Data Center

Monitoring Vs Observability: Why Observability is Better

Updated: May 03, 2024

Monitoring Vs Observability: Why Observability is Better
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Monitoring & Observability are most often used interchangeably. But both these IT terms are different. To understand the difference better, let’s first know them.

 

Understanding the Capabilities Monitoring 

Monitoring allows you to rectify an issue after it happens. These systems are built to detect and caution you about problems in your system or processes after reaching a predefined threshold. Monitoring can also be termed reactive; this is because it involves placing thresholds or alerts that are determined based on predefined conditions. Once those conditions are fulfilled or exceeded, these systems react by activating alerts or notifications. Hence, these focus on responding to the set patterns or deviations from expected standards. 

 

Observability 

Observability monitors system behaviour in real time to identify early signs of potential challenges before reaching the escalation. Where monitoring reacts to predefined conditions, observability offers a comprehensive viewpoint of system performance in real time. Observability allows proactive problem-solving by recognising potential threats before they happen. It involves accumulating and examining diverse data sources, including logs, metrics, traces, and events, to gain insight disclosing how different system components work together.

 

Use Cases: Monitoring v/s Observability

Let's understand the difference between monitoring and observability with a use-case example: 

Monitoring Use-Case: 

Suppose you're operating a manufacturing plant that builds electronic devices, and your primary objective is to ensure minimum downtime and smooth production. You continuously keep track of metrics that include defect rates, throughput, and machine uptime. For collecting real-time data on machinery performance, you use installed sensors and IoT devices.  

In case someday a machine encounters a breakdown situation and deviates from its normal operating parameters then a monitoring system will trigger an alert, alarming your maintenance team to take quick action to resolve the issues. 

 

Observability Use-Case: 

Now, let's understand observability in the context of the same manufacturing facility. Observability includes obtaining insights into the complete production ecosystem involving factors beyond the standard metrics. You collect the machine data and also other information on material quality, operator behaviour and environmental conditions. After this, you attain a holistic view of the entire manufacturing process from the varied-sourced integrating data. If someday the defect rate starts increasing for a particular electronic product, then observability will help you trace the defect's origin point. This is possible via insights like material supply chain data, operator inputs, and examining machine logs. 

 

Summary

Often observability and monitoring work in unison. However, when you are required to choose a fitting tool that supports your team, you can get confused between monitoring and observability.  

Observability is crucial for developers to perform root cause analysis and system debugging. Its user-friendliness is an additional point that often makes it a go-to option. If your priority is easy process analysis, you can reach out to professional integrators like Proactive Data Systems, offering custom observability options.

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