Exam Associate Cloud Engineer topic 1 question 218 discussion

B. Migrating the workload to a Compute Engine VM and starting and stopping the instance as needed allows you to control when the task runs. This approach provides flexibility in terms of when to initiate the batch process, and it can be easily scheduled to run monthly. By stopping the instance when the task is not running, you can save on compute costs.

D is correct

B. is correct. shreykul provided you the correct answer, take it or leave it.

It seems to me that answer is A. Scale to zero - After completed batch processes, minimize cost. Spot VM - minimize cost. failure resistant - do not need restart instance. You already have a template - delete and deploy your Compute instances once a month easily and fast. Can you explain me unless I understand some thing.

A is the most robust and cost-effective for your scenario. This setup leverages the cost savings of Spot VMs while also providing the ability to handle interruptions through a Managed Instance Group, ensuring the process is completed even if individual instances are preempted. Additionally, the automatic scaling based on CPU utilization helps manage resources efficiently, further reducing costs. Thus, A not only minimizes costs by using Spot VMs but also enhances reliability and scalability through a Managed Instance Group, making it the most suitable choice for migrating your batch process to the cloud.

I don´t like this kind of questions... but I think is A.. An Instance Template with Spot VMs (not preemptible)...

Same as 136

I don't believe Spot VMs are the best solution here since they can be preempted by Google at any time. Option B prioritizes predictable execution and cost optimization for this scheduled batch process. It balances cost-savings with the need for guaranteed completion, aligning well with the provided scenario.

Spot VM best practices

Spot VM best practices

Spot VM best practices

An Instance Template with Spot VMs in a Managed Instance Group (MIG) has no 24-hour limitation, can restart via the MIG if interrupted, and offers low costs, making it a perfect match.

Per ChatGPT, Option A is the most appropriate solution as it leverages the cost benefits of Spot VMs, provides scalability through Managed Instance Groups, and aligns with the characteristics of the workload, resulting in minimized cost for running the batch process in the cloud.

https://cloud.google.com/compute/docs/instances/create-use-spot#best-practices Spot VM best practices create an instance template and Spot VM does not have a minimum or maximum runtime to there is no 24 hour limit as suggested by some.

D https://cloud.google.com/compute/docs/instances/spot#limitations Spot VMs are unlike Preemptible VMs (https://cloud.google.com/compute/docs/instances/preemptible#limitations) , which do not stop after 24 hours. And we can re-start the batch job in case if it gets stopped in between as per the question. So D is the best cost optimal solution.

Answer B. Spot VMs are not suitable for batch processes that take an extended period of time to complete, such as a 30-hour batch process. Spot VMs typically have a maximum runtime of 24 hours.

I had this question in my exam. There was Spot VM option available, but I still picked manual starting/stopping as job is not fault tolerant.