SOA-C02 · Question #679
A company has implemented a Kubernetes cluster on Amazon Elastic Kubernetes Service (Amazon EKS) to host a microservices-based application. The company expects application traffic to increase…
The correct answer is B. Implement the Kubernetes Horizontal Pod Autoscaler. Set a target CPU utilization percentage. The Kubernetes Horizontal Pod Autoscaler (HPA) automatically scales the number of pods in a Deployment, ReplicaSet, or StatefulSet based on CPU utilization (or other custom metrics). This ensures that the application can handle increased traffic dynamically without manual…
Question
A company has implemented a Kubernetes cluster on Amazon Elastic Kubernetes Service (Amazon EKS) to host a microservices-based application. The company expects application traffic to increase significantly for the next month and wants to prevent the application from crashing because of the high number of requests. Which solution will meet these requirements with the LEAST administrative overhead?
Options
- ACreate a second EKS cluster. Load balance the workload between the two clusters.
- BImplement the Kubernetes Horizontal Pod Autoscaler. Set a target CPU utilization percentage.
- CMigrate the application from Amazon EKS to Amazon EC2 for the next month. Migrate the
- DImplement the Kubernetes Vertical Pod Autoscaler. Set a target CPU utilization percentage.
How the community answered
(55 responses)- A5% (3)
- B84% (46)
- C2% (1)
- D9% (5)
Explanation
The Kubernetes Horizontal Pod Autoscaler (HPA) automatically scales the number of pods in a Deployment, ReplicaSet, or StatefulSet based on CPU utilization (or other custom metrics). This ensures that the application can handle increased traffic dynamically without manual intervention. HPA scales pods horizontally, meaning it adds or removes pods as needed to match demand. Minimal administrative overhead, as scaling is automated based on resource utilization. EKS natively supports HPA, making it the most efficient and cost-effective solution.
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