Continuous Integration Observability Explained – The New Stack

Continuous integration (CI) is a DevOps practice in which code provided by engineers is frequently and automatically integrated into a project. CI involves the use of a shared version control system (VCS), which is usually accompanied by other tools (including testing tools) to manage the source code. Engineers push code changes using the shared VCS; the code is then reviewed and tested before the build process is complete. This whole process is automated to maximize speed and performance.

Observability refers to the practice of measuring the internal state of a system based on its corresponding output. It lets you gain insight into a system’s health by reviewing logs, data, and other key metrics.

CI Observability therefore provides visibility into your CI pipeline workflow. As more code is integrated, observability becomes an important process so that you can understand the performance of your infrastructure and ensure that quality code is submitted.

Why IC Observability Matters

A typical application’s software is a complex beast with many interconnected components. Therefore, problems or failures can occur in different components and at different stages of the workflow. CI Observability gives you insight into your software infrastructure and workflow. So when a problem inevitably arises, you can identify and fix it as quickly as possible.

CI Observability allows you to:

  • Assess the risk level of each pull request (PR): In a typical CI workflow, engineers generate a high volume of pull requests. With CI Observability, you can detect and analyze problems/failures (or the likelihood of them occurring) for each PR. This stops potential problems in their tracks in the early stages of development – especially major defects – thus limiting future negative costs and consequences.
  • Reduce test cycle times through test prioritization: Test prioritization is a process by which tests are ranked based on factors such as features, functionality, and critical components. This creates upfront cost and time requirements, but ultimately helps reduce test cycle time by producing efficient and relevant tests that allow you to make the necessary fixes.
  • Identify erroneous, slow, and flaky tests: Flaky tests are frustrating. Nobody likes to find out that a test that was previously passed is now failing. CI Observability helps you identify these tests, allowing you to remove or improve them and ensure that only quality, well-tested code is submitted.
  • Improve build times: Optimizing your build speed is crucial in development to help you ship your software sooner. To achieve this, your workflow requires proper testing and automation. However, factors such as flaky or flawed tests or bugs in your code can hinder this. CI Observability shows you where build speed impediments are so you can address them and improve your build times.

Pillars of observability

Now that we understand why CI observability is so crucial, let’s explore in more depth what exactly observability is. Observability consists of three main processes: logging, metrics, and tracing. Taken together, they give an overall picture of the health of your software.


Logging is the process of recording data about events with corresponding timestamps along with indexes with which they can be retrieved. For example, if a payment transaction fails in a payment system, such an event can be logged along with the timestamp at which the event occurred along with other necessary details that can give you an insight into the incident. . Logs are not only useful for recording errors; Recording logs is a general good practice because logs produce data for quantitative and analytical purposes.

Let’s review some benefits of journaling:

  • Event records can be retrieved easily anytime and for any reason using its searchable index.
  • Logs play an important role when you need to find and resolve errors.
  • Some logs can be monitored in real time, making it easy to find problems and solutions quickly.
  • They are plain texts, which makes them easy to store.


Metrics are quantifiable numeric values ​​that can be used to measure your app’s behavior, health, and performance. They can be collected, correlated, aggregated and analyzed to understand the state of your system as a whole.

While logs keep records of events, metrics go one step further by producing data from your system; while logs record events, metrics can show which events are really important. Thus, the metrics can be obtained from the logs.

Some benefits of metrics include:

  • Provide you with explicit data by which you can measure the health and progress of your application.
  • Detect anomalies in your system, which can help you predict future problems.


Tracing involves following the flow of an operation or request from its initiation to its completion. The information obtained is intended to be used to optimize the performance of your application. Tracing helps engineers determine which workflow steps contain bottlenecks, providing information including how and where the error occurred, what feature/function triggered the error, and what change caused the error. caused the error.

Tracing offers benefits such as:

  • Provide visibility on the different stages of an operation’s progress; this can be useful to optimize the application.
  • Help you detect areas in the operation path where problems occur.
  • Provide information with which you can improve the experience of your users.

CI Observability Challenges

With regard to the observability of ICs, specific difficulties are likely to arise. You may encounter challenges particularly related to the complexity and size of your application, which produce difficulties common to CI pipeline observability efforts.

Management of complexities

As more and more code is integrated, your application will become more and more complex. Getting a complete overview and understanding of your application can become difficult and overwhelming as you have to manage a growing multi-part application. As your application scales, the observability challenge also increases.

Real-time visibility

While it’s useful to be able to monitor your application in real time, finding or building a suitable tool can be time consuming if you choose to build and/or implement that tool in-house, or require significant financial outlay if you opt for outsourcing. However, without real-time monitoring, you won’t be able to detect errors in the early stages of your CI workflow, which can result in additional costs, both in time and money, for your team.

Observing substantial CI pipelines

Depending on the size of your project and the structure of your team, your application’s source code may become difficult for one person to understand. Getting good visibility into your CI workflow is essential when it comes to monitoring your workflow steps. Observability helps you identify relevant metrics and act on them quickly, and keeps a team of any size and complexity on the same page. As such, CI observability is essential for efficient and effective processes and for an optimized user experience.

Observability tools

Observability tools have features and functionality that allow you to perform actions such as monitoring, tracing, and logging. As such, they make it easy to gain essential knowledge about your application’s health and performance, thereby gaining insight into any needed fixes or improvements in your system.

Let’s review some key qualities you should look for in your observability tool:

  • Documentation: Good documentation makes the tool easier and faster to set up and use for your engineers.
  • Detailed dashboard: The tool should have a dashboard that can provide you with comprehensive information, as well as provide your team with a pleasant user experience.
  • Automatic error detection/analysis: The tool should be able to automatically detect errors at different stages of your workflow.
  • Event Alerts: Alerts notify you when certain anomalies occur within your application, enabling rapid response to critical events.
  • Event logging: The tool should support logging data in a way that is accessible and easy to retrieve.
  • Workflow monitoring: Monitoring CI workflows and viewing analytics based on system performance gives a holistic view of your system.
  • Real-time monitoring: The tool should be able to perform operations and return data on the go.

Common issues with monitoring tools

Having a powerful observability tool that offers all of the above features is key to optimizing your CI pipeline. However, many tools on the market today, whether APM or error tracking tools, fail in ways that can make full CI pipeline visibility difficult:

  • Some tools lack sufficient detail when dealing with applications with multiple interdependent components, which limits their usefulness and ability to provide complete visibility into your CI pipeline.
  • The volume of data generated from applications with complex architectures can be high, making it difficult to locate problems in the application. Most tools don’t handle this complexity adequately because they aren’t set up to handle and present huge volumes of data.
  • Troubleshooting and debugging can be a problem with tools that lack the functionality to effectively keep all relevant stakeholders up to date on the status of your CI pipeline.

It is essential to select an observability tool capable of handling complex architectures, large volumes of data and large multifaceted teams. Even if your application doesn’t have these needs today, you need a tool that can grow with you as you scale your application.

Introduction to foresight

Foresight is a comprehensive observability tool that gives you complete visibility into the state of your CI/CD pipelines. Foresight helps you assess the risk of new changes, reduce build times, and deliver quality software through powerful functionality.

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