Imagine this: you’ve set up a robust distributed tracing system using io.micrometer and io.zipkin.reporter2, and everything seems to be working as expected. You’re thrilled to see the beautifully rendered traces in your Zipkin dashboard, but then suddenly, you realize that not all traces are visible. You scratch your head, wondering what could be the reason behind this anomaly. Fear not, dear developer, for we’re about to embark on a thrilling adventure to unravel the mystery of the missing traces!
Setting the Stage: Understanding io.micrometer and io.zipkin.reporter2
Before we dive into the solution, let’s take a step back and briefly understand the context. Io.micrometer is a popular metrics library for Java that provides a simple and efficient way to instrument your application. On the other hand, io.zipkin.reporter2 is a reporter that sends spans to Zipkin, a popular distributed tracing system. When you use the `@Observed` annotation from io.micrometer, you’re telling the library to automatically create a span for the annotated method, which is then reported to Zipkin using the reporter. Sounds straightforward, right?
The Problem: Can’t See All the Traces
Now, let’s assume you’ve set up io.micrometer and io.zipkin.reporter2 in your application, and you’ve even added the `@Observed` annotation to the methods you want to trace. However, when you visit your Zipkin dashboard, you notice that some traces are missing. You’ve checked the logs, and the spans are being generated correctly, but they’re just not showing up in Zipkin. What could be the reason?
Possible Causes and Solutions
Let’s explore some possible reasons why you might not be seeing all the traces in Zipkin:
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Incomplete or Missing Configuration
Make sure you’ve properly configured io.micrometer and io.zipkin.reporter2 in your application. Double-check your configuration files, environment variables, or code to ensure that everything is set up correctly.
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Span Sampling
Zipkin uses sampling to control the volume of spans being reported. By default, only 1% of spans are sampled. If your application generates a high volume of spans, it’s possible that some traces are being discarded due to sampling. You can adjust the sampling rate or use a different sampling strategy to ensure that more traces are reported.
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Span Naming and Tagging
When using io.micrometer, you need to ensure that spans are properly named and tagged. If spans are not tagged correctly, they might not be visible in Zipkin. Verify that your spans are named and tagged according to Zipkin’s conventions.
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Reporter Configuration
Check your reporter configuration to ensure that it’s correctly set up to send spans to Zipkin. Verify that the reporter is enabled, and the endpoint URL is correct.
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Network Connectivity Issues
Network connectivity issues or firewall restrictions might prevent spans from being reported to Zipkin. Ensure that your application can reach the Zipkin endpoint and that there are no network connectivity issues.
Deep Dive: Troubleshooting Techniques
Now that we’ve explored possible causes, let’s dive deeper into some troubleshooting techniques to help you identify the root cause of the issue:
Debugging io.micrometer
To debug io.micrometer, you can enable debug logging for the io.micrometer package. This will provide detailed information about the spans being generated and reported. Add the following configuration to your logback.xml file:
<configuration> <appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender"> <encoder> <pattern>%d{yyyy-MM-dd'T'HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern> </encoder> </appender> <root level="DEBUG"> <appender-ref ref="STDOUT"/> </root> <logger name="io.micrometer" level="DEBUG"/> </configuration>
With debug logging enabled, you can analyze the log output to identify any issues with span generation or reporting.
Verifying Spans using Zipkin’s REST API
Zipkin provides a REST API that allows you to query and retrieve spans. You can use this API to verify if spans are being reported correctly. Use a tool like curl or Postman to send a GET request to the Zipkin endpoint:
curl -X GET \ 'http://localhost:9411/api/v2/traces?serviceName=my-service&limit=100'
This will retrieve the last 100 spans for the “my-service” service. Analyze the response to ensure that the expected spans are being reported.
Using a Span Listener
A span listener is a callback that allows you to inspect and manipulate spans before they’re reported to Zipkin. You can use a span listener to verify that spans are being generated correctly and to identify any issues with reporting. Create a span listener class that implements the `SpanListener` interface:
public class MySpanListener implements SpanListener { @Override public void onRequest(Span span) { // Inspect the span and verify its properties System.out.println("Received span: " + span); } }
Register the span listener with io.micrometer using the `Micrometer` builder:
Micrometer micrometer = Micrometer .builder() .spanListener(new MySpanListener()) .build();
Conclusion
In this article, we’ve explored the possible causes and solutions for not seeing all traces in Zipkin when using io.micrometer and io.zipkin.reporter2 with the `@Observed` annotation. By following the troubleshooting techniques outlined in this article, you should be able to identify and resolve the root cause of the issue.
Remember to carefully review your configuration, ensure that spans are properly named and tagged, and verify that the reporter is correctly set up to send spans to Zipkin. If you’re still experiencing issues, consider enabling debug logging or using a span listener to gain deeper insights into span generation and reporting.
With these techniques and a little patience, you’ll be able to uncover the mystery of the missing traces and enjoy a more comprehensive view of your distributed system in Zipkin.
Keyword | Description |
---|---|
io.micrometer | A popular metrics library for Java |
io.zipkin.reporter2 | A reporter that sends spans to Zipkin |
@Observed | An annotation that tells io.micrometer to automatically create a span for the annotated method |
Zipkin | A popular distributed tracing system |
Frequently Asked Question
Get ready to shed some light on the mysteries of io.micrometer
and io.zipkin.reporter2
with the @Observed
annotation!
Why can’t I see all the traces using io.micrometer and io.zipkin.reporter2 with the @Observed annotation?
This might be because the @Observed
annotation only captures metrics and not spans. To see all the traces, you need to use the Tracer
from Zipkin to create spans explicitly. Make sure to register the Tracer
with the MicrometerRegistry
to get the complete picture!
How does the @Observed annotation affect my application’s performance?
The @Observed
annotation has almost zero overhead on your application’s performance. It simply registers the metric with the MicrometerRegistry
, which is a lightweight operation. The real magic happens when you use the metrics to create spans, which can be done asynchronously, ensuring your app remains performant!
What’s the difference between io.micrometer and io.zipkin.reporter2?
io.micrometer is a metrics library that provides a simple way to instrument your application, while io.zipkin.reporter2 is a distributed tracing system that helps you visualize the flow of requests through your system. By combining the two, you get a powerful toolset to monitor and optimize your application’s performance!
Can I use the @Observed annotation with other metrics libraries?
While the @Observed
annotation is specifically designed for Micrometer, you can use similar annotations with other metrics libraries, such as Prometheus or Dropwizard Metrics. Just keep in mind that you might need to adjust the configuration and instrumentation to match the library’s requirements!
How do I customize the tracing and metrics configuration for my application?
You can customize the tracing and metrics configuration by using the respective libraries’ configuration options. For example, with Micrometer, you can use the MicrometerRegistry
to configure the metrics, and with Zipkin, you can use the Tracer
to customize the tracing settings. Don’t be afraid to dig into the documentation to find the perfect setup for your application!