UPDATED [2023] Pass Google Professional-Cloud-Architect Exam in First Attempt Guaranteed
Pass Professional-Cloud-Architect Exam Latest Practice Questions
Exam Details
The Google Professional Cloud Architect test is timed. The exact number of questions has not been revealed by the vendor. But, it is known that candidates will be given 2 hours to complete the exam, and the questions will be based on multiple-choice and multiple select types. Available languages are English and Japanese, and one should pay $200 as a registration fee. Note that there can be an additional tax.
When it comes to the exam delivery formats, there are two choices for an aspirant. They can either sit for it in a testing center near them or can avail of the online proctoring facility. In both methods, the content and pattern of the test will be the same.
For this exam, a beta version is offered as well. Anyone who wants to save 40% on the total fee or willing to recertify can take it. The cost in this case is $120, the length increases to 3 hours, and some questions may be provided in the form of case studies. Also, pay attention to the fact that the results will be known after 6-8 weeks only.
How to book Google Professional Cloud Architect Exams
The registration for the Google Professional Cloud Architect Exam follows the steps given below.
- Step 1: Visit the Google Cloud Webassessor Website
- Step 2: Sign in or sign up to your Google Cloud Webassessor account
- Step 3: Search for the exam name Google Professional Cloud Architect
- Step 4: Take the date of the exam, choose exam center and make further payment using payment method like credit/debit etc.
NEW QUESTION 35
Your applications will be writing their logs to BigQuery for analysis. Each application should have its own table. Any logs older than 45 days should be removed. You want to optimize storage and follow Google- recommended practices. What should you do?
- A. Rely on BigQuery's default behavior to prune application logs older than 45 days
- B. Configure the expiration time for your tables at 45 days
- C. Make the tables time-partitioned, and configure the partition expiration at 45 days
- D. Create a script that uses the BigQuery command line tool (bq) to remove records older than 45 days
Answer: B
NEW QUESTION 36
You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.
What should you do?
- A. Add additional nodes to your Kubernetes Engine cluster using the following command:
gcloud container clusters resize
CLUSTER_Name - -size 10 - B. Add a tag to the instances in the cluster with the following command:
gcloud compute instances add-tags
INSTANCE - -tags enable-
autoscaling max-nodes-10 - C. Create a new Kubernetes Engine cluster with the following command:
gcloud alpha container clusters
create mycluster - -enable-
autoscaling - -min-nodes=1 - -max-nodes=10
and redeploy your application - D. Update the existing Kubernetes Engine cluster with the following command:
gcloud alpha container clusters
update mycluster - -enable-
autoscaling - -min-nodes=1 - -max-nodes=10
Answer: D
NEW QUESTION 37
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. 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.
- B. 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.
- C. Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.
- D. Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.
Answer: D
NEW QUESTION 38
Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?
- A. Implement a Cloud NAT solution to remove the need for external IP addresses entirely.
- B. Remove the default route on all VPCs. Move all approved instances into a new subnet that has a default route to an internet gateway.
- C. Set an Organization Policy with a constraint on constraints/compute.vmExternalIpAccess. List the approved instances in the allowedValues list.
- D. Create a new VPC in custom mode. Create a new subnet for the approved instances, and set a default route to the internet gateway on this new subnet.
Answer: C
Explanation:
Reference:
https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address#disableexternalip you might want to restrict external IP address so that only specific VM instances can use them. This option can help to prevent data exfiltration or maintain network isolation. Using an Organization Policy, you can restrict external IP addresses to specific VM instances with constraints to control use of external IP addresses for your VM instances within an organization or a project.
NEW QUESTION 39
For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?
- A. Build stress tests into each component of your application using resources internal to GCP to simulate load.
- B. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low.
- C. Use the existing infrastructure to test the GCP-based backend at scale.
- D. Create a scalable environment in GCP for simulating production load.
Answer: D
Explanation:
From scenario: Requirements for Game Backend Platform
* Dynamically scale up or down based on game activity
* Connect to a managed NoSQL database service
* Run customize Linux distro
NEW QUESTION 40
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. Write the log concurrently in the cloud and on premises
- B. Digitally sign each timestamp and log entry and store the signature
- C. Use a SQL database and limit who can modify the log table
- D. Create a JSON dump of each log entry and store it in Google Cloud Storage
Answer: B
NEW QUESTION 41
As part of implementing their disaster recovery plan, your company is trying to replicate their production MySQL database from their private data center to their GCP project using a Google Cloud VPN connection. They are experiencing latency issues and a small amount of packet loss that is disrupting the replication. What should they do?
- A. Send the replicated transaction to Google Cloud Pub/Sub.
- B. Add additional VPN connections and load balance them.
- C. Configure their replication to use UDP.
- D. Configure a Google Cloud Dedicated Interconnect.
- E. Restore their database daily using Google Cloud SQL.
Answer: D
NEW QUESTION 42
Case Study: 6 - TerramEarth
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
* Support the dealer network with more data on how their customers use their equipment to better
* position new products and services
Have the ability to partner with different companies - especially with seed and fertilizer suppliers
* in the fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east
* coast.
Create a backup strategy.
* Increase security of data transfer from equipment to the datacenter.
* Improve data in the data warehouse.
* Use customer and equipment data to anticipate customer needs.
* Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
* - 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
* - Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
* - RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.
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: "Nearline", and Action: "Delete".
- B. 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".
- 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: "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".
Answer: B
NEW QUESTION 43
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. Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity. - B. 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.
- C. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- D. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
Answer: C
NEW QUESTION 44
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. Export files to an encrypted USB device, send the device to Google Cloud, and request an import of the data 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. Configure the Storage Transfer service from Google Cloud to send the data from your data center to Cloud Storage
Answer: A
NEW QUESTION 45
You are developing a globally scaled frontend for a legacy streaming backend data API. This API expects events in strict chronological order with no repeat data for proper processing.
Which products should you deploy to ensure guaranteed-once FIFO (first-in, first-out) delivery of data?
- A. Cloud Pub/Sub to Cloud DataFlow
- B. Cloud Pub/Sub to Stackdriver
- C. Cloud Pub/Sub alone
- D. Cloud Pub/Sub to Cloud SQL
Answer: A
Explanation:
Explanation
Reference https://cloud.google.com/pubsub/docs/ordering
NEW QUESTION 46
Your company has successfully migrated to the cloud and wants to analyze their data stream to optimize operations. They do not have any existing code for this analysis, so they are exploring all their options. These options include a mix of batch and stream processing, as they are running some hourly jobs and live-processing some data as it comes in. Which technology should they use for this?
- A. Google Container Engine with Bigtable
- B. Google Cloud Dataproc
- C. Google Compute Engine with Google BigQuery
- D. Google Cloud Dataflow
Answer: D
Explanation:
Dataflow is for processing both the Batch and Stream.
Cloud Dataflow is a fully-managed service for transforming and enriching data in stream (real time) and batch (historical) modes with equal reliability and expressiveness -- no more complex workarounds or compromises needed.
References: https://cloud.google.com/dataflow/
NEW QUESTION 47
The development team has provided you with a Kubernetes Deployment file. You have no infrastructure yet and need to deploy the application. What should you do?
- A. Use kubectl to create a Kubernetes cluster. Use kubectl to create the deployment.
- B. Use kubectl to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- C. Use gcloud to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- D. Use gcloud to create a Kubernetes cluster. Use kubectl to create the deployment.
Answer: D
Explanation:
Gcloud to create
Kubectl to do Kubernete
NEW QUESTION 48
You have a Python web application with many dependencies that requires 0.1 CPU cores and
128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?
- A. Perform the following:
1. Create a Kubernetes Engine cluster with n1-standard-4 type machines.
2. Build a Docker image from the master branch will all of the dependencies, and tag it with
"latest".
3. Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to
"Always". Restart the pods to automatically deploy new production releases. - B. Perform the following:
1. Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2. Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3. Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing. - C. Perform the following:
1. Create a managed instance group with f1-micro type machines.
2. Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3. Restart the instances to automatically deploy new production releases. - D. Perform the following:
1. Create a managed instance group with n1-standard-1 type machines.
2. Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3. Rebuild the Compute Engine image, and update the instance template to deploy new production releases.
Answer: B
NEW QUESTION 49
Your organization requires that metrics from all applications be retained for 5 years for future analysis in possible legal proceedings. Which approach should you use?
- A. Configure Stackdriver Monitoring for all Projects, and export to BigQuery.
- B. Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.
- C. Configure Stackdriver Monitoring for all Projects with the default retention policies.
- D. Grant the security team access to the logs in each Project.
Answer: B
Explanation:
Explanation
Overview of storage classes, price, and use cases https://cloud.google.com/storage/docs/storage-classes Why export logs? https://cloud.google.com/logging/docs/export/ StackDriver Quotas and Limits for Monitoring https://cloud.google.com/monitoring/quotas The BigQuery pricing. https://cloud.google.com/bigquery/pricing
NEW QUESTION 50
Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month.
- A. Connect Google Data Studio to BigQuery. Create a dimension for the users and a metric for the amount of queries per user.
- B. Use 'bq show' to list all jobs. Per job, use 'bq Is' to list job information and get the required information.
- C. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.
- D. In the BigQuery interface, execute a query on the JOBS table to get the required information.
Answer: B
Explanation:
https://cloud.google.com/bigquery/docs/managing-jobs
NEW QUESTION 51
You deploy your custom Java application to Google App Engine. It fails to deploy and gives you the following stack trace.
What should you do?
- A. Recompile the CLoakedServlet class using and MD5 hash instead of SHA1
- B. Upload missing JAR files and redeploy your application.
- C. Digitally sign all of your JAR files and redeploy your application
Answer: C
NEW QUESTION 52
Case Study: 2 - TerramEarth Case Study
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries: About
80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second.
Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced.
The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second, with 22 hours of operation per day.
TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
- Decrease unplanned vehicle downtime to less than 1 week, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP better position new products and services.
- Have the ability to partner with different companies-especially with
seed and fertilizer suppliers in the fast-growing agricultural
business-to create compelling joint offerings for their customers
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?
- A. Use multiple Google Container Engine clusters running FTP servers located in different regions.
Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket. - B. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket.
- C. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
- D. Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.
Answer: C
NEW QUESTION 53
......
Google Professional-Cloud-Architect Study Guide Archives : https://interfacett.braindumpquiz.com/Professional-Cloud-Architect-exam-material.html