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A Differential Site Reliability Engineering Guide - Observability Vs Monitoring

By Team Srijan May 18, 2023
A Differential Site Reliability Engineering Guide - Observability Vs Monitoring
A Differential Site Reliability Engineering Guide - Observability Vs Monitoring

“Flexibility is the key to stability.”

— John Wooden

Although quoted by a prominent sports personality, this quote holds true even in the technology space with scalability in perspective. Modern applications use distributed and service-oriented architectures that resolve legacy software issues like scalability, security, maintenance, compliance, etc. However, it does not guarantee a reliable, resilient, or high-performance application. This is where Site Reliability Engineering (SRE) comes into the picture.

When implementing SRE, it is essential that businesses identify the processes within this practice and understand what complements their needs. Observability and monitoring are two such processes in this context. 

In this blog, we dive deeper to understand how these complementary SRE capabilities play crucial roles in maintaining application health and are used in tandem with one another.

Walls May Not Speak, But Your System Does! Hence, Monitoring.

Monitoring involves the use of tools that aggregate, correlate, and analyze data from the hardware and network they run on, to effectively monitor, troubleshoot, and debug apps. In simpler terms, monitoring measures the health of apps by tracking particular metrics. It collates info, enables teams to build dashboards, analyze long-term trends, and map how exactly apps function using a predetermined set of metrics and logs. Teams can detect and solve errors by tracking known metrics. 

However, monitoring covers only one facet of application health. It may not be sufficient to diagnose errors across complex distributed apps. By nature, it only dispenses data relating to the behavior and performance of your system and highlights any system failures while suggesting a consequent fix. It gives low to no end-to-end visibility on what’s happening in an ever-expanding IT environment.

Observability, on the other hand, enables DevOps and SRE teams with end-to-end ability to monitor multi-layered IT architectures using metrics of latency, traffic, errors and saturation thereby leveraging SRE tools for efficient management and troubleshooting.

Let’s dig a little deeper.

Observability - Take A Step Back To Paint The Big Picture!

When R. Kalman introduced observability, he interlinked it with the study of control systems and stated observability as a practice that examines the internal state of a system from the knowledge of its output. Hence, given the assumption that distributed infrastructure components are spread across abstraction layers, observability is perfectly suited for the needs of enterprises with complex & interconnected IT systems. 

It is divided into 3 basic pillars: 

  • Logs - Files that are recorded events within an environment, that include contextual information to describe when an event has occurred. Irrespective of how logging data is stored, it is aggregated and analyzed collectively by observability tools.
  • Metrics - Observability utilizes metrics to map the performance of apps or infrastructure. Depending on user intent, metrics can be used to trace latency, traffic, and errors.
  • Distributed tracing - By tracking parts of an application, distributed trace records when a component processes the request received by the previous one before passing it to the next component. Traces can well identify which parts of an app trigger an error.

In a bigger context, observability enables IT teams to not only gain deeper insights into the health of applications but also into how resources are utilized within the infrastructure and ways in which uptime can be improved via upgraded performance.

Observability v/s Monitoring: The Key Differentiation

Monitoring predominantly measures the defined metrics using dashboards designed by teams. By contrast, observability is about consuming every facet of data collected from logs, metrics, and tracing using observability tools. Thus, monitoring is reactive while observability is proactive. Since monitoring displays predetermined data to diagnose system anomalies, it cannot pinpoint the underlying issue. With observability on the other hand, teams are able to comprehensively assess, provide granular insights and troubleshoot to debug an issue at hand.




Proactive actions

Reactive actions 

Why? How?

What? When?

Full stack monitoring

Component monitoring 

Integrated Data

Scattered Data


Where monitoring aims to identify what a problem in an application is, observability as a practice can get to the root cause of the problem and identify how, what, and why something has occurred. It “observes” the internal state of a system based solely on its external output and helps IT teams accurately diagnose and navigate from performance issues to its root causes, without additional testing or coding.

Observability, thus, plays a crucial role in IT infrastructure.


There is much more to observability and monitoring than what meets the eye. Implementation of either will greatly depend on the use case for each as well as the intent of their use. An organization may use monitoring to assess some workloads whereas it may consider observability as a solution for other system analysis. 

If you are facing performance bottlenecks, Srijan can provide a thorough assessment of your application including highlighting areas of impact and shed light on the right solution for you. We'll be happy to guide you with site reliability engineering services that are customized exclusively for your business!

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