Spring Boot Demo

Created:2024-06-01 Last Modified:2024-06-24

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#1. Introduction

This chapter uses a microservice application developed with Spring Boot as an example to demonstrate DeepFlow's AutoTracing capabilities.

#2. Deploying the Spring Boot Demo

The demo we use is sourced from this GitHub repository (opens new window), and its call chain is relatively simple: foo_svc -> bar_svc -> loo_svc.

You can quickly deploy the demo in K8s using the following command:

kubectl apply -f https://raw.githubusercontent.com/deepflowio/deepflow-demo/main/DeepFlow-EBPF-Sping-Demo/deepflow-ebpf-spring-demo.yaml

The original GitHub code repository for this demo uses Jaeger for active tracing. To demonstrate AutoTracing capabilities, we have specifically removed Jaeger in the above deployment script.

#3. Viewing Distributed Tracing

Go to Grafana, open the Distributed Tracing Dashboard, select namespace = deepflow-ebpf-spring-demo, and then choose a call to trace. The effect is shown in the figure below:

eBPF Sping Demo

eBPF Sping Demo

DeepFlow's tracing data contains three types of Spans, tracking the entire trajectory of a request:

  • N: Spans extracted from network traffic via BPF
  • S: Spans extracted from system or application function calls via eBPF
  • A: Spans collected from within the application via OTel

The figure above shows the first two types, and the third type can be displayed by integrating OpenTelemetry.

Visit DeepFlow Online Demo (opens new window) to also view the tracing effect. The topology corresponding to the call chain flame graph in the figure above is as follows.

To summarize this tracing demo:

  • Zero Instrumentation: The entire tracing process does not require manually inserting any tracing code or injecting any TraceID/SpanID into the HTTP Header.
  • Multi-language: Supports tracing for Java applications and C (curl) language basic services.
  • Full Link: Utilizing eBPF and BPF, it automatically traces 18 Spans for this trace, including 6 eBPF Spans and 12 BPF Spans.
  • Full Stack: Supports tracing the network path between two Pods across K8s Nodes, even if it passes through tunnel encapsulation in the middle, such as Spans 2-5 (IPIP tunnel encapsulation).