Exam Associate Cloud Engineer topic 1 question 175 discussion

I was a little unsure about this question, here's how I understand why D is the best answer A. Custom Resource Definition... we have docker containers already, which is an established kind of resource for Kubernetes. We don't need to create a whole new type of resource, so this is wrong. B. Docker Compose is a wholly different tool from Kubernetes. C. A Kubernetes job describes a specific "task" which involves a bunch of pods and things. It makes no sense to have one job per microservice, a "Job" would be a bunch of different microservices executing together. D. is the leftover, correct answer. You can add scaling to each Deployment, an important aspect of the question.

D is the correct answer

To deploy a microservices-based application on Google Kubernetes Engine (GKE), it's common to create and deploy a Deployment per microservice. D. Create and deploy a Deployment per microservice. Here's why: Deployment: In Kubernetes, a Deployment is a resource that allows you to define, create, and manage the desired number of replicas of your application. Each microservice can be independently managed and scaled using its own Deployment. This approach provides the flexibility to scale individual microservices as needed and manage their lifecycle effectively. Each microservice will have its own set of pods that can be scaled up or down independently, making it suitable for a microservices architecture.

D is the corrrect answer

D is the correct answer.

D seems more correct , as in A , we already have the own docker container image , so no need to create , b is completely diffenret tool, c is also of no use

D, keyword "each microservice can be scaled individually"!

D is the correct answer

D is the best answer among other choices.

D is right! It's one of Googles main ideas to distribute a complex system into microservices. They do it as well and encourage customers to do the same.

D is the Answer

Ans: D

Yes. D is correct. Can deploy each service through kubectl apply -f <deployment_config.yaml>

D is the correct answer

D is correct

D is the answer