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TerramEarth has a legacy web application that you cannot migrate to cloud. However, you still want to build a cloud-native way to monitor the application. If the application goes down, you want the URL to point to a " Site is unavailable " page as soon as possible. You also want your Ops team to receive a notification for the issue. You need to build a reliable solution for minimum cost

What should you do?

A.

Create a scheduled job in Cloud Run to invoke a container every minute. The container will check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

B.

Create a cron job on a Compute Engine VM that runs every minute. The cron job invokes a Python program to check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

C.

Create a Cloud Monitoring uptime check to validate the application URL If it fails, put a message in a Pub/Sub queue that triggers a Cloud Function to switch the URL to the " Site is unavailable " page, and notify the Ops team.

D.

Use Cloud Error Reporting to check the application URL If the application is down, switch the URL to the " Site is unavailable " page, and notify the Ops team.

TerramEarth has about 1 petabyte (PB) of vehicle testing data in a private data center. You want to move the data to Cloud Storage for your machine learning team. Currently, a 1-Gbps interconnect link is available for you. The machine learning team wants to start using the data in a month. What should you do?

A.

Request Transfer Appliances from Google Cloud, export the data to appliances, and return the appliances to Google Cloud.

B.

Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage

C.

Make sure there are no other users consuming the 1 Gbps link, and use multi-thread transfer to upload the data to Cloud Storage.

D.

Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data to Cloud Storage

For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?

A.

Replace the existing data warehouse with BigQuery. Use table partitioning.

B.

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.

C.

Replace the existing data warehouse with BigQuery. Use federated data sources.

D.

Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.

For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?

A.

Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.

B.

Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi-Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.

C.

Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a MultiRegional Cloud Storage

bucket. Upload this data into BigQuery using gcloud. Use Google data Studio for analysis and reporting.

D.

Use Cloud Dataproc Hive as the data warehouse. Directly stream data into prtitioned Hive tables. Use Pig scripts to analyze data.

For this question, refer to the TerramEarth case study. TerramEarth has decided to store data files in Cloud Storage. You need to configure Cloud Storage lifecycle rule to store 1 year of data and minimize file storage cost.

Which two actions should you take?

A.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Standard”, and Action: “Set to Coldline”, and create a second GCS life-cycle rule with Age: “365”, Storage Class: “Coldline”, and Action: “Delete”.

B.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Coldline”, and Action: “Set to Nearline”, and create a second GCS life-cycle rule with Age: “91”, Storage Class: “Coldline”, and Action: “Set to Nearline”.

C.

Create a Cloud Storage lifecycle rule with Age: “90”, Storage Class: “Standard”, and Action: “Set to Nearline”, and create a second GCS life-cycle rule with Age: “91”, Storage Class: “Nearline”, and Action: “Set to Coldline”.

D.

Create a Cloud Storage lifecycle rule with Age: “30”, Storage Class: “Standard”, and Action: “Set to Coldline”, and create a second GCS life-cycle rule with Age: “365”, Storage Class: “Nearline”, and Action: “Delete”.

For this question, refer to the TerramEarth case study.

You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google ' s recommended best practices. What should you do?

A.

Create a token and pass it in as an environment variable to func_display. When invoking func_query, include the token in the request Pass the same token to func _query and reject the invocation if the tokens are different.

B.

Make func_query ' Require authentication. ' Create a unique service account and associate it to func_display. Grant the service account invoker role for func_query. Create an id token in func_display and include the token to the request when invoking func_query.

C.

Make func _query ' Require authentication ' and only accept internal traffic. Create those two functions in the same VPC. Create an ingress firewall rule for func_query to only allow traffic from func_display.

D.

Create those two functions in the same project and VPC. Make func_query only accept internal traffic. Create an ingress firewall for func_query to only allow traffic from func_display. Also, make sure both functions use the same service account.

For this question, refer to the Mountkirk Games case study.

Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:

• Services are deployed redundantly across multiple regions in the US and Europe.

• Only frontend services are exposed on the public internet.

• They can provide a single frontend IP for their fleet of services.

• Deployment artifacts are immutable.

Which set of products should they use?

A.

Google Cloud Storage, Google Cloud Dataflow, Google Compute Engine

B.

Google Cloud Storage, Google App Engine, Google Network Load Balancer

C.

Google Kubernetes Registry, Google Container Engine, Google HTTP(S) Load Balancer

D.

Google Cloud Functions, Google Cloud Pub/Sub, Google Cloud Deployment Manager

For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to migrate from their current analytics and statistics reporting model to one that meets their technical requirements on Google Cloud Platform.

Which two steps should be part of their migration plan? (Choose two.)

A.

Evaluate the impact of migrating their current batch ETL code to Cloud Dataflow.

B.

Write a schema migration plan to denormalize data for better performance in BigQuery.

C.

Draw an architecture diagram that shows how to move from a single MySQL database to a MySQL cluster.

D.

Load 10 TB of analytics data from a previous game into a Cloud SQL instance, and run test queries against the full dataset to confirm that they complete successfully.

E.

Integrate Cloud Armor to defend against possible SQL injection attacks in analytics files uploaded to Cloud Storage.

For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend Platform architecture. The game communicates with the backend over a REST API.

You want to follow Google-recommended practices. How should you design the backend?

A.

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L4 load balancer.

B.

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L4 load balancer.

C.

Create an instance template for the backend. For every region, deploy it on a multi-zone managed instance group. Use an L7 load balancer.

D.

Create an instance template for the backend. For every region, deploy it on a single-zone managed instance group. Use an L7 load balancer.

For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to design their solution for the future in order to take advantage of cloud and technology improvements as they become available. Which two steps should they take? (Choose two.)

A.

Store as much analytics and game activity data as financially feasible today so it can be used to train machine learning models to predict user behavior in the future.

B.

Begin packaging their game backend artifacts in container images and running them on Kubernetes Engine to improve the availability to scale up or down based on game activity.

C.

Set up a CI/CD pipeline using Jenkins and Spinnaker to automate canary deployments and improve development velocity.

D.

Adopt a schema versioning tool to reduce downtime when adding new game features that require storing additional player data in the database.

E.

Implement a weekly rolling maintenance process for the Linux virtual machines so they can apply critical kernel patches and package updates and reduce the risk of 0-day vulnerabilities.