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Key takeaways
In today’s fast-moving DevOps-centric world, new application releases are delivered continuously, often with the added complexity of AI/ML integrations and evolving security requirements. Simply monitoring applications or infrastructure is no longer enough. To ensure system health and deliver a positive user experience, teams need deeper and more complete visibility into the CI/CD pipelines that power integration and release velocity.
CI/CD pipelines form the backbone of continuous software delivery, connecting development with production.
In this article, we’ll explore why CI/CD monitoring is essential, the key metrics that define pipeline performance, and best practices for observability that link development workflows with operational excellence.
Continuous integration/continuous delivery (CI/CD) pipelines are distinct from runtime environments, but they are deeply intertwined. A healthy pipeline enables development teams to write, build, test, and deploy code and configuration changes continuously — ideally automatically — with each new commit or merge.
Problems that occur inside the CI/CD system create a ripple effect, one that often leads to degraded application performance or missed delivery timelines. Even the best-written code won't meet user expectations if it’s blocked, delayed, or misconfigured during delivery.
(Related reading: the product development lifecycle.)
Poor pipeline visibility creates significant issues, impacting release cycles and developer efficiency. These problems often fall into distinct failure categories:
Slow or unstable CI/CD operations hinder rapid releases, delaying critical bug fixes. A spike in queue time can delay hotfixes during an outage, increasing Mean Time To Recovery (MTTR) and customer churn. Flaky tests causing random build failures also erode developer trust and contribute to these delays.
Without full visibility, detecting problems early is challenging. Bottlenecks like build delays or flaky tests may lead teams to skip important test cases, reducing coverage and increasing production bugs.
Technical debt extends beyond code, all the way into the release process. Lack of visibility often forces teams to rely on manual workarounds or custom scripts, quick fixes for release. Unfortunately, these ad-hoc solutions obscure failure points, making the pipeline harder to debug, scale, or improve.
For example:
When teams lack insight into code flow, adapting to changes (e.g., switching cloud providers or modifying infrastructure) becomes slower and riskier. Visibility enables safe, confident iteration.
Before diving into what to measure, it’s helpful to understand the typical stages of a CI/CD pipeline. While implementations vary, most follow a common structure:
Each of these stages is an opportunity to detect issues early, and each has distinct telemetry points worth monitoring. For a deeper dive into the CI/CD stages and how they connect, read our full guide to CI/CD pipeline architecture.
To prevent the inefficiencies and risks described above, teams must monitor CI/CD workflows as thoroughly as they monitor application environments. These metrics serve as critical signals for identifying friction, failures, and optimization opportunities within the pipeline:
Tracking these metrics gives you the foundation for CI/CD performance analysis. But the true power lies in correlating them with runtime telemetry from the applications themselves.
While ideal metrics vary by organization, there are industry-accepted targets that help teams gauge maturity. Here are rough benchmarks that you can adapt for your unique business and process:
Regularly tracking these metrics and trending them over time helps teams spot regressions and continuously improve delivery efficiency.
CI/CD metrics shouldn’t exist in isolation. When connected with application logs, traces, and performance data, they tell a more complete story and enable faster problem-solving. For example:
Correlating CI/CD metrics with operational signals helps you pinpoint whether issues stem from delivery mechanics, code quality, or infrastructure. And that means smarter triage.
Once you've implemented an observability platform that connects CI/CD pipelines with applications and infrastructure, it's important to turn that visibility into action. Strong CI/CD monitoring uncovers bottlenecks, and it also fuels faster feedback loops, more reliable releases, and better user experiences.
Here are five best practices to maximize the value of your pipeline telemetry:
Modern CI/CD pipelines are built using a variety of tools that handle different stages of the process. Each tool provides integration points for telemetry and monitoring, which should be tapped into for full pipeline observability.
Popular CI/CD tools include:
To create a complete picture of code-to-production health, you’ll first instrument these tools to emit logs, metrics, and traces, and then you feed that data into a unified observability platform. This visibility lets you troubleshoot failures at any stage, whether it's a broken test in GitHub Actions or a failed deployment in ArgoCD.
(See how observability as code (OaC) integrates observability directly into the CI/CD pipeline.)
To gain actionable insight, CI/CD monitoring must integrate with application performance and infrastructure telemetry. Platforms like Splunk Observability Cloud provide unified visibility, helping teams connect delivery metrics to runtime behavior in real time.
By using tools such as Splunk Application Performance Monitoring and Splunk Infrastructure Monitoring, teams can correlate CI/CD performance with logs, metrics, and traces across the software lifecycle. This end-to-end observability ensures that performance issues are resolved faster, before they reach users.
Observability isn't just about speed. It also helps enforce security and compliance across delivery workflows. With the rise of supply chain threats and policy mandates, it's increasingly important to monitor for:
By integrating security-focused signals into your CI/CD observability strategy, you ensure releases are not just fast — but also safe and accountable.
In modern software delivery, CI/CD pipelines are not tools for developers — they are core components of product and customer experience. Monitoring these pipelines with the same rigor applied to applications and infrastructure is essential for sustaining velocity, quality, and customer satisfaction.
By correlating CI/CD data with other application metrics, traces, and log analytics by using tools like Splunk Application Performance Monitoring and Splunk Infrastructure Monitoring, you put yourself in the strongest position to optimize performance and delight your users, even in fast-moving continuous delivery chains.
Ready to gain full visibility and control of your CI/CD delivery process? Start your end-to-end observability journey today with a free trial of Splunk Observability Cloud. Try it for yourself for 14 days.
Key metrics include deployment frequency, lead time for changes, deployment time, change failure rate, mean time to recovery (MTTR), and queue time.
Observability platforms like Splunk Observability Cloud correlate pipeline metrics with application logs, traces, and infrastructure telemetry, enabling faster troubleshooting and deeper delivery insights.
Common integrations include GitHub Actions, Jenkins, ArgoCD, Terraform, and GitLab. These tools emit logs and metrics that feed into centralized dashboards.
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