OpenTelemetry vs OpenTracing: A Guide on Understanding How These Work

OpenTelemetry is a relatively new word that programmers are getting acquainted with in recent times. It’s a Cloud Native Computing Foundation (CNCF) sandbox project. Its uniqueness is found in its final goal, which is to create a unified API set, or what is referred to as vendor-agnostic libraries, useful to gather and send data from back ends that are compatible. 

The most important edge of OpenTelemetry is what is called observability, which simply means an ability to monitor the internal health and status of any given system by focusing on the data it produces by looking at its metrics, traces, and logs. 

The collection of this data is actually not a new concept in the programming field, but having a common format to collect and send data is where OpenTelemetry comes in. The end goal of observability is to determine the extent to which the external outputs of a system can be used to determine its internal state. Read on below to see how OpenTelemetry and OpenTracing work. 

How OpenTelemetry Works

If you’ve followed the explanations so far, you’d see that there’s nothing new in collecting and applying telemetry leveraging on the back ends, logs and metrics. The major distinguishing factor is on the format and collection mechanism, which is different from one application to another.

These differences have been a major problem for developers and operations personnel that are interested in the status of any given application.

This is where OpenTelemetry becomes relevant. OpenTelemetry provides a standard to create observability to cloud-focused applications. This will save companies time as they wouldn’t have to focus on creating mechanisms to collect application’s telemetry. 

How OpenTelemetry Works: Step-by-Step Guide

If you’re still confused about how OpenTelemetry works, here is a step-by-step guide to making the process easier. 

• The first step in OpenTelemetry is communication between collectors, and different back ends through exporters. 
• The next step will be for the collector to aggregate, batch, and process according to the collection’s configuration.
• Then the collector and the exporter exchange data in the form of telemetry, which is usually sent as an in-process. 
• The next step is the need for processing extensions, which can be added by SDK and allows for effects such as filtering, samplings, and enrichments. Sometimes, it’s possible to replace the SDK with an alternative. But to understand this process, we have to first look at the various components of OpenTelemetry.  

Components of OpenTelemetry

OpenTelemetry has several components, these includes:

• APIs: APIs are a core element to OpenTelemetry that are specific to the coding language of the program itself. These are some of the foundations of the program.
• The SDK: This component is also unique to each coding language. It focuses on building the gap between exported elements and the APIs. The SDK also allows other features like transaction sampling and filtering, making them ideal in OpenTelemetry. 
• The In-Process Exporter: This is needed to determine where you want your telemetry sent. This exporter allows you to easily decouple your code from the back-end configuration, making it easy to alternate back ends without having to re-instrument your code. 
• The Collector: This function in telemetry is optional, but a very useful component of OpenTelemetry because it allows for flexibility in the sending and receiving of application telemetry to the back ends. There are two models of deployment of the collector. The first is the agent that uses the same host with the application, and the second is a standalone process which is separate and doesn’t use the same host with the application. 

The point is that OpenTelemetry relies on a back end to store received data because it requires a specification on sending and collecting telemetry. 

OpenTracing

OpenTracing, like OpenTelemetry, is also a CNCF project. It was first released around December 2016. Since then, it has been vendor-neutral API in the semantic specification, useful in tracing writing. About nine languages are supported by its library, with each having a simple interface useful in coding for easy traceability by any project or vendor. 

In OpenTracing, there are outputs which are a time based and orderly breakdown of cycles embedded in the trace request. Also, OpenTracing removes from the application layers the tracing layer, thus allowing developers to be able to change tracers or even create their own tracers without altering the main code.

OpenTelemetry vs OpenTracing

When it comes to comparing both OpenTelemetry and OpenTracing, you’ll notice that OpenTelemetry is like a combination of both OpenTracing and OpenCensus. 

OpenCensus was created in January 2018 as an open-source tool and was introduced by Google in its internal census library. OpenCensus was introduced as a library collection used by applications for distributed tracing and time-series metrics. These metrics collected via OpenCensus uses the same metadata and propagation tags, thus making sure that the observability back end is more. 

Google started OpenCensus as part of its internal libraries and released it in January 2018 as an open-source tool. Unlike OpenTracing, OpenCensus is a collection of libraries for gathering both time-series metrics and distributed tracing from a given application.

These applications mostly import and use desired exporter metrics which are specific to different applications. OpenCensus service can collect metrics and trace data for specific processes that are connected to the back end irrespective of the output and formats used. 

This makes OpenTracing and OpenCensus something that goes hand in hand with the developer. It’s also why OpenTelemetry project major objectives and principles of operation focuses on the combination of the effects of both OpenTracing and OpenCensus. 

Conclusion

In summary, OpenTelemetry is a program framework that combines roles of OpenTracing and OpenCensus. It aims to provide a set of frameworks that’s easy to implement across several languages. This means with OpenTelemetry you can easily move OpenTracing and OpenCensus without any significant changes. There’s a two years instrumentation window created for both OpenTracing and OpenCensus. During this window, there’s an easy and direct migration path from each root project through supported compatibility bridges. 

Share Article

Follow Us

Return to Previous Page