Observability Vs Monitoring

The past few years have seen an increased reliance on distributed architectures by businesses the world over. This has made observability and monitoring very important especially when it comes to the success of these architectures.

Businesses need to identify any issues and understand what could be wrong with their architectures before their operations are negatively affected. Observability and monitoring provide them with one of the best solutions.

However, there is a thin line between observability and monitoring and most development teams do not know the differences between the two. 

Let us explore the differences and the relationship between the two.

What is Observability?

Observability is used to measure the internal state of a system through analysis of data generated through traces, metrics, and logs. It helps businesses in analyzing different processes in multi-cloud environments for them to detect and solve any underlying issues.

It uses different tools and instruments to provide businesses with insights that help with monitoring. This means that observability aids the process of monitoring. Without observability, monitoring would be very difficult.

An observable infrastructure allows businesses to measure and understand the internal operations of the infrastructure. This is important when it comes to navigating from the causes of conflicts or errors to solutions without any problems.

With observability, businesses can answer questions such as the services that requests go through and their performance, reasons for failed requests, how requests are processed, and how processes differ from the expected behavior of their systems.

Observability can be categorized into three;

  • Traces

Traces are used to provide insights into operations performance across different microservices. Applications depend on different services. These services come with their sets of logs and metrics. 

Traces allow businesses to observe requests through cloud environments. They also provide businesses with a full-stack data correlation solution that eases hybrid cloud observability.

  • Metrics

Metrics can be defined as the measurements and counts that businesses aggregate over time. These counts are the foundations needed for monitoring. Metrics allow businesses access to information such as the memory used by an instance or a method and the number of requests handled by a service every second, among others.

  • Logs

Logs are time-stamped records of events that are used when identifying issues in a system. They provide insights into things that might have changed the expected behavior of the system. 

Logs should be ingested in a structured manner and using a format that makes it easy for log visualization. One of the most common formats is JSON.

What is Monitoring?

Monitoring can be defined as the process of collecting and analyzing data related to the performance of an application. The collected data is then used to track the progress of the program to ensure that it reaches its objectives.

Businesses look at specific metrics when monitoring applications. When a business adopts a DataOps mindset, it first decomposes its existing applications into microservices. This allows them to reduce management and repair time and gain operability.

However, their systems might get more complex with time. When this happens, they have to ensure that they have visibility into any system failures for them to address them effectively and within time. This can be done through monitoring.

A monitoring system should provide businesses with answers to what is not working as expected and why. It should allow them to not only watch but also understand the state of their systems using the right logs and metrics.

Monitoring plays an important role when businesses are analyzing their long-term trends, creating alerting systems, and building dashboards. It provides insights into the performance of applications, their growth, and how they are used. 

Unfortunately, complex distributed systems pose a challenge with regard to monitoring because of non-linear production failures that are not easy to predict.

How Do Observability and Monitoring Relate?

Even though monitoring and observability compliment one another, they handle different functions to ensure that architectures meet their expectations. While monitoring lets businesses know when there are issues, observability lets them understand the root cause of the issues.

In addition, monitoring can be viewed as a part and parcel of observability. This is because businesses cannot monitor a system that is not observable.

Businesses use monitoring to track the health of their architectures. They can collect data on system performance with regard to bottlenecks, downtime, connectivity, and access speeds.

On the other hand, they use observability to get answers to questions such as why the architecture does not meet their expectations and what causes issues leading to poor performance.

Businesses need to make sure that their development teams understand the differences between observability and monitoring. This will help them implement the right measures to ensure that their system architectures meet their expectations.