Master Microservices with Spring Boot and Spring Cloud - Step 37 – Introduction to Distributed Tracing with Zipkin

The video tutorial discusses the challenges of tracing requests across multiple microservices and introduces centralized logging as a solution. It explores various tools like the ELK stack and Zipkin for consolidating logs. The tutorial explains how to implement Zipkin with RabbitMQ to handle log messages and provides an overview of request flow through microservices, highlighting the role of unique IDs in tracing requests. The video concludes with a brief on installing RabbitMQ and Zipkin.

What is the main challenge when tracing requests across multiple microservices?

• Centralizing log data

• Assigning unique IDs to requests

• Using RabbitMQ for log messages

• Checking logs of individual applications

Which of the following is NOT part of the ELK stack?

• Logstash

• Elasticsearch

• Kibana

• RabbitMQ

What tool is used in the course to provide a consolidated view of logs?

• ELK stack

• Zipkin distributed tracing server

• RabbitMQ

• Spring Cloud

How are log messages transferred to the Zipkin server?

• Using RabbitMQ

• Through the API gateway

• Directly through HTTP requests

• Via a centralized database

What type of database is used for storing logs in the examples?

• SQL database

• NoSQL database

• In-memory database

• Distributed database