The capacity to see what’s happening within your application is known as observability. It’s not just about monitoring logs; it’s also about understanding application health and how your users interact with your app.

To ensure you’re building a genuinely observable system, you must focus on three key areas: metrics, logs, and traces.

These three core pillars will help you build a system that’s both flexible and scalable.

We’ll detail these three pillars and explain how each helps you achieve observability.

History of Observability

Observability is a traditional concept. Back in the 1950s, researchers observed systems to see how they worked.

They did this by analyzing what happened when you changed one part of the system.

In the 1990s, observability became very popular among software developers who didn’t want to write code anymore. They preferred to dedicate their time to writing features instead. However, there was a problem: most people had no idea if their application was functioning correctly.

So they asked themselves, “How do I ensure my application works?” And the answer was, “I’ll just look at it!”

There are different ways to define observability. For example, some say you’re observable if you can figure out why something went wrong. Others say that you’re observable when you understand what’s happening inside your application.

Still, others say you’re observable whenever you can tell whether something is working correctly.

But there’s another important distinction. You can collect lots of information about your application. But it doesn’t matter much if you can’t use that information to improve your application and enhance the customer experience.

What Is Observability?

Observability refers to monitoring and analyzing data streams, such as network traffic, application logs, and metrics, to identify critical issues early and proactively.

Doing this allows companies to avoid production issues and improve performance.

An observability solution is typically composed of multiple tools. Each tool performs one component of the overall process.

For example, collecting data might involve using a packet sniffer like Wireshark, while analyzing it could use something like Splunk.

Observability helps you understand what’s happening inside your system, whether it’s a web server, mobile app, or software. This includes knowing what happens during regular operations and when something goes wrong.

For example, you might want to know if a request takes too long to process or if a customer gets stuck in a loop while trying to reach your site.

The Three Pillars of Observability

There are three core pillars of observability: metrics, logs, and tracing.

These three components provide different types of insight into system behavior. Each plays a role in building a complete picture of what’s happening inside your application.

Each pillar offers unique benefits, but together, they form a robust set of tools for monitoring and troubleshooting.


Metrics is where the rubber hits the road. You can use it to measure how well your site is performing and whether it’s meeting your goals. But application metrics aren’t just numbers; they show what’s happening inside your system.

For example, they can tell you if there are any critical issues with your server or if visitors are clicking on your ads. And they can even help you find out why people aren’t buying.

Metrics come in a wide variety, with each measuring something slightly different. For example, you might want to know how much traffic you’re getting, how long people spend on your site, and how often they return.

Or maybe you’re curious about the ratio of people who clicked on your ad to those who didn’t.

The good news is that most web analytics tools provide multiple data views. So, while you might start with a single set of metrics, you can always add others later.


Logs are an essential part of any monitoring system. They serve as a source of knowledge about what is happening in your environment.

Logging records events that occur during runtime, including crashes and other unexpected behavior Logs allow developers to correlate problems with specific lines of code. When combined with metric code. After identifying the type of log file you want, you can start looking for clues in the data.

For example, if you see an error in one of your logs, you can try to figure out why it occurred. This could mean finding the source code that caused the error or figuring out what went wrong.

Distributed traces

Distributed tracing is used to monitor how software executes. This type of tracing allows you to see what happens inside each part of your application, including the database, web servers, and even the operating system.

With this information, you can identify potential performance issues and make changes to improve overall app performance. In addition, you can use application traces to troubleshoot problems and optimize your infrastructure.

There are several ways to distribute tracing across multiple machines. For example, you could run different versions of the same binary on separate nodes or deploy a single version of the binary to many hosts. In both cases, you can collect data about the execution of the binary and correlate it with the source code.

Tracing is typically performed manually, but there are some automated tools available to help gather and analyze distributed traces.

These tools visualize the collected data and allow you to drill down into specific events. Some tools even let you generate reports based on the collected data.

What Is Full-Stack Observability?

Full-Stack observability refers to capturing all three pillars of observability. First, this lets users understand how their software runs inside production, capturing performance and operational information about your application.

Several tools available today allow developers to capture metrics and logs while running applications in production.

These tools collect data from various components within the stack, including databases, servers, web services, and APIs.

Using an Observability Platform

An observability platform collects information about your application and presents it in a single place.

You can monitor how things are operating and resolve issues quickly with the use of observability tools.

A full-stack observability platform combines several tools into one easy-to-use interface. These include metrics collection, monitoring, alerting, logging, tracing, profiling, and performance analysis.

OpenTelemetry is one of the leading open source observability platforms available today. It provides detailed metrics about your application, including performance, errors, exceptions, and more. In addition, it’s compatible with.NET and Java programs.

You can also use OpenTelemetry to create custom dashboards and integrations with other tools like Prometheus, Grafana, and InfluxDB.


Observability metrics, tracing, and logging systems are critical for building high availability systems. They allow us to monitor our application components’ behavior and application health.

Application performance monitoring enables us to detect problems early and prevent failures.

People Also Ask

What are the three pillars of observability?

Observability is the ability to see everything that happens within your system. Metrics, logging, and tracing make up the three pillars of observability.

Metrics are data points that tell us what happened inside our systems. These include page views, number of visitors, and clickthrough rates.

Logging is the process of recording events that happen in your system. These could be anything from database queries to file uploads.

Tracing is the method used to track down the line of code that caused a specific event. This includes debugging, reverse engineering, and analyzing log files.

The three pillars of observability are closely related, and together they form the backbone of any modern software development effort.

Without them, we’d never be able to understand what happened in our system, and we wouldn’t be able to fix problems quickly. We’d also miss the opportunity to improve our processes and reduce errors.

What is the OpenTelemetry standard?

OpenTelemetry is an open, vendor-agnostic standard for gathering telemetry data about software and the systems that run it.

It was established in May 2019 as a merger of the OpenCensus and OpenTracing projects. It has since been promoted to the status of a Cloud Native Computing Foundation incubation project.

What is OpenTelemetry instrumentation?

OpenTelemetry provides code instrumentation for various languages, enabling automatic and manual application instrumentation.

Instrumentation libraries provide a central repository for each language. They may or may not provide extra repositories for non-core components or autonomous instrumentation.

The precise installation process for OpenTelemetry differs depending on your programming language.

Why is OpenTelemetry important?

By enabling developers to see what happens under the hood, they can gain insight into performance bottlenecks and bugs.

OpenTelemetry collects data from many sources, such as network traces, CPU usage, memory consumption, and disk I/O, using data points to generate reports and visualizations.

These reports and visualizations give developers a deeper understanding of how their application behaves under load.

OpenTelemetry is especially valuable for mobile apps since they tend to run on constrained hardware resources.

OpenTelemetry enables developers to collect and analyze data from multiple devices running the same app, giving them insights into how their app performs on different hardware configurations.

This enables developers to fix problems faster and improve application performance.