Master Microservices with Spring Boot and Spring Cloud - Step 10 – Introduction to Distributed Tracing

The video tutorial explores the use of Docker to run microservices, focusing on distributed tracing. It explains the challenges of debugging complex microservice call chains and introduces distributed tracing as a solution. The tutorial details how distributed tracing works by sending information to a tracing server, which stores it in a database. The course uses an in-memory database for this purpose. Finally, the video guides viewers on setting up the Zipkin server as a Docker container to connect microservices for tracing.

What is the primary focus of the initial steps discussed in the video?

• Understanding machine learning

• Setting up a database

• Exploring Docker and its features

• Learning about cloud computing

Why is distributed tracing important in microservices?

• It reduces the cost of microservices

• It allows tracing requests across multiple microservices

• It helps in scaling microservices

• It improves the speed of microservices

How does distributed tracing work according to the video?

• By using a cloud-based solution

• By sending information to a central tracing server

• By manually checking each microservice

• By storing logs in each microservice

What type of database is used in the course for storing tracing information?

• Graph database

• In-memory database

• NoSQL database

• SQL database

Which tool is mentioned for implementing distributed tracing in the video?

• Kibana

• Prometheus

• Grafana

• Zipkin