Migrating Development Infrastructure to Google Cloud for Cost Efficiency and Finance Visibility

Migrating Development Infrastructure to Google Cloud

Question

To reduce costs, the Director of Engineering has required all developers to move their development infrastructure resources from on-premises virtual machines (VMs) to Google Cloud Platform.

These resources go through multiple start/stop events during the day and require state to persist.

You have been asked to design the process of running a development environment in Google Cloud while providing cost visibility to the finance department.

Which two steps should you take? (Choose two.)

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D. E. F.

AD.

The question describes a scenario where developers are required to move their development infrastructure resources from on-premises VMs to Google Cloud Platform (GCP) to reduce costs. The resources go through multiple start/stop events during the day and require state to persist. The challenge is to design a process of running a development environment in GCP while providing cost visibility to the finance department.

There are two steps that can be taken to address this challenge, which are described below:

  1. Use the --no-auto-delete flag on all persistent disks and stop the VM Option A suggests using the --no-auto-delete flag on all persistent disks and stopping the VM instead of terminating it. This approach ensures that the data stored in the persistent disks is not deleted when the VM is stopped, and the state is preserved for the next start. By stopping the VM instead of terminating it, developers can quickly resume their work from where they left off, without having to recreate their environment. This approach also enables cost savings by avoiding the need to recreate the environment from scratch every time developers start working.

  2. Use Google BigQuery billing export and labels to associate cost to groups Option D suggests using Google BigQuery billing export and labels to associate costs with groups. By applying VM CPU utilization labels and including them in the BigQuery billing export, the finance department can get visibility into the cost associated with each group of resources. This approach enables accurate cost allocation and provides developers with visibility into the cost of their environment. By associating costs with groups, the finance department can identify areas where cost optimization can be applied.

In summary, the recommended approach is to use the --no-auto-delete flag on all persistent disks and stop the VM instead of terminating it to preserve the state of the environment, and use Google BigQuery billing export and labels to associate costs with groups for accurate cost allocation and optimization. Option A and Option D are the correct answers to the question.

Options B and E are incorrect because terminating the VM or storing the state into local SSD would result in the loss of data, which is not desirable in this scenario. Option C is incorrect because it only provides visibility into CPU utilization, which is not sufficient to associate costs with groups accurately. Option F is incorrect because storing state in Google Cloud Storage and snapshotting the persistent disks can be costly, and it does not address the issue of associating costs with groups.