Link tracking implementation in Spring Cloud microservices

With the popularity of microservice architecture, more and more enterprises are beginning to adopt Spring Cloud as a microservice solution. However, since each component in a microservice system is deployed independently, when a problem occurs in the system, it is difficult to quickly locate the cause of the problem. At this time, link tracking becomes an important tool.

This article will introduce the implementation of link tracking in Spring Cloud microservices, and discuss how to use link tracking to locate problems.

1. What is link tracing

Link tracing is a technology that can track requests in a distributed system and record the entire path of the request in the distributed system. This path includes the entire process from service initiator to service provider to return results. Through link tracing, we can understand how long the request takes at various stages within the system, and on which components the problem occurs.

2. Implementation of link tracking

In Spring Cloud, we can use Zipkin as a link tracking tool. Zipkin is an open source distributed tracing system that can be used to collect, analyze and query tracing data in distributed applications. Zipkin allows us to understand the propagation of requests in a distributed system and show the response time and processing time of requests in different components.

The main core components of Zipkin are Collector, Storage and Query Service:

Collector is used to collect call information between services and is responsible for storing the call information in Storage.

Storage is the storage component used by Zipkin. Zipkin can use a variety of storage methods, such as Cassandra, MySQL, etc.

Query Service is used to query and display tracking data.

In Spring Cloud, we can integrate Zipkin by using Spring Cloud Sleuth. Sleuth is a distributed tracing solution specifically for Spring Cloud microservices that can provide Zipkin-based link tracing capabilities for microservice applications. Sleuth automatically generates a unique Trace ID for each service and adds the Trace ID to the communication between services. As requests pass through the system, each service carries the Trace ID and adds its own Span ID to the request. This way we can sort requests based on Trace ID and see how requests are handled in different components.

3. How to use link tracing to locate problems

When using link tracing to troubleshoot problems, we can follow the following steps:

1. View Requested Trace ID

When we find a problem with a request, we need to first find the Trace ID of the request. We can enter the Trace ID on Zipkin's query page to query and view the path of the entire request in the system.

2. Analyze the processing time of each component

After we view the path of the request in the system, we need to pay attention to the processing time spent by each component. We can view each component's span on Zipkin's query page and see the span's processing time. If a Span takes too long to process, it means there is a problem with this component.

3. Tracking the time when the problem occurred

After we find which component has the problem, we need to further track the specific time when the problem occurred. At this point, we can trace back the entire request link and check the log of a certain component when the problem occurred to find exception information or error stack. This way we can find the problem and fix it more quickly.

4. Summary

Link tracking is a very important tool in distributed systems, which can help us quickly locate problems. In Spring Cloud microservices, we can use Zipkin as a link tracking tool by integrating Spring Cloud Sleuth. When a problem occurs, we can use link tracking information to help us quickly locate the problem and speed up troubleshooting and resolution.

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