TerramEarth

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?

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You have broken down a legacy monolithic application into a few containerized RESTful microservices. You want to run those microservices on Cloud Run. You also want to make sure the services are highly available with low latency to your customers. What should you do?

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What should you do? (Choose two.)

• Open a support case regarding the CVE and chat with the support engineer.

• Read the CVEs from the Google Cloud Status Dashboard to understand the impact.
  

• Read the CVEs from the Google Cloud Platform Security Bulletins to understand the impact.

• Post a question regarding the CVE in Stack Overflow to get an explanation.

• Post a question regarding the CVE in a Google Cloud discussion group to get and explanation

What should you do?

• 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.

• 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.

• 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.

• 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.

You are building a microservice-based application for TerramEarth. The application is based on Docker containers. You want to follow Google-recommended practices to build the application continuously and store the build artifacts. What should you do?

• Configure a trigger in Cloud Build for new source changes. Invoke Cloud Build to build container images for each microservice, and tag them using the code commit hash. Push the images to the Container Registry.

• Configure a trigger in Cloud Build for new source changes. The trigger invokes build jobs and build container images for the microservices. Tag the images with a version number, and push them to Cloud Storage.

• Create a Scheduler job to check the repo every minute. For any new change, invoke Cloud Build to build container images for the microservices. Tag the images using the current timestamp, and push them to the Container Registry.

• Configure a trigger in Cloud Build for new source changes. Invoke Cloud Build to build one container image, and tag the image with the label 'latest.' Push the image to the Container Registry.

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?

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

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

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

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