You are using Cloud Build to build and test application source code stored in Cloud Source Repositories. The
build process requires a build tool not available in the Cloud Build environment.
What should you do?
A. Download the binary from the internet during the build process.
B. Build a custom cloud builder image and reference the image in your build steps.
C. Include the binary in your Cloud Source Repositories repository and reference it in your build scripts.
D. Ask to have the binary added to the Cloud Build environment by filing a feature request against the Cloud Build public Issue Tracker.
You are writing a Compute Engine hosted application in project A that needs to securely authenticate to a Cloud Pub/Sub topic in project B. What should you do?
A. Configure the instances with a service account owned by project B. Add the service account as a Cloud Pub/Sub publisher to project A.
B. Configure the instances with a service account owned by project A. Add the service account as a publisher on the topic.
C. Configure Application Default Credentials to use the private key of a service account owned by project B. Add the service account as a Cloud Pub/Sub publisher to project A.
D. Configure Application Default Credentials to use the private key of a service account owned by project A. Add the service account as a publisher on the topic
You work for a web development team at a small startup. Your team is developing a Node.js application using Google Cloud services, including Cloud Storage and Cloud Build. The team uses a Git repository for version control. Your manager calls you over the weekend and instructs you to make an emergency update to one of the company's websites, and you're the only developer available. You need to access Google Cloud to make the update, but you don't have your work laptop. You are not allowed to store source code locally on a non-corporate computer. How should you set up your developer environment?
A. Use a text editor and the Git command line to send your source code updates as pull requests from a public computer.
B. Use a text editor and the Git command line to send your source code updates as pull requests from a virtual machine running on a public computer.
C. Use Cloud Shell and the built-in code editor for development. Send your source code updates as pull requests.
D. Use a Cloud Storage bucket to store the source code that you need to edit. Mount the bucket to a public computer as a drive, and use a code editor to update the code. Turn on versioning for the bucket, and point it to the team's Git repository.
You are designing an application that uses a microservices architecture. You are planning to deploy the application in the cloud and on-premises. You want to make sure the application can scale up on demand and also use managed
services as much as possible.
What should you do?
A. Deploy open source Istio in a multi-cluster deployment on multiple Google Kubernetes Engine (GKE) clusters managed by Anthos.
B. Create a GKE cluster in each environment with Anthos, and use Cloud Run for Anthos to deploy your application to each cluster.
C. Install a GKE cluster in each environment with Anthos, and use Cloud Build to create a Deployment for your application in each cluster.
D. Create a GKE cluster in the cloud and install open-source Kubernetes on-premises. Use an external load balancer service to distribute traffic across the two environments.
You are developing an application that will allow users to read and post comments on news articles. You want to configure your application to store and display user-submitted comments using Firestore. How should you design the schema to support an unknown number of comments and articles?
A. Store each comment in a subcollection of the article.
B. Add each comment to an array property on the article.
C. Store each comment in a document, and add the comment's key to an array property on the article.
D. Store each comment in a document, and add the comment's key to an array property on the user profile.
You manage an application that runs in a Compute Engine instance. You also have multiple backend services executing in stand-alone Docker containers running in Compute Engine instances. The Compute Engine instances supporting the backend services are scaled by managed instance groups in multiple regions. You want your calling application to be loosely coupled. You need to be able to invoke distinct service implementations that are chosen based on the value of an HTTP header found in the request. Which Google Cloud feature should you use to invoke the backend services?
A. Traffic Director
B. Service Directory
C. Anthos Service Mesh
D. Internal HTTP(S) Load Balancing
You recently developed a new application. You want to deploy the application on Cloud Run without a Dockerfile. Your organization requires that all container images are pushed to a centrally managed container repository. How should you build your container using Google Cloud services? (Choose two.)
A. Push your source code to Artifact Registry.
B. Submit a Cloud Build job to push the image.
C. Use the pack build command with pack CLI.
D. Include the --source flag with the gcloud run deploy CLI command.
E. Include the --platform=kubernetes flag with the gcloud run deploy CLI command.
You are configuring a continuous integration pipeline using Cloud Build to automate the deployment of new container images to Google Kubernetes Engine (GKE). The pipeline builds the application from its source code, runs unit and integration tests in separate steps, and pushes the container to Container Registry. The application runs on a Python web server.
The Dockerfile is as follows: FROM python:3.7-alpine COPY . /app WORKDIR /app RUN pip install -r requirements.txt CMD [ "gunicorn", "-w 4", "main:app" ] You notice that Cloud Build runs are taking longer than expected to complete. You want to decrease the build time. What should you do? (Choose two.)
A. Select a virtual machine (VM) size with higher CPU for Cloud Build runs.
B. Deploy a Container Registry on a Compute Engine VM in a VPC, and use it to store the final images.
C. Cache the Docker image for subsequent builds using the -- cache-from argument in your build config file.
D. Change the base image in the Dockerfile to ubuntu:latest, and install Python 3.7 using a package manager utility.
E. Store application source code on Cloud Storage, and configure the pipeline to use gsutil to download the source code.
You are load testing your server application. During the first 30 seconds, you observe that a previously inactive Cloud Storage bucket is now servicing 2000 write requests per second and 7500 read requests per second. Your application is now receiving intermittent 5xx and 429 HTTP responses from the Cloud Storage JSON API as the demand escalates. You want to decrease the failed responses from the Cloud Storage API. What should you do?
A. Distribute the uploads across a large number of individual storage buckets.
B. Use the XML API instead of the JSON API for interfacing with Cloud Storage.
C. Pass the HTTP response codes back to clients that are invoking the uploads from your application.
D. Limit the upload rate from your application clients so that the dormant bucket's peak request rate is reached more gradually.
You are planning to add unit tests to your application. You need to be able to assert that published Pub/Sub messages are processed by your subscriber in order. You want the unit tests to be cost-effective and reliable. What should you do?
A. Implement a mocking framework.
B. Create a topic and subscription for each tester.
C. Add a filter by tester to the subscription.
D. Use the Pub/Sub emulator.
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