Key Metrics to Fix Continuous Delivery Pipeline Bottlenecks

Key Metrics to Fix Continuous Delivery Pipeline Bottlenecks

Implementation, measurement, and continuous improvement are the three essential ingredients that may make sure the success of your DevOps endeavor. It’s important to know what DevOps metrics you ought to track, especially for continuous integration (CI) and continuous delivery/deployment (CD), so you’ll work out the bottlenecks and fix them to make your efforts worthwhile. CI and CD are both acronyms for continuous delivery and integration. During this blog post, we break down a number of the foremost important metrics that companies may monitor so as to quicken the pace of their CI/CD pipeline. You’d therefore have a stronger understanding of where to start and what KPIs are relevant to your company due to this information.

Metrics for Continuous Integration (CI) and Continuous Delivery (CD), Diminished into their Several Types

Every single DevOps approach should center its core objectives on the subsequent three factors: time, quality, and speed. The subsequent categories may be applied to the measurements when considering the aforementioned aspects:

• Measures looking at time periods
• Metrics of internal control
• Metrics for automated processes

Measures Looking at Time Periods

One of the key objectives of DevOps is to save lots of time and ship code as fast as feasible. As a result, quantifying the quantity of your time spent on each of the tasks that are a part of a CI/CD initiative is the primary focus of the evaluation of the initiative’s performance. The subsequent could be a list of a number of the time-based metrics that are typically measured by businesses:

Time to plug (TTM)

Time required repairing defects “Code freeze-to-delivery” time required for deployment

Time on Market or TTM (TTM)

This quantifies the quantity of time that passes between the conceptions of a feature and therefore the point at which it’s made available to users. Your efforts to implement CI and CD should significantly curtail the number of times needed to bring a replacement feature to your customers. Continuous delivery can foster multiple releases on a weekly or maybe day after day, whereas traditional software delivery can take anywhere from three to 6 months for every internal software release.

Because of this, it’s of the utmost importance to stay an in-depth eye on the quantity of your time it takes to release a feature to a customer and to see whether or not the principles of continuous integration and continuous delivery have helped you reduce TTM. If there’s no improvement, the matter may depend on the technologies that you simply have implemented, the workload of the developers, the extent of complexity of the feature, or the procedures themselves. If you would like to speed up the speed of your CI/CD pipeline, you must perform a retrospective analysis to work out the source of the matter and repair it.

Time required to resolve defects

The amount of time it takes to repair a controversy that arises after the code has been delivered or deployed is named because of the defect resolution time (sometimes called the lifetime of a defect). The length of the time it takes to repair a problem may need considerable touching on your percentage of lost customers. The longer it takes to seek out an answer to an issue, the higher the speed of customer churn is. If despite the deployment of your DevOps methods, the defect resolution cycle takes a protracted time, there must be certain process gaps that you simply have to discover and rectify straight away.

The time from “code freeze” to “delivery”

This establishes the quantity of your time which will pass between the freezing of the team’s code and also the delivery of the code. This point frame is prevented due to continuous integration. If it doesn’t, you’ll have to determine why it failed and adjust your methods accordingly so as to urge the result you wish.

Deployment time

Because there’s a major amount of automation involved in CI/Continuous Delivery procedures, the code deployment should be as simple as clicking a button. If it takes your team over an hour to deploy, the method has reached its highest possible level of inefficiency. Monitoring this measure enables you to eliminate the bottlenecks that are slowing down the pipeline, which successively enables you to reinforce the frequency of deployments.

Metrics of Internal Control

Tracking quality metrics is usually the foremost critical component of DevOps. There’s an opening where you simply are shipping your code at your own pace. However, the standard of your code should be your top priority, and you ought to avoid making any compromises in this regard at the least bit cost. It’s consequently of the utmost importance to regularly assess how you’re performing in terms of quality. The subsequent are a number of the standard metrics that are monitored by organizations, however, the list isn’t exhaustive:

• The success rate on the examination
• The total amount of bugs
• Defect escape rate

Test pass rate

You may get an honest idea of the quality of your product by staring at the test pass rate, which is decided by the proportion of successful test cases. It’s possible to calculate it by dividing the number of test cases that were successful by the entire number of test cases that were disbursed. This metric also helps you assess how well your automated tests operate similarly because of the frequency with which changes to the code cause your tests to fail. It’s impossible to practice continuous integration and continuous delivery in the absence of automated testing. Nevertheless, you must explore whether or not the way you’re doing it’s the right approach.

The total amount of bugs

This measure is extremely important for your continuous deployment efforts because deploying a code that contains flaws faster would simply give more bugs to your clients, which can cause more complicated difficulties in the long term. Therefore, it’s vital to periodically monitor the number of defects, and in the event that there’s a rise, it’s important to analyze the underlying cause. Thanks to the presence of faulty code within the system, none of the DevOps initiatives will produce the results that they ought to have.

Defect escape rate

The defect escape rate is the percentage of flaws that are discovered during pre-production testing as hostile to those discovered during production. You will get an honest idea of the quality of the software releases that you just generate by keeping a tally of the number of bugs that truly make it into production.

If you notice a big number of problems in production, you’ll deduce that your automated testing, quality assurance, and other practices are lacking in a way. As a result, you wish to figure on improving your testing procedures and giving going faster another shot. Your team’s performance may be evaluated by employing a fantastic continuous circuit like the defect escape rate.

Metrics for Automated Processes

When it involves the deployment process, it’s essential to possess a solid understanding of the influence that automation has had, thanks to the actual fact that DevOps is primarily reliant on automation. The subsequent may be a list of a number of the metrics which will assist you in quantifying your efforts regarding automation while attempting to work out whether or not there’s room for improvement:

• Deployment size per pipeline
• Deployment frequency
• Failed Deployments

Deployment size per pipeline

The amount of story points, like feature requests, bug fixes, etc., that are made live across an application in an exceedingly given month is said because of the deployment size or batch size. This number can change betting on the type of program getting used and the way quickly your team works. Nevertheless, it gives you a view of the consequence that your Continuous Delivery endeavor has created and is, as a result, an important statistic to stay track of.

Deployment frequency

During the event process for your product or project, the frequency with which you deploy changes is a vital measure that reflects how well your throughput is performing. The fact that companies like Amazon and Netflix deploy code thousands of times per day is evidence that these companies are successfully implementing DevOps. Are you executing this step correctly? See the solution to the current question if you would like to create improvements to the efficiency of your pipeline.

Have your frequent code deployments on multiple occasions caused unease among your clientele? As for the results of your deployments have there been regular instances of outages and downtime? If the solution is yes, then this metric is completely necessary for your company.

The act of rolling back deployments is one that teams attempt to avoid doing the maximum amount possible. However, if there’s a high rate of failed deployments, you must make preparations for a rapid rollback so as to make sure that the operational continuity of your company isn’t disrupted. Businesses that interact directly with customers specifically just cannot afford to possess failures that occur on a daily basis. It’s consequently necessary to stay track of deployments that have failed so as to calculate the mean solar time to failure (MTTF).

In the field of DevOps, these are just some of the foremost important metrics that are monitored in great detail. There are an outsized number of other metrics that DevOps professionals recommend. At the tip of the day, the precise metrics that mean the foremost to your organization are visiting depend upon the business needs, organizational needs, and human needs that you simply are attempting to deal with, furthermore because of the gaps that you just currently have. The strategy of treating everyone with a “cookie-cutter” solution is ineffective.

As a result, it’s essential to consistently collect data and make effective use of this information so as to steer your firm within the appropriate path. On the other hand, ensure you do not become mired down in non-essential data pieces that will not really help your organization out a great deal. Make certain to stay an eye fixed out for those that are the foremost significant and can assist you in maintaining your finger on the heartbeat of your company.

About Enteros

Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.