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DevOps improves the speed and quality of software delivery through a series of practices that pursue an agile mindset. When you mention DevOps, the first terms that come to mind are continuous integration, continuous delivery and deployment, collaboration, automation, and monitoring. DevOps means different things to different teams. Some teams are all committed to automation, while others do things manually and still think they are doing DevOps. Some people think that it is a kind of culture and a kind of thinking stereotype.

Because DevOps revolves around continuous delivery and fast code delivery, it is important to act quickly without any major errors. Tracking DevOps metrics that can help you achieve this goal is critical. In order to succeed in DevOps, the team needs to use many different tools. This is why different DevOps metrics are critical for different development teams.

Therefore, before you start using DevOps, your team should determine what DevOps means to them. Also, the team should find the biggest DevOps challenge. They can then more easily identify the DevOps metrics they need to monitor more actively to improve and create higher-quality software delivery processes.

The following are important DevOps metrics that most teams consider important:

Deployment frequency

New features and technology enhancements are important to develop and maintain a competitive advantage to provide updates with higher quality and accuracy. The opportunity to increase delivery intensity helps to increase flexibility and better comply with changing consumer needs. The goal should be to make small deployments as often as possible. When the deployment scale is small, software testing and deployment will be more comfortable.

Measuring the frequency of deployment on a regular basis will provide greater visibility to which improvements are successful and which parts need to be changed. A rapid decline in frequency may indicate that other tasks or manual operations are interfering with the workflow. In order to achieve sustainable growth and development, it is recommended that deployment frequency indicators with small but sustainable changes are the best.

Further, make tests easier to manage and measure production and non-production deployments. In this way, you will be able to determine how often the deployment performs quality checks and optimize for early and smaller deployments.

Deployment time

This metric measures how long it will take to implement the deployment. Although it may seem trivial at first, measuring deployment time is one of the DevOps indicators that can indicate potential problems. For example, if your deployment takes an hour, there must be a problem. This is why it is best to focus on smaller but more frequent deployments. Implementation: capture the build time.

Automated test pass rate

It is strongly recommended that teams make effective use of unit testing and integration testing to maximize speed. Because DevOps relies heavily on automation, useful DevOps metrics are used to measure the effectiveness of automated testing. It is useful to know how many code adjustments can cause the test to crash.

Code submission

This metric calculates the number of times the team commits the software before implementing it into production. This can measure both the speed of development and the accuracy of the code. The team should propose the standard code submission scope that each team member should follow.

A large number of commits can mean poor code quality or a lack of clear development goals. On the other hand, when the number of people is below the standard range, the team may be unproductive or well organized. It is necessary to identify reasons for reducing or increasing the number of submissions in order to maintain efficiency and project progress while still maintaining maximum happiness among team members.

Defect escape rate

Regardless of your experience with DevOps, errors can occur-especially if you make frequent adjustments. Software development involves experimentation, and as part of the process, you should always anticipate errors.

The defect escape rate metric shows your ability to capture software defects before they are put into production, which is especially important if you want to deliver code quickly. In order to successfully achieve this goal, you need to detect defects effectively.

Expenses

While the cloud is an excellent solution to reduce infrastructure costs, some unplanned errors and events can lead to high costs. This is why you should focus on capturing unnecessary costs and trying to reduce costs, and visualizing your sources of expenditure can play an important role in understanding your most expensive operations. Ideally, use a tool that automates your sleep cycle and wakes up the environment only when you actually use them to reduce costs.

Failed deployment and environment health

Deployment usually causes problems for your users, and sometimes we have to undo failed deployments. Even if this is not what we want in our activities, we should always be aware that it can happen. Frequently failed deployments are an indicator of our environmental health, which gives us the next indicator.

Detection time

While it is best to reduce or even eliminate failed changes, it is important to catch failures quickly, if they occur. The timing of determining key performance indicators will determine the appropriateness of the current response. This high detection time can trigger restrictions that may disrupt the entire workflow.

Unplanned work

This is the time you spend on tasks that you didn't have in the original plan. In standard projects, the UWR (unplanned work rate) should not exceed 25%. Higher UWR may expose work wasted on unexpected errors that are clearly not found early in the workflow. Along with the rework rate (RWR), this is an attempt to solve the problems in tickets, and UWR is also an important indicator.

Mean time of failure (MTTF) mean time of failure (MTTF) is the average time it takes for a defective system to run until a failure occurs. The duration begins when a major defect occurs in the system and ends when the mechanism finally breaks down.

MTTF is used to track the status of unrepairable system components and to evaluate how long they can work before they fail. This metric also allows the DevOps team to maintain the status of components used in mission-critical systems when identifying failures.

Application performance

Before performing the deployment, you should check for performance failures, unknown errors, and other issues. You can also monitor changes in the entire program output during and after deployment.

After the release, it is normal to see some SQL queries, Web server calls, and other program requirements that make significant adjustments to the use. To detect them, you can use monitoring tools, which will accurately display the changes for you.

Average test time (MTTD)

When problems do arise, it is important that you easily identify them. You don't want a serious local or large machine failure, and you don't know about it. Setting up powerful application monitoring features can help you find errors easily.

Mean recovery time (MTTR)

MTTR is a measure of the success of an enterprise in solving problems. * * the ability to analyze the effectiveness of the business and customer experience provides the perspective needed for a comprehensive understanding and prioritization. MTTR calculates the total response time from failure to resolution and provides information about whether the client has lost control, experienced a delay, or abandoned the system. Improving MTTR can reduce the impact of these problems, thus maintaining users' happiness.

It is critical to reduce MTTR by installing practical application management tools to quickly detect problems and easily execute patches.

Delivery time

An important indicator of workflow and efficiency is to estimate the average time required for a project from concept to implementation. The low delivery time shows that the team is very flexible and responsive, and can respond to feedback quickly.

Agile methods related to DevOps can provide fast processing time for framework improvements, enabling enterprises to meet the needs of consumers and focus on changing trends. You can use tools such as Jira and Trello to effectively capture delivery times.

Quality change

Because DevOps involves frequent changes, you must measure the rate of change between deployments to support deployment frequency numbering. The ultimate goal should be to focus on meaningful improvements to reduce inconvenience and lead to a smoother experience. For each deployment, monitoring changes can describe development more accurately. You can get this information from tools such as GitHub,Bitbucket and Jira.

Customer feedback

A positive customer experience is critical to the survival of the product. Satisfactory customers and good customer service lead to an increase in sales. This is why the customer ticket indicates the level of customer satisfaction that reflects the quality of your DevOps process. The smaller the number, the better the service.

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