Today’s distributed systems are highly dynamic and spread across vast surfaces. They consist of multiple devices and servers, many of which are configured differently. With so much complexity, it’s not difficult to see how distributed systems can be difficult to operate let alone understand and maintain visibility into.
This is where distributed tracing comes into play.
What is distributed tracing?
Tracing is essentially the act of observing your application. It is a method for tracking requests in your application as they travel between back-end services, which could be anything from an ingress proxy to a database.
Distributed tracing is well-suited for microservice-based architectures, as it allows requests to be tracked between autonomous services and modules. This enables observability into cloud native systems. Observability is always difficult in distributed systems, as they consist of so many components spread across such a broad surface. Distributed tracing enables developers to collect telemetry data across different parts of a system.
How does distributed tracing work?
At its core, distributed tracing works by creating a centralized store for information to pass through. It tracks the path of a request from the source to the destination. This creates a timeline of the request as well as an accurate record of the individual services involved in the request.
Distributed tracing platforms start off by collecting data the very second a request is instituted. A request could, for example, be when a user completes a purchase on an e-commerce website. The action initiates the creation of a unique trace ID in the distributed tracing platform. The trace consists of the entire execution path of the request. Within the trace, each span describes a single path during that journey, which might be an API call or a database query. A top-level child span is then built when the request reaches the destination service, and the span encodes all paths that took place within it. All the spans are visualized at the end so developers can trace the entire path of a request.
Why is distributed tracing important in distributed systems?
Without distributed tracing, it is very difficult for engineers to maintain an overview of what is happening. Without a method for distributed tracing, you have to find out on your own how the communication took place. With distributed tracing, a central system brings all the tracing together, so you don’t have to aggregate data and can maintain a view of the entire system.
What are the benefits of distributed tracing?
When implemented effectively, distributed tracing gives you high-quality insights into how your services communicate with each other which gives you the ability to:
- Identify bottlenecks in traffic
- Debug errors and track down latency issues in your network
- Troubleshoot and fix any requests that are experiencing errors
- Comprehend cause-and-effect connections between services to improve performance
- Tace asynchronous activity, such as when a request will be processed and returned in event-driven architectures
Distributed tracing also helps developers understand how much time is taken to fulfill user actions. Distributed also helps improve collaboration between DevOps teams. While different teams may own different services, distributed tracing brings all actions together in a centralized store for end-to-end visibility. As a result, distributed tracing is a popular tool amongst developers to monitor the performance of their applications. It gives them valuable insights into the performance and reliability of a system.
What are the challenges of distributed tracing?
Distributed tracing is chock full of benefits, but these benefits do come with their own challenges. Some of these include:
- Additional infrastructure and monitoring costs from instrumenting an existing system, as distributed tracing can lead to an increase in communication and data exchange between services
- Manual instrumentation in some cases, which can be expensive in time and resources
- Some distributed tracing platforms randomly sample traces whenever a request begins, and this can lead to missing or incomplete traces
- Unless your distributed tracing platform is end-to-end, a trace ID is only created for a request when it reaches the first backend service, which means you won’t have visibility into the corresponding user session in the frontend
How can you implement distributed tracing?
Distributed tracing is a problem to solve on the application side. You need proper instrumentation to implement it. Traefik Proxy is a reverse proxy that helps, as it allows you to detect the traffic that is entering and exiting a service. It forwards traffic to the back-end service. It integrates with a number of industry-standard tracing backends to track requests through a user’s microservice architecture, namely Jaeger, OpenTracing, and Zipkin.
Jaeger is an open source tool that was created by Uber in 2015 and consists of instrumentation SDKs, a backend for data collection and storage, a UI for data visualization, and a Spark/Flink framework for aggregate trace analysis. With Traefik Proxy, you can enable the Jaeger tracer to perform observability.
OpenTracing provides vendor-neutral APIs and instrumentation for distributed tracing. It consists of an API specification, frameworks, and libraries that have implemented the specification, and documentation for the project. It lets developers add instrumentation to application code with APIs that do involve vendor or product lock-in. The Jaeger data model is also compatible with OpenTracing.
Zipkin is a distributed tracing system that gathers timing data needed to troubleshoot latency problems in service architectures. It allows you to collect and search for data. Traefik Proxy includes an integration with Zipkin that you can use to enable the Zipkin tracer.
Overall, distributed tracing is a powerful tool that provides an unprecedented level of visibility into the performance and reliability of a distributed system. By utilizing distributed tracing, it is possible to identify bottlenecks and latency quickly and accurately, as well as gain key insights into the user experience. Traefik Proxy includes integrations with leading, open source tools for distributed tracing, so developers can visualize call flows easily in their architectures.