Monitoring and Observability - What’s the Difference?

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As applications and organizations grow larger, the need for observability and monitoring becomes increasingly important. Although developers sometimes use these terms interchangeably, there is a difference between them. Let's start by defining each term.

What do we mean by monitoring?

Monitoring involves examining patterns over time and triggering alerts. This practice provides insights into the operational state, growth trajectory, and usage patterns of your applications. However, the challenge arises when monitoring complex distributed applications. They become increasingly intricate and non-linear, making debugging a requirement.

What do we mean by observability?

Observability involves the ability to understand and gather information, which is then used to monitor, troubleshoot, and debug the application. The information obtained from observability is also used to understand how changes to the code and infrastructure impact behavior and user experience.

What is the difference between monitoring and observability? Which is better?

Monitoring is a crucial step in the observability process. It can be considered as the first phase, where you gather data and keep an eye on your distributed system. However, observability encompasses more than just monitoring an application, especially when you encounter production issues that need to be resolved.

When organizations start with microservices, they may choose to begin with the monitoring step. However, starting with observability provides the advantage of gathering insights on your entire stack, as explained in What Is Full-Stack Observability?.

Traditionally, monitoring has been effective when we can anticipate the ways in which systems might fail. However, as applications grow more intricate, the ability to run specific queries across multiple systems with distributed tracing becomes more valuable. Predicting failure scenarios in the context of distributed applications often proves elusive. A transformative solution is transitioning a system into an observable state. This paradigm shift provides access to the system's internal state, enabling the identification of bugs and offering insights into the underlying causes of problems.

Observability is a powerful approach that enables teams to understand the impact of changes to application code and infrastructure on the user experience. By combining data streams from various sources like log files, traces, and metrics, teams can comprehensively monitor user interactions, identify performance bottlenecks, and uncover glitches in the user interface. This expedites the process of recognizing and resolving issues that could potentially harm the quality of the user experience.

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