Home Articles DevOps Metrics – How to measure success in DevOps?

DevOps Metrics – How to measure success in DevOps?

Compare the cloud Blog DevOps
Compare the cloud Blog DevOps

Even though there is no perfect definition for DevOps, experts believe it is a combination methodology for improvising the software development lifecycle. It provides collaborative work between the application development and the IT operation team. DevOps delivers enhanced communication, consistency, and collaboration leading to an efficient, secure, and faster software development process. 

The DevOps metrics allow for measuring success, benchmarks, and milestones. The metrics help in tracking performance and provide valuable analytics that help in improving future processes. 

Some Interesting Statistics of DevOps Implementation

Over the past couple of years, the demand for DevOps among App Development companies has risen steeply. Let’s take a look at the interesting facts and statistics about implementing the DevOps strategy. 

  • The word ‘DevOps’ is derived from Software Development (Dev) and IT Operation (Ops). The strategy of DevOps supports agile software development on several occasions.
  • The global market size of DevOps is expected to reach $10.31 Billion by the end of the year 2023. The rising demand for fast application delivery among clients has increased the need for DevOps among Software/App Development Companies. 
  • Organisations that are good at handling DevOps have very strong teams with well-defined communication channels. 

How To Measure DevOps Success?

Measuring DevOps success is essential for modern businesses so that they can easily predict what and how their teams do on application development. Also, metrics involved in measuring DevOps success help businesses analyse the efficiency of their team involvement in app development. 

Here are the few aspects that play a key role in measuring DevOps success.

  • It is important to understand how fast the team can deploy the software while focusing on the technology. Once-a-week deployment is a good option but depends on the individual deployment goals. 
  • Implementing automation in several processes may lead to faster identification and fixing of the issues. Using this team can focus on improvising the application and decreasing the failure rate.
  • Technology may face downtime due to service and maintenance. In such a situation, how the DevOps team can help in resolving the issues and restoring services.  
  • The time taken for the code completion process and app deployment. More expertise will lead to a faster lead time.
  • Efficient customer service will help in prompt addressing of the issues or queries of the customers. 
  • Automation helps in continuous monitoring of the process for the change in code, security, or process parameters. This testing helps in the efficient tracking of automation. 
  • Some defects may be noticed after the deployment of the software. The metrics allow for identifying defects that escape the production line. 

List of DevOps Metrics to Measure DevOps Success:

There are many DevOps Metrics used for measuring DevOps success. Some of the key metrics are briefed below. Take a look.

  • Deployment frequency: This metric helps in measuring how often the team successfully releases the software. With the adoption of continuous integration/ continuous delivery (CI/CD), the frequency of release is high. This high deployment frequency helps in the efficient fixing of bugs, enhanced improvements, prompt implementation of new features, etc. It enables developers to get faster real-world feedback for improved development. This metric enables measuring long-term and short-term efficiency. It allows for identifying bottlenecks and solving the issues effectively.
  • Lead time for changes: The metrics measure the time taken for incorporating the committed code into production. This metric is important as it allows for understanding how quickly the team can respond to any system-related issue. A shorter lead time implies faster issue solving, whereas complex issues may take a longer lead time. This metric can be improved by implementing quality assurance testing within multiple development environments and incorporating automated testing. 
  • Change failure rate: This metric measures the percentage of deployments that fail in production and require bug fixing or roll-back. This metric checks the number of deployments attempted and how many of those failed during production. This metric helps in gauging the stability of efficiency of the DevOps process. If the rate of change failure is more than 40 % means the testing procedures are poor and significant change is required. 
  • Mean time to restore service (MTTR): This metric allows us to understand the time taken by the organisation for recovering from a failure in production. It ensures the resiliency and stability of the software. This metric helps the team understand what improvement is needed in the response process. Longer MTTR indicates poor monitoring and can result in affecting more systems. The deployment of software in small increments can help in achieving quicker MTTR and reducing the risk and deployment of automated monitoring solutions for anticipating failure. 
  • Defect escape rate: This measured the number of bugs escaping testing and getting released into production. It helps in determining the effectiveness of the testing procedure and the overall quality of the product. A higher defect escape rate implies that the process needs improvement and enhanced automation. A lower rate or zero value indicates high-quality software and a well-functioning testing program. It is important to track all the defects from all the stages. 
  • Mean time to detect (MTTD): This metric measures the average time between the start of the incident and its discovery. This metric helps in determining the effectiveness of the monitoring and detection capabilities. For this metric, all incident detection times for all projects and teams are divided by the total number of incidents.
  • Percentage of code covered by automated tests: This metric measures the proportion of the code with respect to the automated testing. Implementing automated testing implies greater stability of the code in software development as compared to manual testing. The goal is to achieve a higher percentage of code.
  • App availability: This metric is useful in measuring the proportion of time for which the application is fully functional and accessible to the end-users. For determining accurate application availability, it is important to measure the actual end-user experience and not the network statistics. 
  • Application usage and traffic: This metric helps in monitoring the number of users accessing the system and also determines the system uptime. On the deployment of the system, the users start accessing the system and the number of transactions is noted, ensuring normal operations. If the application traffic and usage increase, there are increased chances of failure under pressure. If the traffic and usage are less, it indicates there are not many users. The DevOps team can use this metric to ensure systems operate as they have projected, and if it deviates then the team needs to take the appropriate action. 
  • Other metrics: The other DevOps metrics include Change Volume, Meantime to Failure, Customer Feedback, Automated Test Cases, Service Level Agreements (SLAs), Unplanned Work Rate, Process Cycle Time, etc.  

Closing Thoughts

Implementation of DevOps helps in enhanced collaboration and communication between the product development and the IT teams. A successful DevOps practice helps in efficient monitoring of the software development process and ensuring that the process, pipeline, and tools implemented help in achieving the intended goals for faster delivery of software. 

The different metrics help in evaluating the success of the software. It also helps in identifying the issues or defects and helps in improving them. It also gives insights into incorporating newer technology for software development.