfaction and a reputation as a reliable company.

Faster time to restore service - stronger company reputation

Quick recovery times demonstrate robust incident response and recovery procedures. This ensures minimal disruption to users and maintains service reliability, which is crucial for customer trust and satisfaction.

There is always a chance that an outage will happen. The code may fail, the infrastructure may fail, or the data center may be flooded or damaged.

Recovery time shows how long it takes to recover from an error in production.

If it is too long, it leads to:

  • loss of revenue
  • lost customer trust
  • increased operating costs

Elite DevOps teams restore services within one hour. Such speed allows them to minimize the harmful effects of the error and provide the most comfortable user experience to customers.

Do you want to build an elite DevOps team?
DashDevs provides professional Cloud and DevOps services

How to Track and Improve DORA Metrics?

DORA metrics help you track the real state of your DevOps processes and take actionable steps to improve them.

But how exactly do you track DevOps DORA metrics and what DevOps tools should you use for this?

Actually, there is no universal recipe here. Processes should be configured taking into account the specifics of the project.

At DashDevs, we have extensive experience in launching projects from scratch and optimizing existing processes. Given our extensive experience in implementing the best DevOps practices, I provide recommendations on how to track DORA DevOps metrics and how to improve the obtained results.

Tracking and improving DF

Measure how often your team successfully deploys to production. Use CI/CD tools like Jenkins, GitLab CI/CD, and CircleCI. These tools can help you log each deployment event. Thus, you can have a clear history of your deployment activities. 

Visualize data with dashboards. Use tools like Grafana or DataDog to monitor trends and identify irregularities. Visual representation will help you see the big picture of your DevOps processes and facilitate informed decision making.

Deployment DORA metric

Automate your CI/CD pipeline. Encourage small, incremental changes rather than large, infrequent updates. This incremental approach will lower the complexity and risks of deployments. You should also regularly review and refine your deployment process to eliminate bottlenecks. 

Tracking and improving LTC

Measure the time from code commit to code successfully running in production. You can do this by integrating your version control system, e.g., Git, with a CI/CD tool, e.g., Jenkins. These tools automatically capture timestamps for each commit, build, test, and deployment event, so you can easily track the LTC metric.

Analyze timestamps and generate reports. You can use tools like New Relic or Splunk for timestamps analysis. You can also use tools like Grafana or Kibana to visualize obtained data on dashboards.

Shorten lead time for changes. You can do this by automating testing, parallelising processes, frequently merging code changes into a shared repository, and setting clear code review guidelines.

Tracking and improving CFR

Monitor the percentage of deployments that lead to failures in production. Utilize such tools as Jira or GitHub to log incidents and correlate them with deployment events. Integrate these tools with your CI/CD pipeline to automatically track and analyze deployment outcomes. Use Grafana or DataDog to visualize these metrics.

Reduce percentage of failed deployments. Implement automated testing, including unit, integration, and end-to-end tests. Encourage peer code to catch potential issues early. Use canary deployments and blue-green deployments to minimize risk by gradually rolling out changes.

Tracking and improving TTS

Measure the duration from the moment a production issue is detected to the time it is resolved. Use incident management tools to log incidents and response times. I can recommend PagerDuty or Opsgenie for these purposes. You can integrate them with your monitoring systems to automatically capture incident data and identify time needed to restore. 

Take measures to shorten TTS. Develop a robust incident response plan. Clearly define the roles of personnel and their responsibilities when an incident occurs. Additionally, create automatic rollback so that you can revert to the last known stable state in case of a failure.

How to Build Elite DevOps Team

According to DORA DevOps standards, elite DevOps teams deploy code frequently, make changes quickly, rarely experience failures, and if they do, restore services immediately.

How to build such a team? Where to start the DevOps process setup?

With 13+ years of experience in delivering cloud and DevOps services to clients across domains, we at Dash Devs have developed a clear roadmap for setting up an effective DevOps pipeline. Here are the steps to take:

1.Set goals and objectives

Goals are the global result you should reach after setting up the DevOps process. Objectives are the intermediate milestones you should achieve to ensure the final result.

For example, your goal may be to reduce customer churn by 10%. To do this, you need to achieve such objectives as improving performance and minimizing downtime. You can improve performance by increasing DF by 20% and reducing LTC by 30%. Additionally, you can minimize downtime by reducing TTS by 40% and decreasing CFR to less than 5%.

2. Measure current performance

Before you can improve, you need to understand where you stand. Determine the efficiency of your current DevOps processes by answering the questions:

  • How often do you release?
  • How long does it take to push changes to production?
  • How often do you have failures?
  • How long does it take to restore services?

To measure the current performance, use modern DevOps tools. Document the data obtained and identify areas that you want to improve

3. Set up Continuous Integration and Continuous Delivery (CI/CD)

CI/CD is the foundation of an elite DevOps cycle. 

By setting up continuous integration, you can make changes to the code with frequent commits.

With continuous delivery, you automate the deployment of an application in various environments: development, stage, production.

CI/CD requires continuous testing. It is implemented as a set of various automated tests, including regression, performance, and others, that are executed in the CI/CD pipeline.

Mature CI/CD practices allow you to automate build deployment to the production environment. Teams practicing continuous delivery can afford daily or even hourly deployments and qualify for elite DORA software metrics.

4.Integrate security in your SDLC

The most common mistake development teams make is introducing security measures at the last stages of development. This practice leads to the release of vulnerable products, which at any time can experience glitches and data leakage.

Elite DevOps DORA processes require close cooperation between development and operations teams and security specialists from the very beginning of the development cycle.

Creating a secure SDLC and DevOps involves:

  • Setting up secure IT infrastructure
  • Developing secure application architecture
  • Using code reviews
  • Implementing autotests
  • Integrating tools for static and dynamic code analysis 
  • Using the least privilege principle when setting up data access roles

5. Create a motivating work culture

The key resource for building an exceptional DevOps team is its people. No tools, KPIs, or processes can ensure success without professionals who appreciate teamwork and established processes.

DevOps is highly cooperative and cannot be successful with just one or two DevOps engineers. The entire team, from managers to developers to testers, must actively participate in the DevOps process.

Consider a scenario where testers are unable or unwilling to implement automated testing, or operations refuse to use modern IaC tools and instead rely solely on manual setup. Even with significant effort from the DevOps engineer, the CI/CD process will not function effectively. Only when the entire team works together and understands the what and why of their tasks, can an effective DevOps process be established. In this unified effort, each team member must clearly comprehend their role and contribution to the overall outcome and see tangible results from their actions.

Interested in setting up DevOps according to the DORA framework?
DashDevs experts can help

DevOps Transformation: How DashDevs Helped a Client Achieve DORA Metrics Elite Status

Our client, a large financial services company, was facing significant challenges in the software development and delivery process. A big part of their processes was performed manually. Updates could take days or weeks. The client approached us to modernize the DevOps processes.

Initial state

  • Development: The application was built on a monolithic architecture using Java and an Apache Tomcat application server.
  • Deployment: Deployment was performed manually via FTP and SSH.
  • Testing: Testing was performed manually. Automation tests were not in place.
  • Monitoring: Almost non-existent.

Main challenges

  • Lack of automation
  • Insufficient testing
  • Long recovery times - up to several hours
  • Rare deployment - on average, once a month

DashDevs actions

We started with conducting an audit of the client’s DevOps processes. Then, we developed a transformation plan that included the following steps:

CI/CD setup

  • Configured Jenkins to automate builds and testing
  • Integrated GitLab CI/CD to manage the continuous integration and delivery process

Test automation

  • Created test environments that fully imitated the production environment
  • Introduced automation testing using Selenium and JUnit

Monitoring setup

  • Implemented monitoring and logging systems using Grafana and Prometheus
  • Set up alerts via PagerDuty

Deployment process improvement

  • Developed automatic rollback
  • Implemented frequent and small deployments

Results achieved

Six months after the launch, the client achieved impressive results:

  • Increased deployment frequency from 1 time per month to 5 times per week
  • Decreased DORA lead time for changes from 6 hours to 30 minutes,
  • Decreased change failure rate from 20% to 3%, which indicates high quality and reliability of the deployed code.
  • Decreased time to restore service from several weeks to 1 day

Transforming the client’s DevOps culture not only increased the quality of their product, but also significantly improved end-user satisfaction. This ultimately positively impacted client business as a whole.

Do you want to create an effective DevOps process that will contribute to developing a reliable and flexible software product? Let us help you along the way.

Share article

Table of contents
What are the benefits of DORA metrics?
The benefits of DORA metrics include providing objective measurements of DevOps performance, enabling teams to identify areas for improvement in deployment frequency, lead time, change failure rate, and time to restore service. These metrics help organizations achieve faster, more reliable software delivery and enhance overall operational efficiency.
What is the 5th Dora metric?
The 5th DORA metric is reliability. It shows the ability of the DevOps team to meet expectations about the effective SDLC. Reliability is a qualitative indicator. Google does not provide a formula for calculating it.
What are the 4 door metrics?
The 4 DORA metrics are deployment frequency (DF), lead time for changes (LTC), change failure rate (CFR), and time to restore service (TTS).
What does DORA metrics stand for?
Google DORA stands for DevOps Research and Assessment. It refers to a set of metrics designed to measure and improve the performance of DevOps teams in software delivery and operations.
What are DORA metrics?
DORA metrics are key performance indicators used to measure the effectiveness of DevOps teams, focusing on deployment frequency, lead time for changes, change failure rate, and time to restore service. These metrics help organizations assess and improve their software delivery performance.