Answer-first summary for fast verification
Answer: Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster. Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.
The question requires a load testing solution that uses multiple source IPs, parallel threads, and scalable test instances. Option C suggests using a distributed load testing framework on GKE, which aligns with Google's best practices. GKE allows scaling Pods to increase traffic, and if the cluster autoscales nodes, each new node adds a unique IP address. This approach ensures traffic originates from multiple IPs and scales efficiently. Options A and B rely on instance groups with cURL, which lacks the sophistication of a dedicated framework. Option D uses Cloud Shell, which cannot scale effectively or provide multiple IPs. Thus, Option C is the recommended best practice.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
How should you configure load testing for a set of REST API endpoints deployed on Cloud Run that respond to HTTP POST requests, while meeting the following requirements: initiating load from multiple parallel threads, generating user traffic from multiple source IP addresses, and enabling scalability with additional test instances, following Google-recommended best practices?
A
Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in a managed instance group, and run one instance of the image for each VM.
B
Create an image that has cURL installed, and configure cURL to run a test plan. Deploy the image in an unmanaged instance group, and run one instance of the image for each VM.
C
Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster. Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.
D
Download the container image of a distributed load testing framework on Cloud Shell. Sequentially start several instances of the container on Cloud Shell to increase the load on the API.