In today's complex, multi-cloud environments, IT and engineering teams are under increasing pressure to respond to errors affecting their entire system. Therefore, IT operations, DevOps, and SRE teams are all striving to gain complete observability across these increasingly complex and diverse computing environments.
But what exactly does observability mean? Are there tangible benefits for organisations that can be achieved through implementing it, and why is it so critical to preventing system failure?
In this article, we will explore all of these points and more to help you understand why observability should be something you strive to achieve in your organisation.
What Is Observability?
In many cases, observability is said to be a property of a system. Observability can be defined as how readily a given system or subsystem can be observed. As a system's complexity increases, it may become less easily observable. Observability helps your teams focus on what really matters in a constantly changing environment and improves the signal-to-noise ratio in monitoring.
In other words, observability determines how well we can deduce a system's internal state from its external outputs. In essence, this means that if a system is highly observable, we can reliably infer its internal state by monitoring its external output.
In addition to log data, metrics, traces, and events, these external outputs may be created in a variety of formats (such as time-series data). An application that has sufficient observability should result in all failures within the application being contextualised enough that analysis and troubleshooting can be undertaken. This should greatly aid in the process of resolving system failures, among other issues.
For further insights, the importance of building systems so that they are observable was discussed in extensive detail by Bryan Cantrill (formerly of Sun Microsystems) back in 2006.
What Does Observability Mean For DevOps & SRE?
Observability must be understood in the context of other modern practices such as DevOps, site reliability engineering (SRE), and cloud-native innovation. As these movements have grown, observability has been emphasized and designed into their practices.
Observability is a key component of DevOps, SRE, and cloud-native movements. The property of observability is similar to that of testability in that it improves our understanding of technical systems. Observability and testability should be understood that they are not one-time additions, nor can they be achieved with a one-size-fits-all solution.
What Are The Differences Between Monitoring & Observability?
In software engineering, monitoring and observability are often considered synonymous. Thought leaders in this field played a critical role in the rise of observability as a term. Nevertheless, to a typical software engineer, monitoring well means monitoring everything.
Whatever the terminology used to describe this activity, watching, alerting, and observing your systems should be standard practice within your organisation. Monitoring and observability are essential for an application delivery ecosystem to function properly.
It is possible to view monitoring as incompletely implemented observability. Observability requires the ability to reconstruct exactly what happened during an incident.
Further discussion of this topic can be found here Observability vs monitoring .
How Do You Implement Observability?
There have been a number of observability platforms developed in recent years, most notably those that enable cloud observability, like Logit.io, which has grown fast in recent years. To implement observability into your service, you will need a combination of specialist tools and a mindset that fosters cross-team collaboration and eliminates the existence of data silos.
Examples of key observability metrics to be monitored can include measuring total application requests, the count of total microservice instances, the request duration for each service as well as CI/CD pipeline metrics. Across operations and development teams, event logs are considered to be a rich source of distributed system observability and performance data.
What Are Some Examples Of Observability Platforms?
Some of the most commonly used observability tools include Dynatrace, New Relic, Splunk & Logit.io, to name a few. Specifically, Appdynamics position itself as an application observability provider, but many of the previously mentioned providers also extend their services in order to provide this capability to their customers as well.