Ten Key Metrics That Help Identify and Fix Bottlenecks in Your CI/CD Pipeline
March 25, 2020 | by Anjana Ramesh | Posted In DevOps
The secret sauce to making your DevOps initiative successful is “Implement, Measure, and Improve.” Especially, for continuous integration (CI) and continuous delivery/deployment (CD), it is important to understand what DevOps metrics you should track, so you can figure out the bottlenecks and fix them to make your efforts worthwhile. In this blog, we squeeze out some of the key metrics that organizations can track to accelerate their CI/CD pipeline. This would give you an idea of where to start and what metrics make sense to your organization.
Types of continuous integration(CI) and continuous delivery(CD) metrics
The primary goals of any DevOps practice revolve around three aspects: Time, Quality and Speed. Based on the aforementioned factors, the metrics can be grouped as follows:
- Time-based metrics
- Quality metrics
- Automation metrics
One of the main objectives of DevOps is to save time and ship code as fast as possible. Hence, gauging the performance of a CI/CD initiative predominantly revolves around measuring the time taken for each of the activities involved. Given below is a list of the common time-based metrics that organizations measure:
- Time to market (TTM)
- Defect resolution time
- “Code freeze-to-delivery” time
- Deployment time
Time to Market (TTM)
This defines the duration between the ideation of a feature and the “go-live” of the same. Your CI/CD efforts should significantly shrink the time taken to launch a feature to your customers. While traditional software delivery takes 3-6 months for every internal software release, continuous delivery can foster multiple releases weekly or daily.
It is therefore essential to keep a close watch on the time taken to release a feature to the customer and if the continuous integration and continuous delivery principles have helped you shrink TTM. If there’s no improvement, the reason could be the technologies you have employed, the workload of the developers, the complexity of the feature, or the processes per se. You should retrospect to see where the issue is and fix it to increase the speed of your CI/CD pipeline.
Defect resolution time
Defect resolution time or the lifetime of a defect defines the time taken to resolve an issue, raised after the code has been delivered or deployed. The time taken to resolve a defect can significantly impact your customer churn rate. The longer it takes to resolve an issue, the higher your churn rate will be. So, if the defect resolution loop is lengthy despite the implementation of your DevOps practices, there must be some process gaps that you need to identify and fix immediately.
“Code freeze-to-delivery” time
This defines the duration between the code freeze in the team and the delivery of the code. Continuous integration shortens this time frame. If it does not, you need to understand why and fine-tune your practices to achieve the desired result.
Since CI/CD practices involve a lot of automation, the code deployment should happen at the click of a button. If your team takes an hour or so for deployment, the process is at the peak of inefficiency. Tracking this metric helps you increase the frequency of deployment by eliminating the bottlenecks that hamper the speed of the pipeline.
Tracking quality metrics is invariably the most important aspect of DevOps. You might be shipping your code at your own pace. However, the last thing you would want to do is to compromise on the quality of your code. It is therefore pivotal to keep a check on how you are doing on quality. The quality metrics that organizations track include, but are not limited to:
- Test pass rate
- Number of bugs
- Defect escape rate
Test pass rate
The test pass rate gives you a clear picture of the quality of your product, based on the percentage of passed test cases. It can be calculated by dividing the number of passed test cases with the total number of executed test cases. This metric also helps you understand how well your automated tests work and how often code changes are causing your tests to break. Continuous integration and continuous delivery cannot be done without automated testing. However, you need to investigate if you are doing it the right way.
Number of bugs
This metric is crucial for your continuous deployment efforts because shipping a buggy code faster will only deliver more bugs to your customers, causing intricate problems later on. Hence, it is essential to regularly monitor the number of bugs and scrutinize the root cause in case of a spike. With a buggy code in the system, none of the DevOps initiatives will yield the results that it should.
Defect escape rate
The defect escape rate defines the percentage of defects found in pre-production testing versus in production. Tracking how many defects make it to production is a great way to gauge the overall quality of the software releases that you do.
If you are finding too many issues in production, then you know that you’re not doing a good job of automated testing, QA, etc. Therefore, you have to improve your testing practices and try moving faster again. Your defect escape rate is a great constant feedback loop to assess how your team performs.
Since DevOps relies heavily on automation, it is crucial to understand what impact it has created, when it comes to your deployment process. Given below are some of the metrics that will help you quantify your automation efforts while trying to fathom out if there is a scope for improvement:
- Deployment size per pipeline
- Deployment frequency
- Failed Deployments
Deployment size per pipeline
Deployment size or batch size is the number of story points such as feature requests, bug fixes, etc. that have gone live per month/application. This number hinges on the type of application and the velocity of your team. However, it helps you get a glimpse of the outcome that your CI/CD initiative has produced and is, therefore, an important metric to track.
Deployment frequency is a critical metric that indicates how your throughput performs during your product and/or project development process. Companies like Amazon and Netflix deploy code thousands of times every day, which proves they are doing DevOps right. Are you doing it right? This is something you have to find out in order to streamline your pipeline.
Have your code deployments made your customers fretful, time and again? Have there been frequent outages and downtime as a result of your deployments? If yes, this is an indispensable metric for your business.
Rolling back the deployments is not something teams prefer to do. However, if the frequency of failed deployments is high, you have to plan for a quick rollback so it does not affect the operational continuity of your business. Particularly, customer-facing businesses cannot afford to incur frequent failures. It is therefore essential to track the failed deployments to deduce the mean time to failure (MTTF).
These are just some key metrics that are tracked extensively in the world of DevOps. There are lots of other metrics that DevOps experts suggest. At the end of the day, the specific metrics that matter the most to your organization depend on your business, organizational and individual needs and the gaps you are trying to fix. Taking a “one-size-fits-all” approach does not work.
Therefore, collect data on a regular basis and leverage it to steer your organization in the right direction. However, do not get bogged down in inessential data points that would not add much value to your organization. Make sure you look out for the most important ones that will help you keep a finger on the pulse of your business.
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