Which of the following are the main advantages of using ML/AI for data analytics in the cloud as opposed to on premises? (Choose two.)

Elasticity allows access to a large pool of compute resources.

A pay-as-you-go approach allows the company to save money.

Cloud providers offer enhanced technical support.

Elasticity allows access to a large pool of compute resources.

The shared responsibility model offers greater security.

AI enables DevOps to build applications easier and faster.

A pay-as-you-go approach allows the company to save money.

ML enables DevOps to build applications easier and faster.

A cloud administrator suggested using spot instances to reduce cloud costs for part of a new cloud infrastructure.Which of the following conditions must be addressed by the application that will run on these instances?

The application needs to handle unpredictable instance termination.

The application needs to store data in a database.

There is a restriction for distributed network communications.

The application needs to handle unpredictable instance termination.

Resource-intensive compute loads will be forbidden.

Transferring all of a customer's on-premises data and virtual machines to an appliance, and then shipping it to a cloud provider is a technique used in a:

replatforming migration approach.

rip and replace migration approach.

lift and shift migration approach.

A mobile application development team requires frequent software updates for a major launch of a customer-facing application. The business requirement is to be first-to-market on a new feature that leverages third-party-hosted services.Which of the following is the BEST approach to use for speed and efficiency?

Application programming interface

Which of the following are true about the use of machine learning in a cloud environment? (Choose two).

Specialized machine learning algorithms can be deployed to optimize results for specific scenarios.

Machine learning can leverage processes in a cloud environment through the use of cloud storage and auto-scaling.

Specialized machine learning algorithms can be deployed to optimize results for specific scenarios.

Machine learning can just be hosted in the cloud for managed services.

Just one type of cloud storage is available in the cloud for machine learning workloads.

Machine learning can leverage processes in a cloud environment through the use of cloud storage and auto-scaling.

Machine learning requires a specialized IT team to create the machine learning models from scratch.

Using machine learning solutions in the cloud removes the data-gathering step from the learning process.

CompTIA CLO-002 Practice Test 1 - Free Online Exam Prep & Questions

A company is moving to the cloud and wants to enhance the provisioning of compute, storage, security, and networking. Which of the following will be leveraged?

Infrastructure as code

Infrastructure templates

Infrastructure orchestration

Infrastructure automation

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