PROFESSIONAL-CLOUD-DEVELOPER · Question #272
You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests. Your load tests must meet the following requirements: - Load is initiated from
The correct answer is C. Deploy a distributed load testing framework on a private Google Kubernetes Engine cluster.. Deploying a distributed load testing framework (such as Locust or JMeter) on a private GKE cluster is the Google-recommended approach for load testing Cloud Run services. GKE satisfies all three requirements: each pod runs parallel threads, each pod gets its own cluster IP so tra
Question
You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests. Your load tests must meet the following requirements:
- Load is initiated from multiple parallel threads.
- User traffic to the API originates from multiple source IP addresses.
- Load can be scaled up using additional test instances.
You want to follow Google-recommended best practices. How should you configure the load testing?
Options
- ACreate an image that has cURL installed, and configure cURL to run a test plan. Deploy the
- BCreate an image that has cURL installed, and configure cURL to run a test plan. Deploy the
- CDeploy a distributed load testing framework on a private Google Kubernetes Engine cluster.
- DDownload the container image of a distributed load testing framework on Cloud Shell.
How the community answered
(48 responses)- A13% (6)
- B6% (3)
- C79% (38)
- D2% (1)
Explanation
Deploying a distributed load testing framework (such as Locust or JMeter) on a private GKE cluster is the Google-recommended approach for load testing Cloud Run services. GKE satisfies all three requirements: each pod runs parallel threads, each pod gets its own cluster IP so traffic originates from multiple source IPs, and you can scale the number of worker pods or nodes to increase load. Options A and B (cURL-based images) are not purpose-built distributed load testing solutions and do not scale well. Option D (Cloud Shell) is ephemeral and single-instance, making it unsuitable for scalable distributed load generation.
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