Jaeger Tracing Overview

One of the major challenges for developers today is to understand how a request is handled by an application. The lack of visibility into real user interaction with the app can make developers incapable of evaluating its performance. In a competitive market where customer experience is of utmost importance, not having control or the ability to monitor application performance can be a major drawback. While monitoring is critical in ensuring a seamless experience for your customer, the complexity of modern applications only makes it more difficult to do.

In the past, applications were commonly built as monoliths, i.e., as a single functional unit. But with dynamic customer demands and market expectations, enterprises had to seek a better way to accommodate a wide range of features. This necessity gave rise to microservices architecture. In this model, each application is broken down into multiple modular services, each handling a specific functionality. While microservices made it easy to deploy, test, update and manage failures, they did little to help teams track a customer request. One significant reason was that microservices were operated in an ecosystem known as a distributed system. 

IT teams needed a mechanism to monitor these distributed systems and understand what went wrong when the application reported an error. One such process is known as Jaeger tracing. It is done through a software program that enables you to monitor and run root cause analyses to troubleshoot problems within interconnected software setups.

Before we explore Jaeger tracing and how it works, we need to get a quick understanding of what is distributed tracing.

Distributed tracing

In simple terms, distributed tracing is a process of investigating how events take place between microservices.

Let’s understand how microservices architecture works. Imagine you’re at a grocery store with a shopping list. You will have to go through different aisles collecting the items you want before reaching the cash counter, making the payment, and exiting the premises. Similarly, every user request will have to go through multiple microservices to produce the desired result. If there is a blockade or delay in response at any service point, it can disrupt the entire operation. To understand what and where things went wrong, you will have to run an investigation across the systems. However, a better and faster way to isolate the issue is to follow the requests as they traverse between microservices. Tracing a request to identify a performance issue is known as distributed tracing.

Now that we have a basic understanding of distributed tracing, let’s move on to Jaeger tracing.

What is Jaeger Tracing?

Built by Uber, Jaeger is an open-source distributed tracing system used to monitor and manage application performance within a complicated microservices ecosystem. Jaeger helps you to visualize the flow of user requests through different microservices to identify the root cause of a performance issue.

As a graduate Cloud Native Computing Foundation (CNFC) project, Jaeger has a large community of contributors who work constantly to improve the software.

Jaeger tracing has multiple applications in managing the performance of a microservices system. Some of the processes it runs are listed below.

Distributed context propagation

It is the process of tagging descriptive information along with the user request to facilitate better investigation into performance challenges. For example, Jaeger can pass customer names along with order requests so that the request can be mapped back to a specific customer.

Distributed transaction monitoring

Jaeger will allow you to continuously monitor request data moving across the system by setting up alerts so that you can take a proactive stance in detecting issues and mitigating impact.

Root cause analysis

Microservices architecture involves requests traveling through the distributed system in a chain-like structure. This means, one weak link or disruption at one microservice will trigger a chain reaction across the system. In such a setup, Jaeger will enable you to identify the point of inception of any performance issue.

Service dependency analysis

Jaeger can accurately map and visualize the complex interconnections between different microservices, which will apprise you of all the dependencies. 

Performance or latency optimization

You can use Jaeger to identify bottlenecks in the microservices architecture, causing the entire application's slowdown. With Jaeger, you can run various investigations to detect the scope of optimizing performance for faster and enhanced customer experience.

How does Jaeger tracing work?

The workflow of Jaeger tracing can be explained better by dissecting the entire process into different parts. Jaeger has several key components that together gather and visualize how data is traversing through the system.

Traces

Traces are execution requests that Jaeger carries out. It represents the route that data follows in the system.

Span

A span is a logical unit of work comprising the operation name, start time, and duration. One or more spans form a trace.

Jaeger Client

Jaegar clients are libraries written in various programming languages like Go, Javascript, Java, Python, and Ruby that facilitate language-specific implementation of the OpenTracing API for distributed tracing.

Jaeger Agent

A Jaeger agent is a network daemon that captures spans, batches them, and sends them to collectors. Clients send the spans through a communication network known as User Datagram Protocol (UDP). This process ensures that the trace information the application sends does not go to the Jaeger backend.

Jaeger Collector

As the name suggests, a Jaeger collector receives spans that the agent sends and queues them for processing. The scope of the collector includes validation, indexing, transformation, and storage. 

Query

Query is the mechanism that retrieves spans from the storage and passes them to developers for tracing through the Jaeger UI.

Jaeger Console

Jaeger console is the program that presents you with all the tracing data in graphs and charts through an interface, where you can view and analyze data.

The principle of Jaeger tracing is based on two concepts - distributed tracing and OpenTracing. As we already discussed distributed tracing, let’s briefly touch on OpenTracing.

OpenTracing is a standard framework for generating and managing distributed tracing data. Jaeger uses the vendor-neutral OpenTracing API to extend the accuracy it mandates for your monitoring data visualization. 

AI-Powered DevOps Self-Serve

Application complexity will only increase, and so will the intricacies of the microservice architecture of the software. In such an ecosystem, monitoring user interactions with your application and tracing requests through different modules gains significance. To that effect, it is critical to proactively turn to Jaeger tracing to look for issues and performance gaps through continuous monitoring. Sometimes, responding to an error instantly will save businesses a lot of money and increase confidence in app management.

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