What is telemetry and why is it important?

Properly leveraging telemetry is a true game-changer for any IT department looking to optimize and stabilize its systems. Telemetry provides the first step to answering the all-important question, “What’s happening in my network?” It’s your eye into the inner workings of your system, giving you a view into how different components are performing. 

The way you design your telemetry has a huge impact on IT observability, root cause analysis and how well you can relate changes to incidents.

Telemetry: An overview

Telemetry gives you the kind of deep, detailed view into how your most important systems are functioning. It acts as both a telescope, bringing issues closer, and a microscope, helping you zoom in to catch the most granular details. 

It’s a data collection system for retrieving information from components on your network, allowing you to better understand how they’re working. In this way, telemetry serves as the backbone of observability, much like the human nervous system, which sends information about different body parts to a central brain. If a component on your network is offline or underperforming, your telemetric system will let you know.

The role of inputs in telemetry

Inputs are the different kinds of data you collect, which you ultimately use to figure out how your network is performing. The key is to choose inputs that enable you to gain actionable insights.

Choosing your inputs is a matter of asking, “What information will help me understand how my network is doing?” While it may seem logical to gather as much information as possible, it’s more important to be strategic.

For instance, suppose you have an e-commerce web app. Users open the app, choose items to purchase, put them in a shopping cart and then complete the process during checkout. Your company may want inputs to help with user experience optimization, so your input choices may focus on the core components that make selecting items and completing purchases easy. 

Another company may want to change how their e-commerce app works, so their input choices may be specifically designed to see how the changes impact the app’s functionality.

The role of output data analysis in telemetry

Analyzing your telemetry system’s output data is the foundation of your observability strategy. As you choose how to collect and process the data, as well as what to do with it, you’re taking input information and giving it value in a way that boosts business performance.

For example, you can output data to a system that collects and analyzes event logs. In this way, given the right inputs, you have all the info you need to relate changes to incidents, as well as go back and review your data to figure out what caused the changes.

Say hello to OpenTelemetry

OpenTelemetry is a technology that puts all the benefits of telemetry into the palm of your hand, making it easier to build exactly the kind of system you need to collect and report data. One of the benefits of OpenTelemetry is that it works as your very own developer’s toolkit‌. It’s actual code instead of a closed box solution you can’t tweak or control.

You also get access to libraries you can use to quickly connect applications and the data they produce, all without sacrificing control over the solution. OpenTelemetry is like an easy-to-use box of telemetry toys, giving you the freedom to generate deeper, more powerful insights.

Why is telemetry important for IT observability?

In IT observability, telemetry is your information production system. It shows you what’s happening, and you can use this info to fix or fine-tune your system’s performance. Depending on how you choose your inputs and process your outputs, telemetry can make determining root causes far easier and faster, easing the burden on your IT team.

Leverage telemetry data with SUSE Cloud Observability

Telemetry data is crucial for observability. With the right tools, you can get an incredible amount of detail as you look into your system’s performance. However, telemetry data is often captured from separate external IT systems (such as monitoring, provisioning, deployment and configuration management tools). This can cause silos and thus inefficiencies: different teams work with different solutions, which each present their own telemetry data types. The result? There’s lots of data, but it’s difficult to see how everything is related. 

For effective observability, you need a clear and comprehensive picture of the state of your stack. This is exactly what SUSE Cloud Observability’s full-stack observability platform does. 

If you would like to learn how full-stack observability can work for you, download the white paper, “Bridging the gap between traditional and modern observability.”