Introduction to Observability: How Does It Work?

4 Mins read
Introduction to Observability: How Does It Work?

If  you’re keen on the latest in IT developments and trends, you may have come across the term ‘Observability.’ What’s more, there are many industry leaders that emphasize the need to make use of observability. 

One of the main reasons why observability is so important in organizations is the fact that organizations are now using software for many different functions while not being responsible for the writing and coding of the various systems.

Furthermore, as new systems are released, they continue to be all the more complex in their coding and design. Because of this, there’s the need for teams to understand the relationship that exists between all the different software systems. This is the basis of observability.

By making systems observable you can use software to transform your business.

Understanding Observability

What is observability? Observability simply means to deduce the internal workings of the systems by observing the software’s external outputs. And, you can do this without the need to shift to a new code.

One of the main benefits of making a system more observable is that the teams that manage and run the system can see how it’s performing. Developers will also be able to observe what’s going on with the system as it receives traffic, and easily find solutions since they can inspect the logs.

But that is not where things end. Markets and salespeople can ask the developers to include certain aspects such as identifiers for campaigns. They may also want to see customer IDs in the system. This simply means that observability can help make the system more versatile and more suited to the needs of the business.

Observability is important in helping develop tools that deliver work in a world where the complexity of systems continues to increase. Observability also predicts if the system’s code is about to break. This means that you can anticipate the problem and fix it before it causes a disruption in the operation s of the organization.

If the system simply isn’t observable, you won’t be in a position to understand what’s causing an issue and you won’t have any starting point. Ultimately this means that you will not be able to solve issues with the system. Depending on the magnitude, it can end causing a major disruption in business operations. With an observable system, however, you’ll have the instrument to identify the problem.

Simply put observability is all about focusing on both the development of the system as well as its rich instrumentation. Moreover, you won’t only monitor it for thresholds but it also allows you to ask the right questions on how the system actually works.

Keep in mind that it’s impossible to know the type of information you’ll need for a question that’s equally hard to predict. That said, making the software observable also comes with a few challenges.

One of the main challenges involves correlation events. However, you can deal with this by including identifiers to a register. These will inform you of what happened before an error occurred. By properly instrumenting your application, you can better interpret the information.

Aggregating data also proves to be quite challenging. You will eventually find that you have a lot of events that come from different sources. To make things easier it is best to have the application logs and the database longs in the same location.

Now that we understand what is observability lets also define what it is not.

What Observability Is Not

Observability is not monitoring. Often, people tend to associate monitoring with observability and consider it the predecessor. One of the main reasons why this is the case is because the term monitoring came before observability was even a thing.

While observability and monitoring are complementary to each other, they’re separate functions. Monitoring focuses on the overall system and offers a panoramic view, helping identify software shortcomings.

On the other hand, observability goes into detail and aims to identify why the system is not meeting expectations.

The Components of Observability

Here are the three main components of observability:

  • The Metrics: This refers to a number or value that’s taken over a specified period of time. One of the main functions is to trigger alerts as well as helping identify problems within the system.
  • The Logs: These refer to the stored records of events. The benefit of these is to provide information on what happened at a particular point in time.
  • Distributed Traces: These are simply representations of code executions. Their function is to see the flow of an execution path from end to end through a system.

How To Make the System More Observable

The first step towards making a system observable is to ensure that you collect all kinds of data and information that surrounds the system. These include memory, CPU, network, and disk metrics. You’ll also need to include the logs for the application where you don’t control the source codes.

That said, you need to consider the logs from the application itself. To do that, you’ll need to make use of the instrumentation. The great thing is that you can always find available tools that you can use to log information from the metrics, traces, and the logs.

Don’t worry if you notice that after production, the system doesn’t provide enough information. The great thing is that you can always add more information to the system. A point to keep in mind is to always remove information that isn’t necessary or needed.

Also, ensure that you store all the information in one central place. Moreover, the information should also be kept in a raw format to aggregate as well as disaggregate the information as required.

Final Thoughts

With observability, you’ll be able to ask external questions that will help you understand the internal workings of the system. Note that by making your software observable you are able to solve most of the problems but it’s crucial to always keep examining the information to identify if it’s still useful.

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