DevOps Metrics for Optimizing CI CD Pipelines BMC Software Blogs

Observability for the CI/CD pipelines is the step-child, with a less established practice. Lack of CI/CD observability results in unnecessarily long cycle time, or Lead Time for Changes, which is another crucial metric measuring how much time it takes a commit to get into production. It means your bug fixes, enhancements and new features will be rolled out with delay. Now imagine the frustration of the users waiting for it, of the business that wants to launch it, not to mention the other developers wanting to run their own pipelines and get stuck in the queue. Add to that the unfriendly experience of the Developer on Duty needing to handle failed pipelines on his shift.

ci/cd pipeline monitoring

A configuration manager is a centralized point of control for infrastructure settings that can be applied once for multiple servers. CI/CD is the backbone of a DevOps methodology, bringing developers and IT operations teams together to deploy software. As custom applications become key to how companies differentiate, the rate at which code can be released has become a competitive differentiator. ci/cd pipeline icon This can lead to increased collaboration, efficiency, and fewer software development life cycle errors. DevOps teams often use monitoring and observability interchangeably. While both concepts play a crucial role in ensuring the safety and security of your systems, data, and applications, monitoring and observability are complementary capabilities and are not the same.

Deploy Resources and Toolchains with Terraform

It uses declarative programming language and automation to set up the containerization for the DevOps infrastructure. Most of the configuration and CI/CD tools integrate with Kubernetes out of the box. While it’s often seen as only a continuous integration tool, Jenkins offers various plugins to automate the whole process. Any configuration management tool requires installing an agent software. These are small programs that work as a medium between a master program , and pass the commands to the dedicated servers.

As developers push out code, they automatically trigger software builds. We will look at the process from logging a task to coding and then building and deploying to the destination application. We will look at Azure DevOps as the platform for all this process and then deploy the application to an Azure App Service as a web application.

Deployments of 5G technology in Kubernetes

This will provide a deployment-ready artifact after undergoing all the testing, validation, and verification processes. Continuous deployment is a process where code is pushed to production automatically. As the build passes all the tests successfully, automated CI/CD systems can deploy them on the production server.

ci/cd pipeline monitoring

You can also use synthetic monitoring to compare how applications perform with and without the use of CDNs, which will also help you anticipate different types of user experiences. This is a great example of the “experiment” advantage discussed earlier. One is to ensure that your synthetic monitoring tests cover a wide variety of transaction types and variables. Experimentwith different options or techniques to see if performance improves. For example, implement different Resource Hints to see if critical metrics like Web Vitals improve.

RedHat offers a big range of services we have mentioned previously. Considering that OpenShift uses the Kubernetes engine, it seems like a good alternative for the project with open-source code. Docker is widely known for containers, as it’s the most popular tool to build them.

CI & Operational metrics

While most providers offer both cloud and on-premise hosting, Bamboo CI is recently available for on-premise hosting only. Jenkins recognizes the commits and pulls them to create a new build on its server. The enterprise tool that allows for automating the orchestration is paid, so check the corresponding page. The SSH key is a shell that secures connection with a virtual entity , so Ansible utilizes a more simplistic but still secure way to operate the infrastructure. It also uses a declarative language to specify the desired state.

To perform synthetic monitoring, engineers use frameworks that allow them to script application requests and then automatically execute and monitor the transactions. Selenium is probably the most popular open source framework for synthetic testing, although it’s often used in conjunction with proprietary tools that make it easier to orchestrate tests and analyze results. Continuous integration has many benefits, including early integrating and testing, enhancing developer productivity, accelerating delivery, and finding/fixing bugs faster.

Klera offers a high level of flexibility to connect with tools and spin up custom dashboards for monitoring every aspect of an application, its underlying infrastructure, and network. To this end, it offers DevOps 360, which is an out-of-the-box solution that helps you stay on top of your application health and performance. The solution offers detailed dashboards to monitor infrastructure, application, platform, end-user data, builds and deployments, incidents, and more.

Collecting key testing metrics to make the right decisions is very important when building a CI/CD pipeline. Testing pipelines should aim at facilitating early and continuous testing. Unfortunately, it’s still one of the biggest challenges that companies are struggling with today.

This process is mostly run in Agile sprints where a certain number of tasks are assigned to developers for a certain amount of time, e.g., two or four weeks, and this is known as the sprint cycle. The CD in the CI/CD process also stands for continuous deployment. Continuous deployment automatically releases code changes to end-users after passing a series of predefined tests, such as integration tests that test code in a copycat environment to ensure code integrity. However, with the advances of cloud computing, microservice architecture, and automated pipelines, more security vulnerabilities start to appear. DevSecOps is a practice of implementing security testing procedures in the whole DevOps process.

Step 1: Collect with OpenTelemetry

Data Analytics us best for predictive analytics, which can help organizations allocate resources more effectively. Organizations can predict the resources required for future projects by analyzing historical data on software development projects. Predictive analytics can also help organizations identify areas where additional resources may be required to meet project deadlines. The test stage incorporates all the automated testing to validate the behavior of the software. The goal of this stage is to prevent software bugs from reaching end-users. Multiple types of testing from integration testing to functional testing can be incorporated into this stage.

  • Jenkins is self-contained in Java and supplied by libraries and files of OSs like Mac, Windows, and other Unix-based ones.
  • CI/CD pipeline helps IT leaders, to pull code from version control and execute software build.
  • Monitoring, Dashboard, and Reports are vital when building a CI/CD pipeline.
  • The application delivery lifecycle has many stages — from app development, to testing, to monitoring in production.
  • It enables responsible developers to know about the important issues.

Splunk On-Call integrates metrics, logs and your monitoring toolset into a single source of truth that allows on-call teams to quickly fix problems. Additionally, teams can collaborate on problems via chat integrations and alert routing through mobile and web interfaces, and post-incident reports mean teams’ services improve over time. With CI, a developer practices integrating the code changes continuously with the rest of the team. The integration happens after a “git push,” usually to a master branch—more on this later.

Why optimize CI CD pipelines with data analytics?

With people and locations established, the next step is to decide on timing and how development teams will work with the business. CI/CD is considered a joint transformation for the business, so simply having IT run the process isn’t enough to create change. Software development teams should map capabilities to processes, then map processes to assets. They should also set goals for themselves along the way, such as one capability mapped per week.

CI/CD pipeline examples

One way to address this is to frequently merge the code and validate it. The pipeline gets activated when changes are made to the repository, like code commits. The pipeline downloads the code and initiates the build process. Best practices for the use of CI/CD pipelines range from those specific to the CI/CD tools employed to the integration of security into the apps. However, the use of automation, experimentation, DevOps, and best practices across the entire development life cycle and all development components – including CI/CD pipelines – can make a difference. Jenkins is an automated CI server written in Java and used for automating CI/CD steps and reporting.

Now, let’s turn to actual metrics that can help you determine how mature your DevOps pipeline is. Once you have dashboards for Jenkins and ArgoCD Grafana, it is fairly easy to set-up alerts for them. If you are using MetricFire’s Hosted Prometheus offering then you should be able to set up alerts in a breeze. Alternatively, you can also configure alerts in a Prometheus rules file and deliver them using Alertmanager. Now, since Github is a hosted service at this time we will focus on Monitoring Jenkins and ArgoCD only.

How To Set Up a Continuous Integration & Delivery (CI/CD) Pipeline

Understanding tooling will help you set up the process for the DevOps team in the right way. In this article, we’ll discuss the categories of tools existing for DevOps and look at instruments for continuous delivery/integration, testing, monitoring, collaboration, code management, and more. If you know the basics, feel free to skip the first section and jump right into the DevOps tools section. By automating CI/CD throughout development, testing, production, and monitoring phases of the software development lifecycle, organizations are able to develop higher quality code, faster. Although it’s possible to manually execute each of the steps of a CI/CD pipeline, the true value of CI/CD pipelines is realized through automation. While it is possible to use some open-source CI/CD monitoring tools, it is debatable if it’s ok to refer to them as free CI/CD pipeline monitoring tools.

In the reactive approach, updates to monitoring systems are here a reaction to incidents and outages. This approach is therefore most useful after an incident happens, as it allows you to capture and store real-time metrics. These metrics are later used to investigate historical data and analyze it. Based on the outcome of this analysis, preventive measures are introduced to prohibit the recurrence of this incident.