Understanding Observability and Monitoring

In today’s tech landscape, Observability and Monitoring stand as pillars of operational excellence.
Observability provides profound insights into a system’s intricacies while Monitoring acts as a vigilant guardian over predefined metrics. Together, they create a symbiotic duo, fortifying organizations against downtime and bottlenecks.

In our recent internal workshop, our colleague Ajdin Baručija delved into this intriguing topic, and we’re excited to share key insights with you. Join us on a journey as we decode the essence of Observability and Monitoring — the heartbeat of a resilient technological ecosystem.

What is Observability?

Observability gives engineers a proactive approach to analyzing and optimizing their systems based on the data they generate. Observability platforms provide a centralized way to collect, store, analyze, and visualize logs, metrics, and traces to provide a connected real-time view of all the operational data in your software system, as well as the flexibility to ask questions about your applications and infrastructure to understand system behavior and get to the answers you need to improve system performance.

A simple way of describing observability is how well you can understand the system from the output. In control theory, observability is defined as how engineers can infer the internal states of a system from knowledge of that system’s external outputs.

Expanded to IT, software, and cloud computing, observability is how engineers can understand the current state of a system from the data it generates. To fully understand, you’ve got to proactively collect the right data, and then visualize it and apply intelligence.

What is Monitoring?

Monitoring is a process to periodically collect, analyze, and use the information to actively manage performance, maximize positive impacts, and minimize the risk of adverse impacts. It is an important part of effective management because it can provide early and ongoing information to help shape implementation in advance of evaluations.

Observability vs. Monitoring: What Is the Difference?

Monitoring and observability are related concepts in that they help software engineers understand the behavior of their IT environments. However, there is one major difference between them.

Monitoring will usually concern capturing metrics related to the current health and performance of systems, while observability includes all facets of an application’s performance, such as logs, metrics, events, and traces.

Monitoring tools use dashboards to capture and display predetermined data that helps DevOps and other IT teams detect potential problems and long-term performance trends. However, while monitoring notifies DevOps teams of operational issues using alerts, it may not pinpoint the individual component or underlying reason behind the issue, especially in a highly complex distributed system.

On the other hand, observability software provides insights and comprehensively assesses the entire IT environment using data gathered from each internal system, including metrics like memory usage, bandwidth utilization, response time, requests per minute, or uptime, as well as logs of recorded events, and traces for transactions. This granular and contextual insight it provides can help teams understand, identify, and troubleshoot the root cause of issues across the IT infrastructure. Thus, it acts as a knowledge base for engineers to define what they want to monitor and how to improve performance.

What Are the Similarities?

Fundamentally, observability and monitoring use the same type of telemetry data. These are additionally referred to as the “three pillars of observability “, which are:

• Logs are application and system records of events in your software. It also provides context and details on how an issue impacted the system.
• Metrics give a numerical assessment of the system’s performance and resource utilization. This assessment can show the difference between past and current values (delta metrics) within a specific period (gauge metrics) or changes over time (cumulative metrics).
• Traces show how operations move throughout distributed cloud environments. Thus, it contextualizes troubleshooting to specific user actions or service relationships.

The similarity between observability and monitoring lies in their end goal, which is to get insight into the infrastructure of your complex distributed systems and deliver a great user experience.

The Relationship Between Observability and Monitoring

Monitoring notifies teams of issues to address issues before they escalate using telemetry data and alerts. However, to prevent recurrences of the same issue, in-depth analysis, and pinpointing of the underlying cause of the issue are needed. This can only be provided by observability.

Let’s paint a scenario.

Memory, CPU utilization rates, and cache hit ratio are often tracked when monitoring a database. Thus, alerts are usually set on them to ensure they don’t exceed the threshold. An alert stating that the CPU utilization has increased or that the cache hit ratio has decreased could be a sign of a poorly written or optimization query. However, an observability tool would need to be utilized for you to be sure.

Monitoring complex distributed applications is much more than this conventional database performance use case. It is also much harder to debug. Thus, the bottom line of the observability vs. monitoring dilemma is that pairing the two approaches is essential to address issues more efficiently and promptly. By doing this, teams will be able to know the occurrence, understand the context, and provide answers to what, how, and why of today’s distributed multi-cloud microservice architectures with multiple dependencies and shifting complexities.

Observability or Monitoring: Which One Is Better?

While they share similarities and differences, it isn’t a monitoring vs. observability situation. You should instead think of them as complementary strategies that help you efficiently achieve your goal — understanding your system better.

Although monitoring helps one track what’s happening within the environment, observability is necessary for any contextualized analysis of your infrastructure landscape. On the other hand, the opposite is also true. Monitoring is necessary for observability and, thus, is a prerequisite. This is because you cannot observe an unmonitored system.

Both approaches are, therefore, essential to get meaningful insight into today’s complex IT systems.

In conclusion, the symbiotic relationship between Observability and Monitoring emerges as a crucial foundation for achieving operational excellence in today’s intricate technological landscape. Observability empowers engineers with proactive insights, allowing them to understand and optimize systems based on real-time data. On the other hand, Monitoring serves as a vigilant guardian, capturing predefined metrics to ensure the current health and performance of systems. While both share similarities in utilizing telemetry data, they differ in scope, with Observability encompassing a holistic view of application performance through logs, metrics, events, and traces.

In the spirit of this sharing knowledge culture, stay tuned for more engaging workshops, discussions, and explorations into fascinating topics shaping the tech landscape. From emerging technologies to innovative strategies, we aim to bring you valuable insights that empower you in navigating the ever-evolving world of IT.