Many companies that thrive on technological advancements use cloud enablement services to host data from various resources and the IT infrastructure. Such companies make use of distributed tracing, which works in distributed cloud environments. Distributed tracing interacts with microservices and helps to improve user experience. It is instrumental in monitoring every aspect of dynamic microservices, right from the applications to the infrastructure of the systems.

What is meant by distributed tracing?

In distributed systems, requests are propagated and traced. Distributed tracing is essentially a diagnostic technique. It deals with specific requests and coordinates all services included in the request path. When distributed tracing follows one request, that single trace reveals all activity in that particular transaction. The trace starts from the application that is being monitored and goes right through the system’s database. While data can be traced from a single activity, it helps when all requests have been observed and data collection is possible. The collected data is known as trace data, and it allows professionals to understand which areas require optimization. It also helps to reveal the impact of all back-end services and the database on the system’s performance. Companies can use the trace data to understand how the performance affects user experience and what can be done to change or improve it.

How does distributed tracing work?

Distributed tracing follows specific requests and performs particular tasks to improve the microservices architecture. Once the request is made, distributed tracing will follow the path of the request. It will collect data from every service or application the request moves through. The trace data is then analyzed thoroughly. The analysis of trace data can help monitor system performance, debug, troubleshoot, and even optimize the service. The activity of distributed tracing, collecting, and analyzing data is known as a segment or span. When the request initiates or triggers a segment, it is immediately recorded. The activity happens as long as distributed tracing follows the path of the request. The activity in and on each service is registered. The data is saved with a name, timestamps for the start and end of the segment, and metadata. Once an activity is completed, it is known as the “parent span”, and distributed tracing moves onto the next activity, known as the “child span”. The final trace data places each of these segments or spans in the proper order.

How can service owners use distributed tracing?

When distributed tracing is used, it can follow a single request through different parts of a system. While distributed tracing can be used to record the end-to-end path of the request, distributed tracing has many more uses related to the health of the system and IT infrastructure. Here are a few ways in which distributed tracing can be used:

• Distributed tracing in microservices can be used to understand the health of software applications. Trace data can help to determine which areas are degrading and require immediate change or correction. If distributed tracing is used for monitoring, it can prevent the malfunction of applications early.
• Often, there are attacks and problems with the systems that technicians cannot understand at the very beginning. It occurs mainly with the security services. While companies invest in cyber security and compliance services, distributed tracing helps track unseen issues and help troubleshoot.
• Performance problems at the code level are common. But these can be resolved quickly with distributed tracing. The trace data can reveal bottlenecks and assist in debugging entire systems, if necessary.
• While distributed tracing can be used to monitor the health of applications, it can also be used to monitor the system’s overall performance. Professionals can use the metrics obtained from monitoring interactive visual dashboards to understand if the system is functioning correctly.
• Distributed tracing can be used to analyze the end-user experience. Companies using distributed tracing can analyze response times and complete digital experiences with the help of trace data. This will allow companies to optimize their systems to improve user experience.

Why is it necessary to analyze trace data?

Digital transformation services and solutions are being adopted by every company that uses software applications in any department. Distributed tracing, too, is a solution that needs to be used. It works well with existing technologies and can help to reveal the aspects that require modifications or transformation. The biggest reason why it can do so is the availability of insights on analyzing trace data. The real impact and use of distributed tracing hinge on these insights. When the trace data is analyzed, the metrics obtained can be used to solve various issues. The metrics are used in the correct context so that they have the maximum impact. It is especially important for troubleshooting or improving the overall user experience. The insights are initially gathered from analyzing individual traces. Then they are applied to the global health of the system. The metrics available help professionals understand the historical performances, the real-time impact of the segment, latency, and errors.

Companies and service owners are responsible for how their systems function. They need real insights along with solutions for troubleshooting. If end-users are experiencing performance issues, service owners need to explain the issue and provide immediate rectification. The issue can be due to internal problems like bugs in an updated version. It can also be due to third-party interference or attacks on the service. Complete analysis of the trace data will reveal the exact cause of the issue, and thus companies will have a better idea of how to solve it. Such insights can also ease the clients’ concerns about the system and direct them towards a more optimized system of service.

Conclusion

Every modern and advanced software architecture is either serverless or is dependent on microservices. While this assists in the better development of applications, it can also result in limited visibility. Distributed tracing can increase real-time visibility by observing the request path through the system. This technique has thus vastly improved the operation of different services and the global system behavior.