Master Microservices with Spring Boot and Spring Cloud - Step 27 – Autoscaling Microservices with Kubernetes

The video tutorial explains how to implement autoscaling in Kubernetes using the Horizontal Pod Autoscaler (HPA). It begins with an introduction to autoscaling, followed by a comparison with manual scaling. The tutorial then provides a step-by-step guide to setting up autoscaling based on CPU utilization, including configuring minimum and maximum pod limits. It also covers monitoring the autoscaling process and demonstrates how to revert changes and clean up resources. The tutorial emphasizes the ease of using HPA for efficient resource management in Kubernetes.

What is the main drawback of manual scaling in Kubernetes?

• It does not allow for any scaling.

• It requires constant monitoring and manual intervention.

• It automatically adjusts the number of pods.

• It is more efficient than autoscaling.

Which command is used to set up autoscaling in Kubernetes?

• kubectl apply

• kubectl scale

• kubectl autoscale

• kubectl deploy

What parameter is typically used to decide when to scale up in a production environment?

• CPU percentage

• Network bandwidth

• Memory usage

• Disk space

What is the role of a Horizontal Pod Autoscaler in Kubernetes?

• To monitor network traffic

• To manually scale the number of pods

• To automatically adjust the number of pods based on load

• To deploy new applications

How can you check the CPU utilization of pods in Kubernetes?

• kubectl get pods

• kubectl logs

• kubectl describe pods

• kubectl top pod

What happens to the additional pods when the Horizontal Pod Autoscaler is deleted?

• They are automatically scaled up.

• They continue running until manually scaled down.

• They are immediately terminated.

• They are converted to services.

Which command is used to revert the deployment to its original configuration?

• kubectl apply

• kubectl delete

• kubectl revert

• kubectl reset