Master Microservices with Spring Boot and Spring Cloud - Step 26 – Configuring Liveness and Readiness Probes for Microse

The video tutorial discusses how to minimize downtime during application releases by using Kubernetes liveness and readiness probes. It explains the functionality of these probes and how they help maintain high availability of microservices. The tutorial also covers the integration of Spring Boot Actuator's inbuilt probes and demonstrates configuring these probes in a deployment YAML file. Finally, it shows how to switch application versions without downtime by leveraging these probes.

What is the primary purpose of using liveness and readiness probes in Kubernetes?

• To enhance the security of the application

• To reduce the cost of cloud services

• To ensure high availability and manage traffic during application transitions

• To increase the speed of application deployment

How does Spring Boot Actuator assist with Kubernetes probes?

• It provides inbuilt endpoints for liveness and readiness checks

• It encrypts the application data

• It automatically scales the application

• It reduces the memory usage of the application

What is the role of the 'actuator' endpoint in Spring Boot?

• To manage application security settings

• To expose health and metrics information

• To configure application logging

• To provide a user interface for the application

Which HTTP method is used to configure a readiness probe in Kubernetes?

• PUT

• POST

• GET

• DELETE

What happens if a liveness probe fails in Kubernetes?

• The traffic is redirected to another service

• The pod is restarted

• The application is scaled up

• The application is moved to a different node

During a version upgrade, when does Kubernetes terminate the old version of a pod?

• When the new version is ready to receive traffic

• After a fixed time interval

• As soon as the new version is deployed

• When the old version fails

What is the significance of the 'diff' command in the context of Kubernetes deployment?

• It shows the differences between the current and previous deployments

• It deletes the old deployment

• It scales the deployment

• It updates the deployment to the latest version