Observability vs. Monitoring: Understanding the Differences

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This post was written by Siddhant Varma. Scroll down to read the author’s bio.


Software development isn’t just about building and deploying software. There’s a wide range of operations and activities you need to tackle even after you’ve successfully deployed it. The two most common are observability and monitoring. While they’re similar in a lot of ways, it’s important to understand that they are not exactly the same, and each has its own purpose.

In this post, I’ll help you understand the differences between observability and monitoring.

What is observability?

To begin with, let’s first make sure you understand what observability is. It’s the ability to understand how your system is behaving at any given moment by collecting various data points pertaining to your system’s behavior from a number of sources. It’s usually used for systems that are fairly complex, such as distributed systems or microservices architecture.

In order to measure observability, you need to look at the output the system generates. Then you’ll need to collect some data points based on that output. These data points commonly include metrics, logs, and traces. Finally, you need to analyze and process these data points to deduce the internal state or the behavior of your system.

Metrics, logs, and traces

Metrics are the quantitative data about your system. Network latency, throughput, error rate, etc. are some examples of metrics.

Logs are records of events that occurred in the system. For instance, an application log will give you details or descriptions of events pertaining to an application, such as when a user authenticated to your system, when they made a write query to your database, etc.

Finally, traces are data about the inflow and outflow of requests through the system. For instance, network traces will measure all the incoming and outgoing network requests and give you details about things such as packet loss, bandwidth consumption, etc.

What is monitoring?

Monitoring is the process of periodically observing your system and collecting and analyzing certain data points that indicate how the system is functioning. Such data points usually include CPU usage, memory usage, network traffic, and error rates. These data points help you know if the system is strong enough to function without any anomalies or if there are potential issues that need to be diagnosed and dealt with.

Monitoring helps you determine the reliability and availability of your system. It can help you instantly detect and fix issues that can impact your end users directly. You can also use monitoring to collect more data about your system over time. This can help you analyze patterns that might lead to a complete system failure or outage.

Observability vs monitoring: key differences

Now that you understand what observability and monitoring mean, let’s look at the differences between them. We’ll compare them on the basis of scope, timeframe, proactivity, and granularity.


Scope defines the range over which observability and monitoring spreads. When we talk about scope, we mean how far along the system, from a few metrics to all, these concepts cover.

Observability gives you insights about the internal state of a system based on external output. That means the whole system is the scope because you’re trying to understand how the system behaves or performs as a whole. On the other hand, monitoring focuses on only certain metrics. For instance, when you measure CPU utilization or memory usage, you’re only measuring the overall performance of the system. That means that in monitoring the scope is strictly limited to performance indicators.


You know that monitoring helps you collect data that you can analyze over periods of time to form patterns. Hence, monitoring’s timeframe is longer since you’re gathering data over a period of time.

Observability on the other hand, only shows you the current state of the system. Data collected from observability only pertains to how the system is behaving at that moment.


Since observability is used to analyze the present state of the system with the entire system as its scope, it’s a proactive process. Developers or reliability engineers have to be more proactive when they’re analyzing the observability of the system. This can help them anticipate and prevent errors and issues before they occur.

On the other hand, monitoring is more reactive. It’s about knowing when an issue has already occurred and alerting the engineers and developers so they can take action.


While you collect data in both observability and monitoring, the granularity of the data differs vastly. Since observability deals with the present system and aims to avoid issues and errors in the future, it’s geared toward collecting more granular data. For instance, a network trace in observability gives you details about any packet loss in network requests.

Monitoring, on the other hand, focuses on high-level metrics, which means the data is less granular than observability data. For instance, monitoring a network request will give you data about the traffic obtained on the network and won’t give you any finer details such as bandwidth consumption or packet loss.

Summing up the differences

To sum up, observability is best used when you want to get a deeper insight into the inner workings of your entire system in the current scenario. This includes your application as a whole, its performance, the network behavior, its communication with other applications, its infrastructure, etc. Observability will help you answer complex questions pertaining to specific events or behaviors about your system.

On the other hand, monitoring tracks performance metrics over time, and you can use that data to optimize your system for the future. Monitoring is used reactively by engineers to ensure that the system is performing as expected so they can address any issues or potential bottlenecks as they occur.

The relationship between observability and monitoring

Now that you understand how these concepts differ, we can dig a little deeper into the relationship between them. You’ve already seen that observability is concerned with the system as a whole, whereas monitoring only focuses on certain aspects of the system, such as performance.

If your system has any immediate problems that are happening in the present, observability will help you detect them. Meanwhile, monitoring will help you detect bottlenecks and other historical problems that are ongoing. However, after monitoring the system and knowing what to watch out for, you can see whether or not the recurring issues are flaring up in real-time using observability.

It’s important to understand that both are absolutely essential. Each helps you ensure that your system is performing and functioning as intended. You can also use these processes to understand your system better and optimize it for the future.

Striking the right balance

As a reliability engineer or a developer, you need to strike the right balance between the two. Focusing only on monitoring will give you a narrow view of the system, and detecting present issues might become challenging. On the other hand, focusing too much on observability might overwhelm you with information overload.

Both observability and monitoring are designed to achieve different goals. You need to prioritize them according to the goal you wish to achieve. If you want to understand and analyze your system’s behavior in real-time to get a bigger picture, focus on observability. If you need to diagnose issues via metrics and alerts, focus on monitoring.

About the author

Siddhant is a full stack JavaScript developer with expertise in frontend engineering. He’s worked with scaling multiple startups in India and has experience building products in the Ed-Tech and healthcare industries. Siddhant has a passion for teaching and a knack for writing. He’s also taught programming to many graduates, helping them become better future developers.