Spans are fundamental building blocks of distributed tracing. A single trace in distributed tracing consists of a series of tagged time intervals known as spans. Spans represent a logical unit of work in completing a user request or transaction.
In the ever-evolving world of software development, one constant remains - the pursuit of better performance. As applications grow in complexity and demand, the need for tools to uncover performance bottlenecks becomes paramount.
Flamegraphs, a brainchild of Brendan Gregg, has emerged as an important visualization of insight, showing those dark corners of your codebase that need optimization. Before we dive into understanding how to use these instruments, let's first light the flames of curiosity by exploring what exactly a Flamegraph is and why it's a must-have in your performance optimization toolkit.
Microservices architecture allows technology companies to build application services around business capabilities. It enables rapid development and also boosts developer productivity. But it also introduces complexity. Troubleshooting and operating an internet-scale application based on microservices is hard. And that’s where distributed tracing comes into the picture.
In modern microservices-based applications, it is difficult to get an overview of how requests are performing across multiple services, infrastructure, and protocols. As companies began moving to distributed systems, they realized they needed a way to track requests in their entirety for debugging applications. Distributed tracing is a technology that was born out of this need.
Monitoring and troubleshooting distributed systems like those built with microservices is challenging. Traditional monitoring tools struggle with distributed systems as they were made for a single component. Distributed tracing solves this problem by tracking a transaction across components.
OpenTelemetry is an open-source standard for instrumenting cloud-native applications for generating different types of telemetry data. A robust observability framework set up using OpenTelemetry can help tremendously while troubleshooting software in production.
OpenTelemetry consists of several main components. But to understand the architecture, we will start by understanding some of the key design principles behind the design and architecture of OpenTelemetry.
In the previous article, we learned what distributed tracing is, why it is necessary, how to do tracing, encountered challenges with existing tracing tools, and finally discovered that there is a more mature option available for the industry to adopt in terms of telemetry and observability.
In this article, we will be trying to understand OpenTelemetry in more depth.
Have you heard about traces? Most likely, yes! Do you confuse it with auditing? Hope not. Today, we're going to talk about tracing, specifically “Distributed Tracing,” and do a deep dive into it. Once we’re familiar with distributed tracing, we will show you how to implement it with OpenTelemetry - a new-age observability framework.
Jaeger is a popular open-source tool used for distributed tracing in a microservice architecture. In a microservice architecture, a user request or transaction can travel across hundreds of services before serving what a user wants. Distributed tracing helps to track the performance of a transaction across multiple services.