Observability vs. monitoring in software development

In software development, the ability to quickly understand the health of your applications and diagnose issues is essential. Monitoring and observability are two approaches that can help teams detect, understand, and address problems. Although they are related, they serve different roles in tracking application health, especially in cloud-native environments and complex, distributed architectures.

In this article, we’ll explore the differences between observability and monitoring, their roles in software development, and how they can work together to boost productivity and improve resilience. Additionally, we’ll discuss how CI/CD fits into this ecosystem, allowing teams to simplify issue detection and resolution from development through production.

CircleCI CTO Rob Zuber talks with Honeycomb CEO Christine Yen about how observability helps teams deliver change with confidence on the Confident Commit podcast.

What is observability?

Observability is the ability to understand a system’s internal state by analyzing its external outputs. In software development, observability enables teams to analyze vast amounts of data from various sources to gain insights into the health and behavior of applications.

Observability is especially valuable in modern, distributed systems because it helps teams identify not only where failures occur but also why and how. By analyzing telemetry data, observability allows developers to view complex applications as cohesive systems rather than isolated services. This comprehensive view is critical for diagnosing issues that span multiple services or environments.

Observability typically relies on three types of telemetry data:

• Logs: Records of discrete events, valuable for pinpointing exact events or errors.
• Metrics: Quantitative data points, such as CPU usage or request rates, that reveal trends over time.
• Traces: Data showing the path of a request across components, essential for understanding latency or bottlenecks.

Observability makes it possible to collect, store, and analyze enormous amounts of information from across network boundaries, giving developers a complete picture of what is happening within an environment — even when multiple technologies are involved. It goes beyond error detection to provide actionable insights developers can use to improve and optimize their software.

What is monitoring?

Monitoring focuses on tracking predefined metrics and key performance indicators (KPIs) to detect deviations from expected behavior. Typically, teams use monitoring tools to collect data on factors like queue depth, CPU usage, response time, memory utilization, and error rates. Alerts are often configured to notify teams when certain thresholds are breached, allowing quick responses to potential problems.

While monitoring provides real-time insights into system performance and helps maintain service levels, it may not always identify the root cause of issues, especially in complex systems. For example, monitoring may detect that a service’s error rate has increased, but it may require deeper, more contextual insights—provided by observability—to understand the underlying issue.

In essence, monitoring is reactive, alerting you to issues as they arise, while observability is proactive, providing the tools to understand and prevent issues more effectively.

Observability vs. monitoring: How do they compare?

Both observability and monitoring play an important role in building resilient applications, especially within CI/CD workflows. Monitoring tracks essential health metrics and flags anomalies, helping teams respond quickly. Observability adds deeper, contextual insights, helping teams uncover patterns and relationships that monitoring alone may miss.

Monitoring	Observability
Focuses on known metrics: Monitoring is goal-driven, encouraging teams to define and track specific performance indicators, such as response times, error rates, and memory usage. These metrics provide a real-time snapshot of application health and ensure that systems meet predefined standards.	Explores unknown issues: Observability allows teams to detect issues that aren’t directly measured by established metrics. By analyzing logs, traces, and other telemetry data, observability helps uncover unexpected patterns, often referred to as “unknown unknowns.”
Real-time alerts: Monitoring triggers alerts based on threshold breaches, making it possible to react immediately to incidents that affect performance or uptime. This is especially valuable for responding to issues as soon as they arise.	Root cause analysis: Observability enables deeper analysis of the system’s internal state by interpreting data from multiple sources. This context allows teams to trace issues back to their root cause, rather than just treating symptoms.
Predefined performance goals: Monitoring helps teams ensure that systems meet specific service-level agreements (SLAs) and user expectations by tracking agreed-upon metrics.	Broad contextual insight: Observability offers a more comprehensive view of system behavior, helping teams understand complex relationships between services and identify the underlying factors driving performance changes.
Ideal for routine checks: Monitoring is effective for high-level health checks and day-to-day performance management, alerting teams to standard deviations that require action.	Supports proactive troubleshooting: Observability provides rich data that supports proactive troubleshooting and system optimization, enabling teams to address potential issues before they impact users.

While monitoring ensures that essential metrics are tracked and SLAs are met, observability provides the contextual data needed to understand and address complex, unexpected issues. Together, they empower teams to diagnose problems more accurately and lower mean time to resolution (MTTR) by enabling both quick detection and in-depth analysis. By using monitoring to identify immediate issues and observability to dive into root causes, teams can maintain robust, resilient systems that meet both performance and user expectations.

How to add observability and monitoring to your workflow

Integrating observability and monitoring tools in your development and CI/CD workflows allows teams to detect issues earlier in the software lifecycle. Here’s how they can be added effectively:

• Cloud provider monitoring: Major cloud platforms offer native monitoring tools. Examples include Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor, which help monitor applications and infrastructure across their respective ecosystems.
• Log and metric aggregation tools: Tools like Prometheus, Grafana, and the ELK stack (Elasticsearch, Logstash, and Kibana) help centralize log data, visualize trends, and set up alerts.
• Distributed tracing tools: Tools like Jaeger and Zipkin trace user requests across service boundaries, aiding in the diagnosis of latency issues in complex systems.
• All-in-one observability platforms: Platforms like Datadog, Honeycomb, and New Relic combine metrics, logs, and traces, providing a holistic view of application performance and health.

When combined with a CI/CD platform, these observability and monitoring tools can detect and address issues earlier, reducing downtime and ensuring smooth, dependable releases.

Observability and monitoring in CI/CD workflows

CI/CD pipelines automate and accelerate the build, test, and deploy process, ensuring new code moves quickly to production. Integrating observability and monitoring directly into your CI/CD workflows provides valuable, actionable feedback at each stage of development:

• Early issue detection: Teams can detect performance regressions or bugs immediately after a build, reducing the risk of issues reaching production.
• Increased confidence in testing and deployment: By analyzing telemetry data at each stage, teams gain confidence that new changes won’t negatively impact production environments.
• Faster feedback loops: Integrated observability provides real-time feedback, enabling teams to adjust quickly and release improvements faster.

With a CI/CD platform like CircleCI, teams can integrate third-party observability tools directly into their development workflow, ensuring that monitoring and observability extend from code changes to live production. CircleCI’s flexibility allows teams to connect with a range of observability tools, supporting a proactive approach to application health and reliability.

Conclusion

Observability and monitoring are both essential for maintaining the health and performance of modern applications, but each serves a distinct role. Monitoring focuses on detecting issues through specific metrics and alerts, while observability provides a deeper, systemic view of application behavior that enables teams to understand the root causes of issues.

Incorporating both practices into your CI/CD workflow allows for faster issue detection, continuous performance insights, and more confident releases. As you build a resilient development process, consider adopting a CI/CD platform like CircleCI. By automating your build, test, and deployment processes, CircleCI helps teams seamlessly integrate observability and monitoring into the development cycle, gaining actionable insights and enhancing overall productivity. Sign up for a free CircleCI account and start improving your development workflow today.