Google Professional Cloud DevOps Engineer Question 233
Select 3Google Cloud PlatformYou are managing a web application deployed on Google Kubernetes Engine (GKE) that experiences highly variable traffic throughout the day. You want to ensure the application scales efficiently to handle peak traffic while minimizing costs during low-traffic periods. Which scaling configurations should you implement?
- A
Enable Horizontal Pod Autoscaler (HPA) to automatically adjust the number of pods based on CPU or custom metrics.
- B
Set up a manually defined fixed number of replicas in your Deployment configuration.
- C
Configure Cluster Autoscaler to adjust the number of nodes in the cluster based on resource demands.
- D
Use Vertical Pod Autoscaler (VPA) to automatically adjust the CPU and memory requests/limits for running pods.
- E
Deploy a Managed Instance Group (MIG) instead of GKE to handle traffic spikes more effectively.
Show answer and explanation
Correct answers: A, C, D
Explanation
To efficiently handle variable traffic for a GKE-based application, combining Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler ensures that both pod-level and node-level scaling are dynamically managed based on resource demands. Additionally, Vertical Pod Autoscaler (VPA) optimizes resource utilization by adjusting pod resource requests and limits. These strategies together ensure cost efficiency and high availability, while manually defined replica counts and solutions like Managed Instance Groups are not appropriate in this scenario.
- A. Correct.
Correct: Horizontal Pod Autoscaler (HPA) is used in GKE to dynamically adjust the number of pods in a deployment based on CPU utilization, memory usage, or custom metrics, ensuring your application can handle traffic fluctuations effectively.
- B. Incorrect.
Incorrect: Manually defining a fixed number of replicas does not allow for automatic scaling, which is critical for efficiently handling variable traffic.
- C. Correct.
Correct: Cluster Autoscaler complements HPA by scaling the number of nodes in the cluster up or down based on the resource demands of pods, ensuring that the cluster has enough capacity for scaling.
- D. Correct.
Correct: Vertical Pod Autoscaler (VPA) optimizes resource usage by automatically adjusting resource requests and limits for pods. This is especially useful for workloads with fluctuating resource needs.
- E. Incorrect.
Incorrect: While Managed Instance Groups (MIGs) are an effective autoscaling solution for Compute Engine, they are not relevant to a GKE-based workload, which uses Kubernetes-native scaling mechanisms like HPA and Cluster Autoscaler.