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NEW QUESTION # 42
Your team is working on a project to deploy a microservices-based application on a cloud platform using Terraform. Each microservice has specific configurations and dependencies, and you want to ensure modularity, reusability, and consistency across deployments.
Which Terraform feature would you use to achieve these objectives efficiently?
Answer: D
Explanation:
Terraform Modules are used to organize and group related configuration resources into reusable components. By using modules, you can achieve modularity, reusability, and consistency across different deployments, making it easier to manage complex infrastructure setups.
For a microservices-based application, where each microservice has specific configurations and dependencies, modules allow you to define the infrastructure for each microservice in a modular way. This helps to maintain clean, reusable code and ensures consistency across deployments.
NEW QUESTION # 43
How do OCI DevOps Deployment Pipelines reduce risk and complexity of production applications?
Answer: A
Explanation:
OCI DevOps Deployment Pipelines automate the process of deploying applications to production environments. By using automated, repeatable deployment processes, they help reduce the risk of change-driven errors, which are often introduced during manual deployments. This automation reduces human errors and ensures consistency across environments, thus minimizing complexity and risk in production.
NEW QUESTION # 44
A team wants to deploy artificial intelligence and machine learning workloads in their OCI Container Engine for Kubernetes (OKE) cluster. They prioritize strong isolation, cost-efficiency, and the ability to leverage serverless capabilities.
Which solution is best suited for their requirements?
Answer: A
Explanation:
Virtual nodes in OKE provide a serverless experience for deploying Kubernetes workloads, which means you do not have to manage or scale the underlying infrastructure. This solution is particularly cost-efficient because you only pay for the resources used by the pods, and it provides strong isolation for workloads.
Virtual nodes are well suited for AI/ML workloads as they allow users to easily scale compute resources without being constrained by the limits of individual worker nodes.
NEW QUESTION # 45
How can you run applications on GPU worker nodes in clusters created using Container Engine for Kubernetes (OKE)?
Answer: D
Explanation:
To run applications on GPU worker nodes in Oracle Kubernetes Engine (OKE), you need to:
Select a managed node pool and choose a GPU shape for the worker nodes.
Use a GPU image that has the necessary CUDA libraries pre-installed to ensure that GPU workloads can be executed properly.
In the pod specification, specify the number of GPU resources required for the container to utilize the GPU hardware during execution. This allows Kubernetes to schedule the pod on a node with an available GPU.
NEW QUESTION # 46
As a DevOps engineer working on managing clusters on the OCI platform for your organization, which statement is true about managing cluster add-ons in OCI OKE Cluster?
Answer: B
Explanation:
Essential cluster add-ons are required for the basic functioning of the Kubernetes cluster and cannot be disabled during cluster creation. These add-ons provide necessary features such as core DNS, networking, and other critical functionalities for the cluster's operation.
NEW QUESTION # 47
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