You are developing a deep learning model that requires high-performance access to large volumes of media data currently stored in Cloud Storage. Model training will be executed on multiple VM instances with GPUs attached, but your application must interact with the data as if it were on the local file system. You need to minimize complexity and cost. What should you do?

• A.Use the gsutil command line tool to download the data to your VM instances.
• B.Copy the data from Cloud Storage to Filestore, and then mount the Filestore volume as a local file system on your VM instances.
• C.Create a shared persistent disk, attach the disk to your VM instances, and load data from the Cloud Storage bucket.
• D.Use the gcsfuse command line tool to mount the Cloud Storage bucket as a local file system, and perform read/write operations in your bucket using standard file system semantics.

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You are analyzing and defining business processes to support your startup's trial usage of GCP, and you don't yet know what consumer demand for your product will be. Your manager requires you to minimize GCP service costs and adhere to Google best practices. What should you do?

• A.Utilize free tier and sustained use discounts. Provision a staff position for service cost management.
• B.Utilize free tier and sustained use discounts. Provide training to the team about service cost management.
• C.Utilize free tier and committed use discounts. Provision a staff position for service cost management.
• D.Utilize free tier and committed use discounts. Provide training to the team about service cost management.

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You manage a highly distributed, hybrid- and multi-cloud IT environment, and your developers rely heavily on Prometheus for their workflows. You need a cloud-based, highly scalable, low- maintenance enterprise solution that supports Prometheus Query Language (PromQL) queries, quick metric viewing, and efficient issue diagnosis. What should you do?

• A.Deploy a Prometheus operator in your existing Kubernetes and Serverless setup across multi- cloud environments.
• B.Set up Cloud Monitoring as a single pane of glass across multi-cloud environments.
• C.Enable Google Cloud Managed Service for Prometheus to monitor and alert on your workloads at scale.
• D.Build a SaaS-based, Prometheus-compatible solution to display metrics for each cloud in a customizable way.

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You are a cloud architect for a healthcare organization that is running its containerized, stateless web applications on Google Kubernetes Engine (GKE) with Autoscaler enabled. These customer-facing services have a strict 99.5% availability requirement. You also run nightly batch processing jobs for data analysis that are fault-tolerant and can be stopped and restarted. You need to ensure the solution meets the availability SLA while minimizing compute costs wherever possible. What should you do?

• A.Create two separate GKE node pools. Use a node pool of Standard VMs for the web applications and another node pool of Spot VMs for the batch jobs.
• B.Create two separate GKE node pools using Standard VMs for both. Purchase one-year committed use discounts (CUDs) for the resources in the batch processing node pool.
• C.Configure the GKE cluster with a single node pool of Standard VMs to run both workloads.
• D.Create two separate GKE node pools. Use a node pool with Spot VMs for the web applications and a node pool with Standard VMs for the batch jobs.

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Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling. Which two compute products should you choose? Choose 2 answers

• A.Compute Engine with containers
• B.Google Kubernetes Engine with containers
• C.Google App Engine Standard Environment
• D.Compute Engine with custom instance types
• E.Compute Engine with managed instance groups

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