Observability vs. Monitoring: Differences, Significance, and Solution

The modern age of mobile experiences needs high-performance applications and systems with minimal downtimes. Having more uptime is key, and that’s why you need appropriate monitoring and observability tools.

The terms may sound similar but are hardly the same. While observability is seeing the big picture, monitoring is the quantitative approach of aggregating metrics. Both are essential for your system’s performance.

However, both monitoring and observability need aggregation, analysis and processing of key data related to metrics or events. According to an IDG survey, data volumes are growing at an alarming rate of 63% per month. So, you need a reliable solution for enhanced controllability and observability of systems.

Another aspect of understanding the difference between observability and monitoring is to customize your solution accordingly. For example, monitoring focuses on events while observability tracks data on a macroscopic level through the system’s output.

What is Observability?

Observability has recently become popular in IT and cloud computing. This concept is driven by control systems engineering. It is defined as the measurement of the system’s internal states determining the outputs in control system engineering.

Any system is observable only if the system’s present state can be defined through outputs in a specific period. So, the result of the function matters here. Every activity and behavior of the system is evaluated based on the output it produces. Similarly, if the output cannot convey the system’s behavior, it is deemed unobservable.

IT infrastructure and cloud-based applications record each activity and keep logs. Such records have information on applications, systems, servers, security, and other components. Therefore, the observability of an IT infrastructure depends on monitoring and analysis of key events recorded through these logs.

Apart from the events, monitoring key metrics and data from different components can offer actionable insights into the system’s behavior. In addition, organizations can leverage tools that offer controllability and observability of event logs for enhanced performance of their systems.

What is Monitoring?

Monitoring is a vigilant activity of tracking, analyzing, and recording significant events related to different components of an application. Modern app development processes have seamlessly integrated the service-based architecture to reduce repair time in case of incidents. They deploy concurrent services for higher availability.

While this is a great approach to overcome any shortcomings in terms of uptime, it becomes difficult to sustain the same efficiency as the application scales. Furthermore, due to higher scaling and integrations of several functions, application architecture becomes complex. So, several components need monitoring to ensure uniform performance.

As Google states, you need answers to simple questions like what is broken and why from your monitoring systems. Every monitoring system allows higher visibility to the system’s states through predefined metrics comparable to standards. Apart from the metrics, it also allows you to understand the root cause of system failure.

Monitoring Vs. Observability – Key Differences

When it comes to discussing observability vs. monitoring, it is the difference between seeing something and acting to achieve it. Any component is observable when the system offers data from within, while monitoring deals with the extraction of information from different resources across systems. However, you need to follow up on observability and monitoring activities without which both the processes are pointless.

If you consider the pyramid of robust application performance analysis, observability and monitoring are the pillars that together provide actionable intelligence. However, it is essential to understand that you can leverage one pillar for another to complete the process of controllability and observability.

For example, you can use a synthetic monitoring approach to extract data for an unobservable system or component. So, when you think of the entire observability vs. monitoring aspect of cloud assessments, it can be interoperable in specific use cases.

ObservabilityMonitoring
The data is offered within the system through outputInformation is extracted from event logs and records
Needs more experienced and skilled professionals for the execution of observabilityNeeds reliable monitoring tool for extraction, analysis, and processing of data
If output data fails to determine the behavior of the system, it is unobservableAny system can be monitored that has event records of logs
It relies on the output data rather than eventsIt relies on events rather than event logs or output data

Observability in DevOps

Imagine finding a needle in the haystack! That’s where the real difference between observability vs. monitoring comes into the picture. Monitoring is your go-to approach when looking closely at a microscopic level, like finding a needle in the haystack.

But, for a macroscopic overview, observability is the key in DevOps. Observability in DevOps offers the ability to formulate an overview of the system performance and health through the key metrics sourced by monitoring activities.

There are three significant components of observability in DevOps,

1. Logging– It records all the incidents that teams can leverage to 

  • learn important information on previous events, and 
  • accelerate the search for the leading cause of an error.

2. Tracing- It is an essential part of observability. Tracing establishes the relationship between the reason for errors and its impact. These traces are visualized through waterfall graphs to better understand different aspects like the time needed to trace the system.

3. Metrics- These are the quantitative data points that determine the pattern of errors and other such systems’ behavior over a period.

Observability offers a complete overview of the system along with actionable insights that help in data-driven decision-making. However, you need a reliable solution for efficient observability, and that is where Cloudlytics can help.

How Cloudlytics acts as a tool for observability?

Cloudlytics is the one-stop solution for all your observability needs without the hassle of relying on output data to determine the system’s behavior. It employs two intelligent tools to offer excellent observability.

The first is event analytics that enables monitoring and analysis of several system events. The second is an AI-based cloud intelligence engine that enables a complete overview of the system through more innovative and actionable insights.

Together they form an intelligent observability tool that enables,

  • System monitoring
  • Event tracing
  • Logging
  • Graphical overview
  • Data-driven insights

Conclusion

With the rapid adoption of cloud computing across business domains, the need for better controllability and observability will increase. First, however, you need to understand the difference between observability vs. monitoring to design an effective and efficient system for your business. The best way is to choose an intelligent observability tool from a monitoring solution provider like Cloudlytics and achieve optimal results.

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ABOUT THE AUTHOR

Varoon Rajani

Varoon Rajani

Varoon Rajani is the co-founder & CEO at Blazeclan and Cloudlytics. Varoon spotted the cloud opportunity early on and since then, built a born-in-the-cloud, global organization that delivers full-stack cloud solutions. He is excited by the dynamism offered by cloud technologies, is obsessed with customer success, and is deeply passionate about innovation.

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