Making sense of DORA Metrics: A Concise Outline

DORA Metrics

What do you think are DORA metrics?

DORA metrics assist engineers to take data-driven decisions to continually improve their practices and deliver software more quickly and ensure that it stays stable. Four metrics are:

  • Change Lead Time
  • Deployment Frequency
  • Change Failure Rate
  • Mean Time To Recovery (MTTR)

“You cannot improve what you don’t evaluate.” This is a principle to follow in the context of DevOps. Making DevOps quantifiable is essential to being able to identify and invest in tools and processes work and how to fix or eliminate the ones that don’t. DORA metrics are now the standard for teams seeking to improve their efficiency and attain the DevOps goals for speed, stability, and efficiency.

Do you know what DORA is?

The DevOps Research and Assessment (DORA) team is a research-based program which was purchased by Google in the year 2018. The goal of the team is to better understand the processes, practices and capabilities that allow teams to attain high performance in software and delivery of value. From 2014 through 2019the group released their most popular research, which included a series of annual reports that benchmark DevOps practices, address questions that are common to all DevOps team members, and then offer guidance on the ways DevOps teams can continually enhance their capabilities and processes.

In their book of the year, Accelerate Accelerate, the DORA team defined a number of indicators that they say shows the effectiveness of software teams with regard to development and deployment capabilities. Length of Lead, Time to Deployment Mean Time To Resolution as well as Change Failure Rate. These are now the parameters that become known in the form of DORA metrics.

The four DORA Metrics

The DORA group discovered that the top software teams that perform well – those which provide the greatest value, are the fastest and with the highest consistency – improve for four specific parameters specifically:

Change Lead Time

Lead time for change is the time from when work on a change request started to the point that the change has been put into production, and therefore delivered to the client. Leap time allows you to understand the efficiency of the development process we use is. Long lead times could be due to an slow process or bottlenecks along the pipeline for development or deployment.

The most popular method to measure lead time is to measure the date of the first commit of code to an issue with the date of deployment. An alternative, more thorough (though equally difficult to determine) approach is to measure the time at which an issue is chosen for development with the time of deployment.

The Deployment Frequency

Deployment Frequency is the measure of how frequently an organization pushes changes into production. This is a measure of how fast the team delivers software at your speed. DORA informs us that the best performance teams strive to make smaller and more frequently scheduled deployments. This can result in increasing the customer value by reducing time to value and reducing risk (smaller modifications mean less trouble for production issues when they are caused by changes) for the team responsible for development.

Change Failure Rate

Variation Failure Rate (CFR) is a measure of the speed that production changes can cause rollbacks, incidents or even failures. This indicates the quality of the code that you’re pushing to production. The lower the percentage here, the more efficient (higher performance teams have a failure rate for changes between 0 and 15%) However, the ultimate objective of the team in this case is to reduce the rate of failure to change with time as the capabilities and processes get better.

The most difficult part for many teams is defining what constitutes a “failure” for the company. It is too broad or limiting of a definition can encourage bad behavior. The definition of failure must be specific to every service, organization or even the group.

Mean Time To Recovery (MTTR)

MTTR is all about resolving issues or production issues in the event that they do occur. It’s the measure of the amount of time that passes from the moment an incident is started to the time it is resolved through changes to production. The objective to optimize MTTR is to reduce the amount of downtime and then, as time passes develop the systems to identify, diagnose, and rectify issues when they occur.

Utilizing DORA metrics to enhance your DevOps methods

As an engineer You are in the position to provide your team with direction and tools needed to be successful. Through monitoring and measuring DORA metrics and developments over time, teams, developers and engineers can make better-informed decisions on what needs to be improved and the best way to improve your development processes. If your DORA metrics increase you’ll be able to feel confident that you’ve taken the right decisions to support your team and also that you’re providing greater value to your customers.

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