Monitoring Vs Observability

Nowadays, modern applications are more complex, due to the need to monitor the various components of a distributed app. It has never been more apparent that modern applications require more inclusive debugging and diagnostics methods, particularly those that rely on distributed systems.

Modern applications can easily be deployed and managed using cloud and orchestration tools. When it comes to unpredictable failures, monitoring and testing have proven to be less effective than a combination of them in the past. Observability plays a key role here.

Based on the output of a system, observability deals with how well the state of the system can be understood. It is derived from control theory, which examines how well you can observe a system's output to infer its internal state.

Development teams still struggle to make a clear distinction between observability and monitoring since observability is so new. We explore observability and monitoring and provide insights into some tools that facilitate observability in this article.

Monitoring Systems
There are two key questions that need to be answered by a monitoring system and these are what is impacted and why it is impacted ?

There is a difference between a symptom and a cause. A symptom is what's broken, while a cause is what's causing the symptom.

Monitoring a distributed system with minimal noise and maximum signal requires a clear understanding of the distinction between the "what" and the "why". Utilizing a predefined set of metrics and logs, monitoring enables you to track and understand the state of your system. In order to detect known failures, we monitor applications.

The purpose of monitoring is to analyze long-term trends, to build dashboards, and to send alerts. App analytics give you an idea of how your apps are performing, how they’re growing, and how they’re being used. A system that uses monitoring and alerting can tell what is wrong or about to go wrong. Your app's behavior can be easily understood, problems can be detected, and issues can be corrected rapidly before consumers are affected.

Observability
An observable system is one that can be understood from its external outputs in order to determine its internal states. Observability is derived from control theory.

Logs, metrics, and traces are the three main pillars that make up observability.

In the sense that a system can be monitored if it is observable, one might think of observability as a superset of monitoring. Monitoring is aided by the insights that observability offers. Once a system is visible, monitoring is what you do. In the first place, monitoring is not possible without some degree of observability. 

You can move from causes to effects in a production system using an observable system. It is in a condition that makes it possible to comprehend and measure the internal workings of the system. What, where, and why are revealed by observability. 

Fig 1.2- Monitoring Vs Observability

Particularly if you're implementing cloud-based distributed architectures, like those frequently found with microservices and serverless architectures, observability will also help your team own the system and better understand how it operates in a real context.