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Home > IT Monitoring > Understand the differences between monitoring and observability
December 03, 2022
The complexity of modern systems and applications has increased considerably. The need for a method of debugging and diagnosing problems has never been greater, especially in distributed systems.
Historically, monitoring and testing have been used to deal with predictable failures. However, this approach is less practical with unpredictable failures. This is where observability comes into play, according to Thundra analysts. Observability has its roots in control theory, which addresses how well you can infer the internal state of a system by looking at its output.
As observability is still very new, the line dividing observability and monitoring seem blurred. Even more so with so many monitoring tools starting to include observability features.
Many define monitoring as an indispensable tool for building, operating and running systems.
In practice, monitoring allows you to observe and understand the state of your system using a predefined set of metrics and logs. Therefore, it should address two questions: What is broken and why? “What is broken” is about the symptom, while the “why” is about the cause of the problem. A good understanding of the distinctions between “what” and “why” allows you to effectively monitor a distributed system with minimal noise and maximum signal, explains Mark Burgess, in a book published by O’Reilly Media.
While it doesn’t make systems immune to failure, monitoring should provide a reasonably good view of system integrity. But being effective requires you to know what is expected and what metrics to track.
When monitoring is combined with alerts, your system can tell you what is broken or about to break. With this data, you can easily understand the behaviour of infrastructure and applications, detect problems and resolve them quickly before users are affected. Even if your monitoring data is not used directly to generate alerts, it should provide a snapshot of a system’s behaviour and performance through dashboards.
As monitoring can become complex, it is always good to design your monitoring system as simply as possible.
Observability, according to Cisco, is a process that uses software tools to detect problems by looking at the inputs (application and infrastructure) and outputs (business transactions, user experiences and application performance) of the technology stack.
Observability tools collect and analyse a broad spectrum of data, including application health and performance, business metrics such as conversion rates, user experience mapping, and infrastructure and network telemetry, to resolve issues before they affect business KPIs.
The demand for observability solutions is generated by several factors caused by the growing demand for digital services and the increasing complexity of IT systems and applications.
Those factors include:
It is gaining attention mainly because of its effectiveness in enabling developers to raise the Customer Experience level of their software, often affected by the increasing complexity of digital enterprises and the emergence of new technologies such as cloud-native, DevOps, microservices, containers and virtualization.
When you apply observability, the benefits to your business are immense: faster innovation and implementation, less sluggishness, reduced costs and a better understanding of how to prioritise your time and attention within applications.
Metrics, events, tracking and logs are essential data for observability. They are analyzed to produce insights to understand and interpret errors so that intelligence can be triggered more quickly. Once this data is aggregated, it manages and monitors suspicious activity.
Often observability provides insights that help in monitoring.
It is useless to conceptualize the relationship between observability and monitoring as “observability versus monitoring”. Observability does not replace monitoring and does not eliminate the need for monitoring. Observability and monitoring are complementary.
Although they serve different purposes, increasingly, the two are beginning to be seen as symbiotic rather than mutually exclusive. Working together, they are more efficient.
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