CI/CD Insights and Analytics

4 Best Practices for Observability

In this blog post, we discuss the four techniques your team can use for a fully observable CI/CD pipeline, so you can achieve faster fixes and improve code confidence.
Ismail Egilmez
4 mins read

4 Dimensions of CI/CD Observability

Observability is the most important feature for DevOps teams—letting them use a system’s external outputs to infer its internal state. An observable CI/CD pipeline makes it easier to proactively monitor any problems or track errors during the build process.

Ideally, observability is a continual process that starts with CI/CD pipelines and continues during the application’s entire lifetime. Without this level of visibility, it’s harder—if not impossible—for DevOps teams to understand the root causes of issues that arise.

In this blog post, we’ll discuss the four techniques your team can use for a fully observable CI/CD pipeline—so you can achieve faster fixes and improve code confidence.

1. Optimizing Logs

Using log data gives DevOps teams greater visibility into systems and applications. Logs can provide critical troubleshooting insights, showing exactly how a system became faulty or how frequently an error is occurring within an application. When properly implemented, logging improves your application-state monitoring.

The issue is, logs are often written ineffectively. Developers choose when and how to log, and this can lead to insufficient logging, excessive logging that is too noisy to be useful, or logs that fail to add enough context to make the information actionable. Log-data bloat can quickly add to the time and cost required for analysis, among other challenges associated with extraneous data.

By optimizing and centralizing log data, DevOps teams can prioritize the application-critical metrics they need to track. So make sure your logs are structured and descriptive, tracking only the essential details:

  • Unique user ID
  • Session ID
  • Timestamps
  • Resource usage

Keep these logs organized and available in a centralized location so they can be correlated and linked to a user or session to provide system-wide insights.

2. DevOps Culture

While organizational culture may seem intangible, it is critical to achieving a high level of observability across an application. Some strategic initiatives can only be met when employees support the idea and are aligned around the processes needed to achieve it.

Consider a DevOps cultural transformation to increase collaboration and communication between your operations and development teams. Achieving this means you have to:

  • Embrace end-to-end responsibility
  • Build a collaborative environment
  • Drive a willingness to fail (and learn from it)
  • Focus on continuous improvements
  • Zero in on customer needs
  • Automate as much as possible

Each software team should own its entire lifecycle, with debuggable code from beginning to end, and wrap that code with useful metrics, KPIs, and logging. This way, the application will have greater overall observability, and the operations team will have what it needs to predict failures or detect them quickly when they occur.

Unpredictability is the norm when it comes to deploying code, but a DevOps culture allows you to be prepared for anything that happens. No matter what unexpected application errors crop up, they can be effectively addressed when everyone understands your organization’s shared goals—that is, knowing the answers to these questions:

  • How are we determining failure and success?
  • What metrics are needed to assess rates of success and failure?
  • What is most important to optimize and improve?

Software developers and engineers can’t achieve observability without the rest of the organization. It’s a collective responsibility to build a DevOps culture that transforms processes, mindsets, and daily practices.

Once created and sustained, a DevOps culture can increase performance and observability for applications, streamline work processes, boost collaboration, and improve productivity.

3. Observability in Production

No matter how excellent the software you created is, something that will inevitably be missed or new issues will arise. Even Amazon’s CTO, Werner Vogels, says, “Everything fails, all the time.” Applications depend on storage, queues, and other critical components. Some errors don’t happen until after the application is deployed to production.

Traditional monitoring and testing can’t always help with new errors or intermittent issues. If your applications and systems are built with observability in mind, your team will be able to anticipate problems more effectively.

Production observability depends on two things: passive monitoring and alerting.

Passive Monitoring

A passive monitor collects user data from individual network locations, monitoring data flow and gathering statistics about usage patterns. This is critical for a comprehensive understanding of efficiency, user habits, and other details that enable software teams to track user experience directly with real data.


Alerts can be configured to send notifications when an application behaves outside of predefined parameters. It detects important events in the system and alerts the responsible party—usually via email, SMS, or even Slack. An alert system ensures that developers know when something has to be fixed so they can stay focused on other tasks.

4. Pre-Production Observability

Developers always hope their code gets deployed to production, fully functional and bug-free. This doesn’t always happen, but increasing observability pre-deployment will reduce the errors that can eventually occur in production.

Often, attention is focused on production systems, where downtime and errors need a more urgent response. This means DevOps teams miss the opportunity to make systems observable from the very beginning of development. Pre-production observability helps teams fix potential issues before their code enters production—and can have lasting benefits throughout an application’s life. By increasing pre-production observability, teams are better prepared to plan architectural changes, decide what gets built, determine how features are shipped, and optimize how code is written.

One method of resolving issues discovered outside of a production environment is via test monitoring, which gives developers yet another layer of security. Test monitoring tools like Foresight make it possible to debug tests before your code is deployed into production. It enables you to troubleshoot the route courses of the erroneous tests without reproducing the error locally.

Whether in a cloud-native environment, Kubernetes, Lambda, on-premises, or a wide range of other deployments, developers can monitor their CI pipelines with Foresight and get a deep dive into the errors or latencies.


The four strategies discussed above can all increase observability in their own ways, but pre-production is the most effective approach. It allows DevOps teams to catch and repair issues before they affect users—and while the cost to remediate is still low.

Software teams that use test debugging tools like Foresight can boost development velocity, saving time they would normally spend reproducing production issues locally. With Foresight, they can detect any defects on the CI server (AWS, Azure, GCP, etc.) without having to reproduce errors locally.

Solving problems should be taken care of before systems are in production. Foresight offers end-to-end observability and deep insights by integrating security, visibility, and debugging with your CI/CD workflows.

Improve your observability and see errors at a glance. Get started with your free Foresight account today.

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