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Associate-Cloud-Engineer – Associate Cloud Engineer

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Showing 7–9 of 10 questions

Question 7

You have a single binary application that you want to run on Google Cloud Platform. You decided to automatically scale the application based on underlying infrastructure CPU usage. Your organizational policies require you to use virtual machines directly. You need to ensure that the application scaling is operationally efficient and completed as quickly as possible. What should you do?

Select an option, then click Submit answer.

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    Create a Google Kubernetes Engine cluster, and use horizontal pod autoscaling to scale the application.
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    Create an instance template, and use the template in a managed instance group with autoscaling configured.
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    Create an instance template, and use the template in a managed instance group that scales up and down based on the time of day.
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    Use a set of third-party tools to build automation around scaling the application up and down, based on Stackdriver CPU usage monitoring.
Question 8

Your organization has strict requirements to control access to Google Cloud projects. You need to enable your Site Reliability Engineers (SREs) to approve requests from the Google Cloud support team when an SRE opens a support case. You want to follow Google-recommended practices. What should you do?

Select an option, then click Submit answer.

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    Add your SREs to roles/iam.roleAdmin role.
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    Add your SREs to roles/accessapproval.approver role.
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    Add your SREs to a group and then add this group to roles/iam.roleAdmin.role.
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    Add your SREs to a group and then add this group to roles/accessapproval.approver role.
Question 9

You want to run a single caching HTTP reverse proxy on GCP for a latency-sensitive website. This specific reverse proxy consumes almost no CPU. You want to have a 30-GB in-memory cache, and need an additional 2 GB of memory for the rest of the processes. You want to minimize cost. How should you run this reverse proxy?

Select an option, then click Submit answer.

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    Create a Cloud Memorystore for Redis instance with 32-GB capacity.
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    Run it on Compute Engine, and choose a custom instance type with 6 vCPUs and 32 GB of memory.
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    Package it in a container image, and run it on Kubernetes Engine, using n1-standard-32 instances as nodes.
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    Run it on Compute Engine, choose the instance type n1-standard-1, and add an SSD persistent disk of 32 GB.