Professional-Cloud-Architect Exam Study Guide Free Practice Test LAST UPDATED DATE Dec 14, 2023
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NEW QUESTION # 86
TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location, its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US, Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles.
You want to run this job on all the data.
What is the most cost-effective way to run this job?
- A. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the job
- B. Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job
- C. Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job
- D. Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi- region bucket and use a Dataproc cluster to finish the job
Answer: D
Explanation:
Storageguarantees 2 replicates which are geo diverse (100 miles apart) which can get better remote latency and availability.
More importantly, is that multiregional heavily leverages Edge caching and CDNs to provide the content to the end users.
All this redundancy and caching means that Multiregional comes with overhead to sync and ensure consistency between geo-diverse areas. As such, it's much better for write-once-read-many scenarios. This means frequently accessed (e.g. "hot" objects) around the world, such as website content, streaming videos, gaming or mobile applications.
Reference: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the-best- performance-5c847ac8f9f2
NEW QUESTION # 87
You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.
How should you handle these types of errors?
- A. Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting
- B. Implement retry logic using a truncated exponential backoff strategy.
- C. Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.
- D. Use gRPC instead of HTTP for better performance.
Answer: D
Explanation:
an incident.
Explanation:
Reference https://cloud.google.com/storage/docs/json_api/v1/status-codes
NEW QUESTION # 88
You want to create a private connection between your instances on Compute Engine and your on- premises data center. You require a connection of at least 20 Gbps. You want to follow Google- recommended practices. How should you set up the connection?
- A. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises datacenter using a single Cloud VPN.
- B. Create a VPC and connect it to your on-premises data center using Dedicated Interconnect.
- C. Create a Cloud Content Delivery Network (Cloud CDN) and connect it to your on-premises data center using Dedicated Interconnect.
- D. Create a VPC and connect it to your on-premises data center using a single Cloud VPN.
Answer: B
Explanation:
https://cloud.google.com/compute/docs/instances/connecting-advanced
NEW QUESTION # 89
Your company has a Google Cloud project that uses BlgQuery for data warehousing There are some tables that contain personally identifiable information (PI!) Only the compliance team may access the PH. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables What should you do?
- A. 1 From the dataset where you have the source data, create views of tables that you want to share, excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team
3 Assign access controls to the dataset that contains the view - B. 1 From the dataset where you have the source data, create materialized views of tables that you want to share excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team 3. Assign access controls to the dataset that contains the view. - C. 1. Create a dataset for the data science team.
2. Create materialized views of tables that you want to share, excluding Pll
3. Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset - D. 1 Create a dataset for the data science team
2 Create views of tables that you want to share excluding Pll
3 Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset
Answer: D
Explanation:
This option can help minimize cost and time by using views and authorized datasets. Views are virtual tables defined by a SQL query that can exclude PII columns from the source tables. Views do not incur storage costs and do not duplicate data. Authorized datasets are datasets that have access to another dataset's data without granting direct access to individual users or groups. By creating a dataset for the data science team and creating views of tables that exclude PII, you can share only the relevant information with the team. By assigning an appropriate project-level IAM role to the members of the data science team, you can grant them access to the BigQuery service and resources. By assigning access controls to the dataset that contains the view, you can grant them access to query the views. By authorizing the view to access the source dataset, you can enable the view to read data from the source tables without exposing PII. The other options are not optimal for this scenario, because they either use materialized views instead of views, which incur storage costs and duplicate data (B, D), or do not create a separate dataset for the data science team, which makes it harder to manage access controls (A). Reference:
https://cloud.google.com/bigquery/docs/views
https://cloud.google.com/bigquery/docs/authorized-datasets
NEW QUESTION # 90
You need to upload files from your on-premises environment to Cloud Storage. You want the files to be encrypted on Cloud Storage using customer-supplied encryption keys. What should you do?
- A. Supply the encryption key in a .boto configuration file. Use gsutil to upload the files.
- B. Use gsutil to upload the files, and use the flag --encryption-key to supply the encryption key.
- C. Use gsutil to create a bucket, and use the flag --encryption-key to supply the encryption key. Use gsutil to upload the files to that bucket.
- D. Supply the encryption key using gcloud config. Use gsutil to upload the files to that bucket.
Answer: A
Explanation:
Explanation
https://cloud.google.com/storage/docs/encryption/customer-supplied-keys#gsutil
NEW QUESTION # 91
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine. The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Create a new service account with BigQuery access and execute your script with that user
- B. Run your script on a new virtual machine with the BigQuery access scope enabled
- C. Install the bq component for gccloud with the command gcloud components install bq.
- D. Install the latest BigQuery API client library for Python
Answer: B
Explanation:
The error is most like caused by the access scope issue. When create new instance, you have the default Compute engine default service account but most serves access including BigQuery is not enable. Create an instance Most access are not enabled by default You have default service account but don't have the permission (scope) you can stop the instance, edit, change scope and restart it to enable the scope access. Of course, if you Run your script on a new virtual machine with the BigQuery access scope enabled, it also works
https://cloud.google.com/compute/docs/access/service-accounts
NEW QUESTION # 92
One of your primary business objectives is being able to trust the data stored in your application. You want to log all changes to the application data. How can you design your logging system to verify authenticity of your logs?
- A. Use a SQL database and limit who can modify the log table.
- B. Digitally sign each timestamp and log entry and store the signature.
- C. Create a JSON dump of each log entry and store it in Google Cloud Storage.
- D. Write the log concurrently in the cloud and on premises.
Answer: B
Explanation:
Explanation
https://cloud.google.com/storage/docs/access-logs
References: https://cloud.google.com/logging/docs/reference/tools/gcloud-logging
NEW QUESTION # 93
You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified the appropriate web response is coming from each instance using the curl command. You want to ensure the backend is configured correctly. What should you do?
- A. Ensure that a firewall rule exists to allow source traffic on HTTP/HTTPS to reach the load balancer.
- B. Create a tag on each instance with the name of the load balancer. Configure a firewall rule with the name of the load balancer as the source and the instance tag as the destination.
- C. Assign a public IP to each instance and configure a firewall rule to allow the load balancer to reach the instance public IP.
- D. Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.
Answer: D
Explanation:
The best practice when configuration a health check is to check health and serve traffic on the same port. However, it is possible to perform health checks on one port, but serve traffic on another. If you do use two different ports, ensure that firewall rules and services running on instances are configured appropriately. If you run health checks and serve traffic on the same port, but decide to switch ports at some point, be sure to update both the backend service and the health check.
Backend services that do not have a valid global forwarding rule referencing it will not be health checked and will have no health status.
References: https://cloud.google.com/compute/docs/load-balancing/http/backend-service
NEW QUESTION # 94
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers
- A. Use a slimmed-down base image like Alpine linux.
- B. Copy the source after the package dependencies (Python and pip) are installed.
- C. Remove Python after running pip.
- D. Remove dependencies from requirements.txt.
- E. Use larger machine types for your Google Container Engine node pools.
Answer: A,B
NEW QUESTION # 95
For this question, refer to the Helicopter Racing League (HRL) case study. Your team is in charge of creating a payment card data vault for card numbers used to bill tens of thousands of viewers, merchandise consumers, and season ticket holders. You need to implement a custom card tokenization service that meets the following requirements:
* It must provide low latency at minimal cost.
* It must be able to identify duplicate credit cards and must not store plaintext card numbers.
* It should support annual key rotation.
Which storage approach should you adopt for your tokenization service?
- A. Use column-level encryption to store the data in Cloud SQL.
- B. Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.
- C. Store the card data in Secret Manager after running a query to identify duplicates.
- D. Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.
Answer: A
NEW QUESTION # 96
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. Set up a CI/CD pipeline using Jenkins and Spinnaker to automate canary deployments and improve development velocity.
- 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. 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.
- D. 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.
- E. Adopt a schema versioning tool to reduce downtime when adding new game features that require storing additional player data in the database.
Answer: A,C
NEW QUESTION # 97
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?
- A. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
- B. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- C. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
- D. Kubernetes Engine, Cloud Pub/Sub, and Cloud SQL
- E. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
Answer: A
Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
References: https://cloud.google.com/solutions/big-data/stream-analytics/ Mountkirk Games, B Testlet 1 Company Overview Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
* Increase to a global footprint.
* Improve uptime - downtime is loss of players.
* Increase efficiency of the cloud resources we use.
* Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
* Dynamically scale up or down based on game activity.
* Connect to a transactional database service to manage user profiles and game state.
* Store game activity in a timeseries database service for future analysis.
* As the system scales, ensure that data is not lost due to processing backlogs.
* Run hardened Linux distro.
Requirements for Game Analytics Platform
* Dynamically scale up or down based on game activity
* Process incoming data on the fly directly from the game servers
* Process data that arrives late because of slow mobile networks
* Allow queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users. Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
NEW QUESTION # 98
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical
architecture for the compute workloads for your company, Mountkirk Games. Considering the Mountkirk
Games business and technical requirements, what should you do?
- A. Create network load balancers. Use preemptible Compute Engine instances.
- B. Create network load balancers. Use non-preemptible Compute Engine instances.
- C. Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible
Compute Engine instances. - D. Create a global load balancer with managed instance groups and autoscaling policies. Use non-
preemptible Compute Engine instances.
Answer: C
NEW QUESTION # 99
You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine.
The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?
- A. Run your script on a new virtual machine with the BigQuery access scope enabled
- B. Create a new service account with BigQuery access and execute your script with that user
- C. Install the latest BigQuery API client library for Python
- D. Install the bq component for gccloud with the command gcloud components install bq.
Answer: C
Explanation:
Explanation
https://cloud.google.com/bigquery/docs/python-client-migration
Applications that use BigQuery must be associated with a Google Cloud Platform Console project with the BigQuery API enabled.
Reference: https://cloud.google.com/bigquery/create-simple-app-api
NEW QUESTION # 100
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. Set up a CI/CD pipeline using Jenkins and Spinnaker to automate canary deployments and improve development velocity.
- 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. 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.
- D. 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.
- E. Adopt a schema versioning tool to reduce downtime when adding new game features that require storing additional player data in the database.
Answer: A,C
Explanation:
Explanation/Reference:
NEW QUESTION # 101
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. Use a commercial partner ETL solution to extract the data from the on-premises database and upload it into Cloud Storage
- B. Use the Data Transfer appliance to perform an offline migration
- C. Compress the data and upload it with gsutii -m to enable multi-threaded copy
- D. Develop a Dataflow job to read data directly from the database and write it into Cloud Storage
Answer: B
Explanation:
The Data Transfer appliance is a Google-provided hardware device that can be used to transfer large amounts of data from on-premises environments to Cloud Storage. It is suitable for scenarios where the bandwidth between the on-premises environment and Google Cloud is low or insufficient, and the data size is large. The Data Transfer appliance can minimize the time it takes to complete the migration, the overall cost and database load, by avoiding network bottlenecks and reducing bandwidth consumption. The Data Transfer appliance also encrypts the data at rest and in transit, ensuring data security and privacy. The other options are not optimal for this scenario, because they either require a high-bandwidth network connection (B, C, D), or incur additional costs and complexity (B, C). Reference:
https://cloud.google.com/data-transfer-appliance/docs/overview
https://cloud.google.com/blog/products/storage-data-transfer/introducing-storage-transfer-service-for-on-premises-data
NEW QUESTION # 102
Google Cloud Platform resources are managed hierarchically using organization, folders, and projects. When Cloud Identity and Access Management (IAM) policies exist at these different levels, what is the effective policy at a particular node of the hierarchy?
- A. The effective policy is the policy set at the node and restricted by the policies of its ancestors
- B. The effective policy is the intersection of the policy set at the node and policies inherited from its ancestors
- C. The effective policy is the union of the policy set at the node and policies inherited from its ancestors
- D. The effective policy is determined only by the policy set at the node
Answer: A
Explanation:
Reference:
l
NEW QUESTION # 103
Your company is running a stateless application on a Compute Engine instance. The application is used heavily during regular business hours and lightly outside of business hours. Users are reporting that the application is slow during peak hours. You need to optimize the application's performance. What should you do?
- A. Create an instance template from the existing disk. Create a custom image from the instance template. Create an autoscaled managed instance group from the custom image.
- B. Create a snapshot of the existing disk. Create an instance template from the snapshot. Create an autoscaled managed instance group from the instance template.
- C. Create a snapshot of the existing disk. Create a custom image from the snapshot. Create an autoscaled managed instance group from the custom image.
- D. Create a custom image from the existing disk. Create an instance template from the custom image. Create an autoscaled managed instance group from the instance template.
Answer: C
Explanation:
https://cloud.google.com/compute/docs/instance-templates/create-instance-templates
NEW QUESTION # 104
Case Study: 7 - Mountkirk Games
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of their games using some server-side integration. Historically, they have used cloud providers to lease physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs) to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into usage patterns so we can adapt the game to target users.
Additionally, our current technology stack cannot provide the scale we need, so we want to replace MySQL and move to an environment that provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design a way to test the analytics platform's resilience to changes in mobile network latency.
What should you do?
- A. Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.
- B. Build a test client that can be run from a mobile phone emulator on a Compute Engine virtual machine, and run multiple copies in Google Cloud Platform regions all over the world to generate realistic traffic.
- C. Create an opt-in beta of the game that runs on players' mobile devices and collects response times from analytics endpoints running in Google Cloud Platform regions all over the world.
- D. Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.
Answer: C
NEW QUESTION # 105
Your marketing department wants to send out a promotional email campaign. The development team wants to minimize direct operation management. They project a wide range of possible customer responses, from 100 to 500,000 click-throughs per day. The link leads to a simple website that explains the promotion and collects user information and preferences. Which infrastructure should you recommend?
- A. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.
- B. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.
- C. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data.
- D. Use a Google Container Engine cluster to serve the website and store data to persistent disk.
Answer: B
NEW QUESTION # 106
You are deploying an application on App Engine that needs to integrate with an on-premises database. For security purposes, your on-premises database must not be accessible through the public Internet.
What should you do?
- A. Deploy your application on App Engine standard environment and use App Engine firewall rules to limit access to the open on-premises database.
- B. Deploy your application on App Engine flexible environment and use App Engine firewall rules to limit access to the on-premises database.
- C. Deploy your application on App Engine flexible environment and use Cloud VPN to limit access to the on-premises database.
- D. Deploy your application on App Engine standard environment and use Cloud VPN to limit access to the on-premises database.
Answer: A
NEW QUESTION # 107
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
- A. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- B. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
- C. Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity. - D. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
Answer: B
Explanation:
https://cloud.google.com/storage/docs/access-control/signed-urls
NEW QUESTION # 108
You are creating a solution to remove backup files older than 90 days from your backup Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend. What should you do?
- A. Write a lifecycle management rule in JSON and push it to the bucket with gsutil.
- B. Write a lifecycle management rule in XML and push it to the bucket with gsutil.
- C. Schedule a cron script using gsutil is -lr gs://backups/** to find and remove items older than 90 days.
- D. Schedule a cron script using gsutil ls -1 gs://backups/** to find and remove items older than 90 days and schedule it with cron.
Answer: D
NEW QUESTION # 109
The operations manager asks you for a list of recommended practices that she should consider when migrating a J2EE application to the cloud. Which three practices should you recommend? Choose 3 answers
- A. Integrate Cloud Dataflow into the application to capture real-time metrics.
- B. Port the application code to run on Google App Engine.
- C. Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable.
- D. Select an automation framework to reliably provision the cloud infrastructure.
- E. Instrument the application with a monitoring tool like Stackdriver Debugger.
- F. Deploy a continuous integration tool with automated testing in a staging environment.
Answer: B,C,F
Explanation:
Reference:
https://cloud.google.com/appengine/docs/standard/java/building-app/cloud-sql
NEW QUESTION # 110
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