In our blog series, we’ve debunked the following observability myths so far:

• Part 1: You can skip monitoring and rely solely on logs
• Part 2: Observability is built exclusively for SREs
• Part 3: Observability is only relevant and beneficial for large-scale systems or complex architectures
• Part 4: Observability is always expensive
• Part 5: You can create an observable system without observability-driven automation

Today, we’re delving into another misconception about observability—the belief that it’s solely applicable to a specific part of your stack or application.

This misconception arises from a fundamental misunderstanding of observability’s core concept. By viewing observability as limited to one layer, it overlooks its holistic nature, which spans across all stack layers and their interconnections. By dispelling this myth, our goal is to illuminate observability’s essence as a comprehensive practice offering profound insights into the functionality and performance of entire systems.

In modern software and system management, observability goes beyond focusing on just one part of the stack. It encompasses the entire system—from the application layer to the infrastructure layer and everything in between.

The myth likely stems from a narrow view that only monitoring one specific component, such as the application layer, is sufficient for understanding system behavior. However, this approach can overlook intricate interactions and dependencies between different parts of the stack.

True observability requires observing and analyzing data from all layers of the system, including application metrics, traces, and infrastructure telemetry. This comprehensive approach enables teams to uncover insights into how the entire system operates, identify performance bottlenecks, detect anomalies and, ultimately, deliver a more reliable and efficient experience for users.

Observability is applicable across various platforms—including mobile, web, cloud and mainframe systems—because it encompasses a wide range of technologies and environments.

Let’s explore the technical details of how observability works in different technology stacks and why it should be adopted universally:

• Mobile applications: Observability in mobile applications involves instrumenting code to capture relevant events, metrics and logs. It is achieved through observing real-time frameworks, performance-monitoring libraries and crash-reporting tools. By integrating observability mechanisms into mobile apps, developers can gain insights into user interactions, performance bottlenecks and errors, helping improve user experience and overall app quality.
• Web applications: In web applications, observability revolves around capturing and analyzing data from different layers, such as frontend, backend and infrastructure. This includes logging HTTP requests, database queries, server response times and system resource utilization. By aggregating and analyzing this data using observability tools, teams can identify performance issues, detect errors and optimize application performance.
• Cloud-based services: For cloud-based services, observability focuses on monitoring and analyzing distributed systems and microservices architectures. This involves capturing and correlating logs, metrics and traces across various components and services. Technologies like distributed tracing and service mesh enable end-to-end visibility, allowing teams to understand request flows, identify latency bottlenecks and troubleshoot issues across different service boundaries.
• Mainframe systems: Even in mainframe systems, observability plays a vital role. Monitoring tools and frameworks designed specifically for mainframes can capture metrics, transaction logs, and resource usage data. By leveraging observability in mainframes, organizations can gain insights into system performance, identify inefficiencies, and optimize resource allocation for critical business processes.

• Comprehensive system understanding: Observability provides a holistic view of the entire system stack, enabling teams to understand the interactions, dependencies and performance characteristics across different components and technologies.
• Faster troubleshooting and debugging: Observability data helps teams quickly identify and resolve issues by providing granular insights into system behavior, allowing for efficient troubleshooting and debugging.

• Proactive issue detection and prevention: With observability, organizations can detect anomalies, monitor key metrics and set up alerts to proactively identify and address potential issues—minimizing downtime and improving system reliability.
• Improved customer experience: By leveraging observability across all platforms, organizations can continuously monitor user interactions, identify performance bottlenecks and optimize the customer experience, leading to higher satisfaction and retention rates.

Overall, embracing observability universally empowers organizations to gain actionable insights, enhance system performance and deliver better experiences across diverse technology stacks and environments.

IBM’s observability solution, IBM Instana, is purpose-built for cloud-native and designed to automatically and continuously provide high-fidelity data—one-second granularity and end-to-end traces—with the context of logical and physical dependencies across mobile, web, applications and infrastructure.

If you want to enhance your observability practices with full-stack visibility and the ability to monitor your cloud dependencies in real-time, we invite you to request a demo.

Many customers have been able to achieve tangible results using IBM Instana. For example, Conrad Electronic offers global, multichannel sales of more than 450,000 components and devices, and it processes millions of updates and requests in real-time.

Keep an eye out for our upcoming eBooks that offer a downloadable compilation of observability insights that could significantly influence your next decision regarding enhancing or starting your observability.