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WorksheetsGoogle Professional Architect 8 - 141 to 160
Total questions: 20
Worksheet time: 20mins
Name
Class
Date
1.
Your company is developing a web-based application. You need to make sure that production deployments are linked to source code commits and are fully auditable. What should you do?
a)
Make sure a developer is tagging the code commit with the date and time of commit.
b)
Make sure a developer is adding a comment to the commit that links to the deployment.
c)
Make the container tag match the source code commit hash.
d)
Make sure the developer is tagging the commits with latest.
2.
An application development team has come to you for advice. They are planning to write and deploy an HTTP(S) API using Go 1.12. The API will have a very unpredictable workload and must remain reliable during peaks in traffic. They want to minimize operational overhead for this application. Which approach should you recommend?
a)
Develop the application with containers, and deploy to Google Kubernetes Engine.
b)
Develop the application for App Engine standard environment.
c)
Use a Managed Instance Group when deploying to Compute Engine.
d)
Develop the application for App Engine flexible environment, using a custom runtime.
3.
Your company is designing its data lake on Google Cloud and wants to develop different ingestion pipelines to collect unstructured data from different sources.
After the data is stored in Google Cloud, it will be processed in several data pipelines to build a recommendation engine for end users on the website. The structure of the data retrieved from the source systems can change at any time. The data must be stored exactly as it was retrieved for reprocessing purposes in case the data structure is incompatible with the current processing pipelines. You need to design an architecture to support the use case after you retrieve the data. What should you do?
a)
Send the data through the processing pipeline, and then store the processed data in a BigQuery table for reprocessing.
b)
Store the data in a BigQuery table. Design the processing pipelines to retrieve the data from the table.
c)
Send the data through the processing pipeline, and then store the processed data in a Cloud Storage bucket for reprocessing.
d)
Store the data in a Cloud Storage bucket. Design the processing pipelines to retrieve the data from the bucket.
4.
You are responsible for the Google Cloud environment in your company. Multiple departments need access to their own projects, and the members within each department will have the same project responsibilities. You want to structure your Google Cloud environment for minimal maintenance and maximum overview of
IAM permissions as each department's projects start and end. You want to follow Google-recommended practices. What should you do?
a)
Create a Google Group per department and add all department members to their respective groups. Grant each group the required IAM permissions for their respective projects.
b)
Create a folder per department and grant the respective members of the department the required IAM permissions at the folder level. Structure all projects for each department under the respective folders.
c)
Create a Google Group per department and add all department members to their respective groups. Create a folder per department and grant the respective group the required IAM permissions at the folder level. Add the projects under the respective folders.
d)
Grant all department members the required IAM permissions for their respective projects.
5.
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster. You have separate clusters for development, staging, and production. You have discovered that the team is able to deploy a Docker image to the production cluster without first testing the deployment in development and then staging. You want to allow the team to have autonomy but want to prevent this from happening. You want a Google Cloud solution that can be implemented quickly with minimal effort. What should you do?
a)
Configure a Kubernetes lifecycle hook to prevent the container from starting if it is not approved for usage in the given environment.
b)
Implement a corporate policy to prevent teams from deploying Docker images to an environment unless the Docker image was tested in an earlier environment.
c)
Configure binary authorization policies for the development, staging, and production clusters. Create attestations as part of the continuous integration pipeline.
d)
Create a Kubernetes admissions controller to prevent the container from starting if it is not approved for usage in the given environment.
6.
Your company wants to migrate their 10-TB on-premises database export into Cloud Storage. You want to minimize the time it takes to complete this activity, the overall cost, and database load. The bandwidth between the on-premises environment and Google Cloud is 1 Gbps. You want to follow Google-recommended practices. What should you do?
a)
Develop a Dataflow job to read data directly from the database and write it into Cloud Storage.
b)
Use the Data Transfer appliance to perform an offline migration.
c)
Use a commercial partner ETL solution to extract the data from the on-premises database and upload it into Cloud Storage.
d)
Compress the data and upload it with gsutil -m to enable multi-threaded copy.
7.
Your company has an enterprise application running on Compute Engine that requires high availability and high performance. The application has been deployed on two instances in two zones in the same region in active-passive mode. The application writes data to a persistent disk. In the case of a single zone outage, that data should be immediately made available to the other instance in the other zone. You want to maximize performance while minimizing downtime and data loss.
What should you do?
a)
1. Attach a persistent SSD disk to the first instance. 2. Create a snapshot every hour. 3. In case of a zone outage, recreate a persistent SSD disk in the second instance where data is coming from the created snapshot.
b)
1. Create a Cloud Storage bucket. 2. Mount the bucket into the first instance with gcs-fuse. 3. In case of a zone outage, mount the Cloud Storage bucket to the second instance with gcs-fuse.
c)
1. Attach a regional SSD persistent disk to the first instance. 2. In case of a zone outage, force-attach the disk to the other instance.
d)
1. Attach a local SSD to the first instance disk. 2. Execute an rsync command every hour where the target is a persistent SSD disk attached to the second instance. 3. In case of a zone outage, use the second instance.
8.
You are designing a Data Warehouse on Google Cloud and want to store sensitive data in BigQuery. Your company requires you to generate the encryption keys outside of Google Cloud. You need to implement a solution. What should you do?
a)
Generate a new key in Cloud Key Management Service (Cloud KMS). Store all data in Cloud Storage using the customer-managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
b)
Generate a new key in Cloud KMS. Create a dataset in BigQuery using the customer-managed key option and select the created key.
c)
Import a key in Cloud KMS. Store all data in Cloud Storage using the customer-managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
d)
Import a key in Cloud KMS. Create a dataset in BigQuery using the customer-supplied key option and select the created key.
9.
Your organization has stored sensitive data in a Cloud Storage bucket. For regulatory reasons, your company must be able to rotate the encryption key used to encrypt the data in the bucket. The data will be processed in Dataproc. You want to follow Google-recommended practices for security. What should you do?
a)
Create a key with Cloud Key Management Service (KMS). Encrypt the data using the encrypt method of Cloud KMS.
b)
Create a key with Cloud Key Management Service (KMS). Set the encryption key on the bucket to the Cloud KMS key.
c)
Generate a GPG key pair. Encrypt the data using the GPG key. Upload the encrypted data to the bucket.
d)
Generate an AES-256 encryption key. Encrypt the data in the bucket using the customer-supplied encryption keys feature.
10.
Your team needs to create a Google Kubernetes Engine (GKE) cluster to host a newly built application that requires access to third-party services on the internet.
Your company does not allow any Compute Engine instance to have a public IP address on Google Cloud. You need to create a deployment strategy that adheres to these guidelines. What should you do?
a)
Configure the GKE cluster as a private cluster, and configure Cloud NAT Gateway for the cluster subnet.
b)
Configure the GKE cluster as a private cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).
c)
Configure the GKE cluster as a route-based cluster. Configure Private Google Access on the Virtual Private Cloud (VPC).
d)
Create a Compute Engine instance, and install a NAT Proxy on the instance. Configure all workloads on GKE to pass through this proxy to access third-party services on the Internet.
11.
Your company has a support ticketing solution that uses App Engine Standard. The project that contains the App Engine application already has a Virtual Private
Cloud (VPC) network fully connected to the company's on-premises environment through a Cloud VPN tunnel. You want to enable the App Engine application to communicate with a database that is running in the company's on-premises environment. What should you do?
a)
Configure private Google access for on-premises hosts only.
b)
Configure private Google access.
c)
Configure private services access.
d)
Configure serverless VPC access.
12.
Your company is planning to upload several important files to Cloud Storage. After the upload is completed, they want to verify that the uploaded content is identical to what they have on-premises. You want to minimize the cost and effort of performing this check. What should you do?
a)
1. Use Linux shasum to compute a digest of files you want to upload. 2. Use gsutil -m to upload all the files to Cloud Storage. 3. Use gsutil cp to download the uploaded files. 4. Use Linux shasum to compute a digest of the downloaded files. 5. Compare the hashes.
b)
1. Use gsutil -m to upload the files to Cloud Storage. 2. Develop a custom Java application that computes CRC32C hashes. 3. Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files. 4. Compare the hashes.
c)
1. Use gsutil -m to upload all the files to Cloud Storage. 2. Use gsutil cp to download the uploaded files. 3. Use Linux diff to compare the content of the files.
d)
1. Use gsutil -m to upload the files to Cloud Storage. 2. Use gsutil hash -c FILE_NAME to generate CRC32C hashes of all on-premises files. 3. Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files. 4. Compare the hashes.
13.
You have deployed an application on Anthos clusters (formerly Anthos GKE). According to the SRE practices at your company, you need to be alerted if request latency is above a certain threshold for a specified amount of time. What should you do?
a)
Install Anthos Service Mesh on your cluster. Use the Google Cloud Console to define a Service Level Objective (SLO), and create an alerting policy based on this SLO.
b)
Enable the Cloud Trace API on your project, and use Cloud Monitoring Alerts to send an alert based on the Cloud Trace metrics.
c)
Use Cloud Profiler to follow up the request latency. Create a custom metric in Cloud Monitoring based on the results of Cloud Profiler, and create an Alerting policy in case this metric exceeds the threshold.
d)
Configure Anthos Config Management on your cluster, and create a yaml file that defines the SLO and alerting policy you want to deploy in your cluster.
14.
Your company has a stateless web API that performs scientific calculations. The web API runs on a single Google Kubernetes Engine (GKE) cluster. The cluster is currently deployed in us-central1. Your company has expanded to offer your API to customers in Asia. You want to reduce the latency for users in Asia.
What should you do?
a)
Create a second GKE cluster in asia-southeast1, and expose both APIs using a Service of type LoadBalancer. Add the public IPs to the Cloud DNS zone.
b)
Use a global HTTP(s) load balancer with Cloud CDN enabled.
c)
Create a second GKE cluster in asia-southeast1, and use kubemci to create a global HTTP(s) load balancer.
d)
Increase the memory and CPU allocated to the application in the cluster.
15.
You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud. You are unsure about the optimum CPU and memory options. The applications have a consistent usage pattern across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?
a)
Create an instance template with the smallest available machine type, and use an image of the third-party application taken from a current on-premises virtual machine. Create a managed instance group that uses average CPU utilization to autoscale the number of instances in the group. Modify the average CPU utilization threshold to optimize the number of instances running.
b)
Create an App Engine flexible environment, and deploy the third-party application using a Dockerfile and a custom runtime. Set CPU and memory options similar to your application's current on-premises virtual machine in the app.yaml file.
c)
Create multiple Compute Engine instances with varying CPU and memory options. Install the Cloud Monitoring agent, and deploy the third-party application on each of them. Run a load test with high traffic levels on the application, and use the results to determine the optimal settings.
d)
Create a Compute Engine instance with CPU and memory options similar to your application's current on-premises virtual machine. Install the Cloud Monitoring agent, and deploy the third-party application. Run a load test with normal traffic levels on the application, and follow the Rightsizing Recommendations in the Cloud Console.
16.
Your company has a Google Cloud project that uses BigQuery for data warehousing. They have a VPN tunnel between the on-premises environment and Google
Cloud that is configured with Cloud VPN. The security team wants to avoid data exfiltration by malicious insiders, compromised code, and accidental oversharing.
What should they do?
a)
Configure Private Google Access for on-premises only.
b)
Perform the following tasks: 1. Create a service account. 2. Give the BigQuery JobUser role and Storage Reader role to the service account. 3. Remove all other IAM access from the project.
c)
Configure VPC Service Controls and configure Private Google Access.
d)
Configure Private Google Access.
17.
You are working at an institution that processes medical data. You are migrating several workloads onto Google Cloud. Company policies require all workloads to run on physically separated hardware, and workloads from different clients must also be separated. You created a sole-tenant node group and added a node for each client. You need to deploy the workloads on these dedicated hosts. What should you do?
a)
Add the node group name as a network tag when creating Compute Engine instances in order to host each workload on the correct node group.
b)
Add the node name as a network tag when creating Compute Engine instances in order to host each workload on the correct node.
c)
Use node affinity labels based on the node group name when creating Compute Engine instances in order to host each workload on the correct node group.
d)
Use node affinity labels based on the node name when creating Compute Engine instances in order to host each workload on the correct node.
18.
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual machines. The full test suite takes several hours to complete, running on a limited number of on-premises servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the amount of time it takes to fully test a change to the system, while changing the tests as little as possible.
Which cloud infrastructure should you recommend?
a)
Google Compute Engine unmanaged instance groups and Network Load Balancer
b)
Google Compute Engine managed instance groups with auto-scaling
c)
Google Cloud Dataproc to run Apache Hadoop jobs to process each test
d)
Google App Engine with Google StackDriver for logging
19.
A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run properly on Google Cloud Platform.
What should you do?
a)
Help the engineer to convert his websocket code to use HTTP streaming
b)
Review the encryption requirements for websocket connections with the security team
c)
Meet with the cloud operations team and the engineer to discuss load balancer options
d)
Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
20.
The application reliability team at your company this added a debug feature to their backend service to send all server events to Google Cloud Storage for eventual analysis. The event records are at least 50 KB and at most 15 MB and are expected to peak at 3,000 events per second. You want to minimize data loss.
Which process should you implement?
a)
• Append metadata to file body • Compress individual files • Name files with serverName – Timestamp • Create a new bucket if bucket is older than 1 hour and save individual files to the new bucket. Otherwise, save files to existing bucket.
b)
• Batch every 10,000 events with a single manifest file for metadata • Compress event files and manifest file into a single archive file • Name files using serverName - EventSequence • Create a new bucket if bucket is older than 1 day and save the single archive file to the new bucket. Otherwise, save the single archive file to existing bucket.
c)
• Compress individual files • Name files with serverName - EventSequence • Save files to one bucket • Set custom metadata headers for each object after saving.
d)
• Append metadata to file body • Compress individual files • Name files with a random prefix pattern • Save files to one bucket.
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