IMPORTANCE OF Observability and Monitoring

Developers are unable to comprehend application behavior and support day-two operations in the current state. The goal is to address the issue of unclear application state or behavior, which is frequently brought on by anomalies or duplications in telemetry data. This can ultimately prolong the time it takes to find the underlying cause, but it's not the only reason.

Understanding behavior to improve stability and quality is one of the most important aspects of cloud-native applications. As per Gartner's analysis product teams will bear more of the monitoring burden because of the increasing ephemerality that results from the transition from monolith to polyglot. According to the same report, 70% to 80 % of businesses will put developers in charge of their application and product monitoring teams by 2023.

The goal of the Observability and Monitoring product line is to enable the product team transformation journey through the rollout of Observability and data socialization.

It is crucial to emphasize that the Observability?and Monitoring product line are major enablers of product team transformation because of additional variables. To take a few -

The VUCA World

The 12 Factor

In recent times we have been talking about the terms Observability and Monitoring a lot. How does this appear? Is this a Technology? Not. I would say it's a practice which may vary from case to case. The end goal is to simply the the Monitoring with a lot of advanced features in a tool that can fix more of these by themselves. What we want is integrated and modular solutions/tools to consume the data already collected from different sources and data points. fully decoupled, only those data which we need, open source vendor supported, fully automated along with custom metric features, etc

Let's talk about some Monitoring, this allows you to reduce the costs associated with outages. Profits are lost when a system or device goes down for an extended period, but with careful monitoring, you can detect and solve problems as they arise.

It also allows you to see if your assets are operating efficiently over time because it covers long-term trends in the performance of your system. You can determine whether your assets are operating efficiently and plan to update and improve your infrastructure. As a result, and with fewer technological bottlenecks, your overall productivity rises.

when it comes to Observability, it assesses how well you can understand a system's internal states by looking at its outputs. Its origins can be traced back to control theory. Instrumentation is used by Observability to deliver monitoring insights. Monitoring is what you do when a system has become observable. Monitoring is impossible without some amount of observability.

Observable systems help you to understand system behaviors, even in complicated microservice architectures, so you can more quickly traverse from the effects to the cause. It enables you to discover answers to questions such as what service gives a request and where the performance bottlenecks occurred.

Now if we see things in a structured way, we can say that Observability and Monitoring have three pillars. Let's have a picture for this:-

Brief About Logs:

We only review logs for information when something goes wrong. A text line that details an event that occurred at a specific time is called a log. Logs can sometimes be found in plain text format, depending on the system that generates them. However, structured logs are increasingly more common, making it easier to interpret the data and execute queries to efficiently debug. A timestamp and a payload that contributes to providing additional event context make up a log.

Brief About Metrics:

Metrics, often known as telemetry data, are numerical representations of system and application components measured at a certain time in the context of observability and monitoring. Developers can effectively store, process, visualize, and send out alerts based on data points from multiple systems using the Metrics platforms. These data points can come from custom application metrics, which reveal key performance indicators like the frequency of a specific business transaction, or they can come from the underlying infrastructure, which includes CPU and Memory usage.

Brief About Traces:

Information about certain application operations is "traced" by application trace data. These days, there are a lot of application interdependencies, therefore these actions will usually include hops across several services.

Thus, traces provide vital insight into the overall health of an application. However, they only pay attention to the application layer and offer a restricted view of the state of the underlying infrastructure. Therefore, to fully understand your environment, metrics are still necessary, even if you gather traces. Traces are a good source of data for an app-centric perspective because APM tools deliver trace information to a centralized metrics database.

If we consider the practice of Observability and Monitoring as a Product then let's have a look at the Product line chart.

Even though the market is quite active and many companies are making every effort to simplify and onboard as many additional tool components as possible, the complexity of observability and monitoring space remains. Additionally, businesses are making every effort to include legacy system monitoring within their purview.

One such tool that I have personally used is OPSRAMP, which can effectively handle all aspects of observability and monitoring in addition to AI operations and utilizing generate AI for forward-thinking research in this field.