Скачать или смотреть How to Specify Sampler Probability with Spring Cloud Sleuth: An In-Depth Guide

Discover how to configure sampler probabilities using Spring Cloud Sleuth annotations or programmatically. We'll break down the solutions and help you choose the right approach for your needs.
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How to Specify Sampler Probability with Spring Cloud Sleuth: An In-Depth Guide

Spring Boot applications often require efficient trace management, especially for microservices. When working with Spring Cloud Sleuth, you might find yourself needing to control the sampler probability for specific methods or use cases. This guide will guide you through the process of specifying sampler probabilities, whether through annotations or programmatic methods, perfect for developers navigating the complexities of tracing in distributed systems.

Understanding Sampler Probability in Spring Cloud Sleuth

What is Sampler Probability?

Sampler probability in Spring Cloud Sleuth determines how often traces for requests should be sampled and recorded. It’s expressed as a decimal between 0 and 1, where 0.1 means 10% of requests will be sampled. Setting this correctly can help you manage trace data volume effectively.

The Challenge

In an ongoing project using Spring Boot 2.7.0 and Spring Cloud 2021.0.3, it's crucial to have the flexibility to specify differing sampler probabilities for specific methods. The default configuration might work for most flows, but you might encounter cases where certain methods should always have a trace generated, regardless of the general sample rate.

Solutions to Specify Sampler Probability

Let’s dive into the solutions that will allow you to manage sampler probabilities optimally.

1. Use Spring Annotations

Currently, there isn’t a straightforward way to specify the sample rate probability on a method level directly through annotations in Spring Sleuth. As of now, the sampling decision is generally made at a broader level. However, there's a workaround using a custom SpanFilter.

2. Programmatic Approach for Sampler Probability

If you want finer control over which requests to trace programmatically, you can create a custom SpanFilter. This is how you can do it:

Creating a Custom SpanFilter

To programmatically control sampling:

Create a Bean: Define a new bean of type org.springframework.cloud.sleuth.exporter.SpanFilter.

Implement the Method: Within this bean, implement the logic to check the FinishedSpan and decide whether to export the span or not.

Here's a sample implementation:

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3. Configuring Different Sample Rates in Properties

If you are looking for a way to configure different sample rates in your application.properties or application.yml, this approach currently does not exist in a straightforward manner. Each property level is fixed, and there are limitations to changing sample rates for individual methods directly from configuration files.

Conclusion

In summary, managing sampler probability in Spring Cloud Sleuth can help streamline your tracing strategy, ensuring that you capture meaningful data without inundating your system with unnecessary traced requests. Use a combination of global settings in your properties file and a custom SpanFilter to achieve the desired behavior on a method-specific basis.

By understanding how to implement these solutions, you can effectively adapt your tracing needs in a scalable and manageable way.

Remember: Whether you opt for annotations, programmatic configurations, or rely on property files, knowing your requirements clearly will help you choose the right approach for specifying sampler probabilities in your Spring Boot applications.