CI/CD stands for Continuous Integration/Continuous Delivery (or Continuous Deployment). It’s a set of software development practices that enable frequent and efficient delivery of software updates to users by automating the entire software delivery process. CI/CD is often visualized as a pipeline that involves adding a high degree of ongoing automation and continuous monitoring to app development. You can transform your CI/CD pipeline into a source of real-time actionable information about its health and performance by making it observable.

ci/cd pipeline monitoring

Logging tools collect and store logs, allowing you to search, filter, and analyze them. This can be useful for troubleshooting, identifying root causes, and auditing events. Metrics tools collect numerical data such as CPU usage, memory consumption, response time, error rate, and throughput. This data can be used to visualize trends, set thresholds, and alert on anomalies. Tracing tools record sequences of events that represent a request or transaction in order to map dependencies, latency, and errors in distributed systems. Finally, APM tools combine logging, metrics, and tracing data to provide a holistic view of application performance.

Change failure rate

If GitLab is running in the cloud, look for a cloud container
registry offered by the vendor. In addition to that, you can make use of the
GitLab container registry which can be accessed
by the GitLab instance faster than other registries. Make careful choices when configuring pipelines to speed up pipelines and reduce
resource usage. This includes making use of GitLab CI/CD’s built-in features that
make pipelines run faster and more efficiently.

ci/cd pipeline monitoring

New Relic is a cloud-based performance monitoring and analytics platform that can be used to display metrics from a variety of data sources, including agents, integrations, and APIs. It allows you to create custom dashboards, and set up alerts and can be used to display pipeline metrics. Azure Pipelines is a cloud-based continuous integration and continuous delivery (CI/CD) service provided by Microsoft Azure. It is used to build, test, and deploy code to multiple targets, such as cloud services, virtual machines, and on-premises servers. To deliver the greatest level of visibility, these metrics should be correlated with other data, including log analytics and traces from your application environment.

Different approaches to monitoring

You can also scope your CI data by repository, branch, or commit in order to surface trends and troubleshoot issues. This provides a comprehensive view into CI activity and makes it easier to resolve bottlenecks, reduce CI costs, and deliver better software. In addition to the above, you can also use observability tools such as Application Performance Management (APM) solutions like New Relic or Datadog. APMs provide end-to-end visibility of the entire application and infrastructure, which in turn gives the ability to identify bottlenecks, performance issues, and errors in the pipeline. CI/CD operations issues may also make it difficult to test each release against a wide variety of configuration variables.

The list of metrics can also be quite exhaustive, but you don’t want to fall into the trap of trying to measure everything. Doing so can lead to analysis paralysis where your teams have access to lots of information but can’t make sense of which metrics to focus on to understand, address, or rectify certain issues, often leading to no effective work being done. These examples are very high-level and rudimentary but should help to provide a basis on which the team can start to extract this data from the CI pipeline to your required data source. Some data sources provide a command line tool that can be used to push data to the data source. For example, you can use the curl command to push data to a REST API endpoint.

Define your goals and metrics

An efficient alerting mechanism that augments the Continuous Integration and Continuous Delivery pipeline is crucial to support engineering and product velocity. They use built-in alerting to detect failures or anomalous conditions and combine alerts with webhooks to proactively solve problems when they’re detected. I’ve provided some examples of dashboards that could provide good visualization of your CI pipelines. The below dashboards are all created in Grafnan, but these sorts of visualizations can be represented in other tools. The below examples do showcase the benefit though of being able to configure the look of dashboards to better match your needs rather than relying on a generic dashboarding template which only provides a limited scope.

  • This gives you the ability to easily collect telemetry like metrics and distributed traces from your services.
  • Datadog was named Leader in the 2022 Gartner Magic Quadrant for Application Performance Monitoring (APM) and Observability.
  • Prometheus is an open-source monitoring and alerting system that can be used to collect and store metrics from a variety of data sources.
  • Are tests failing due to code changes, or instead because of race conditions and lack of computing resources?
  • By utilizing Splunk pipeline analytics and observability, you can ensure that your transformation objectives are being met.
  • The Service page provides more granular insights into your CI/CD workflows by breaking down health
    and performance metrics by pipeline.

By following these steps, you can find the system monitoring tools that meet your needs and help you reach your DevOps and CI/CD objectives. GitLab is a user-friendly code management platform that includes tools for CI/CD, code views, and troubleshooting, and comes with pre-installed packages for Linux distributions. It is a great option if you’re looking for one platform that allows you to plan, build, test, deploy and monitor applications. GitLab CI/CD is a continuous integration and delivery tool that’s available in open source or enterprise editions. Next there is automatic instrumentation and monitoring of application components (OpenTracing and OpenCensus, merged to form OpenTelemetry). Instrumentation is the process through which application code is extended to capture and report trace spans for the operations of interest in the path of handling a particular user request or transaction.

You may be using different tools in your team, but the principles should largely still apply. You may need to explore how best to achieve the same results given your specific toolset. Just having a CI pipeline in place though is not enough if you want to get the greatest value. Even the best-written code or the most flawless application will result in a poor user experience if problems in the CI/CD pipeline prevent smooth and continuous deployment. To use Azure Pipelines, you need an Azure DevOps organization or a GitHub repository. Azure DevOps organization is a cloud-based platform that provides a set of tools for application development, such as version control, agile project management, and continuous integration and delivery.

Continuous Integration

Elastic works with the Open Source communities leveraging OpenTelemetry to provide the best coverage. Integrating with many popular CI/CD and DevOps tools like Maven or Ansible using OpenTelemetry, Elastic Observability
solves these problems by providing deep insights into the execution of CI/CD pipelines. There are several key components of observability in a CI pipeline, including monitoring, logging, and tracing. There are plenty of other ways to do it, but using Prometheus is certainly the path of least resistance. This may simply be because it helps you monitor other workloads running in your Kubernetes clusters. You can also aggregate metrics from Prometheus instances running in different clusters by using Thanos.

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