2022 Realistic Verified Free Google Professional-Cloud-Architect Exam Questions [Q101-Q124]

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2022 Realistic Verified Free Google Professional-Cloud-Architect Exam Questions

Professional-Cloud-Architect Real Exam Questions and Answers FREE

Q101. You need to design a solution for global load balancing based on the URL path being requested. You need to ensure operations reliability and end-to-end in-transit encryption based on Google best practices.
What should you do?

Create a cross-region load balancer with URL Maps.

Create an HTTPS load balancer with URL maps.

Create appropriate instance groups and instances. Configure SSL proxy load balancing.

Create a global forwarding rule. Configure SSL proxy balancing.

Q102. You have found an error in your App Engine application caused by missing Cloud Datastore indexes. You have created a YAML file with the required indexes and want to deploy these new indexes to Cloud Datastore.
What should you do?

Point gcloud datastore create-indexes to your configuration file

Upload the configuration file the App Engine’s default Cloud Storage bucket, and have App Engine detect the new indexes

In the GCP Console, use Datastore Admin to delete the current indexes and upload the new configuration file

Create an HTTP request to the built-in python module to send the index configuration file to your application

Q103. 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?

Cloud Pub/Sub alone

Cloud Pub/Sub to Cloud DataFlow

Cloud Pub/Sub to Stackdriver

Cloud Pub/Sub to Cloud SQL

Q104. A news teed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed. What is the most likely cause of this problem?

The session variable is local to just a single instance.

The session variable is being overwritten in Cloud Datastore.

The URL of the API needs to be modified to prevent caching.

The HTTP Expires header needs to be set to -1 to stop caching.

Q105. For this question, refer to the Dress4Win case study.
At Dress4Win, an operations engineer wants to create a tow-cost solution to remotely archive copies of database backup files. The database files are compressed tar files stored in their current data center. How should he proceed?

Create a cron script using gsutil to copy the files to a Coldline Storage bucket.

Create a cron script using gsutil to copy the files to a Regional Storage bucket.

Create a Cloud Storage Transfer Service Job to copy the files to a Coldline Storage bucket.

Create a Cloud Storage Transfer Service job to copy the files to a Regional Storage bucket.

Q106. For this question, refer to the Dress4Win case study.
Dress4Win has configured a new uptime check with Google Stackdriver for several of their legacy services.
The Stackdriver dashboard is not reporting the services as healthy. What should they do?

Install the Stackdriver agent on all of the legacy web servers.

In the Cloud Platform Console download the list of the uptime servers’ IP addresses and create an inbound firewall rule

Configure their load balancer to pass through the User-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)

Configure their legacy web servers to allow requests that contain user-Agent HTTP header when the value matches GoogleStackdriverMonitoring- UptimeChecks (https://cloud.google.com/monitoring)

Q107. For this question refer to the TerramEarth case study
Operational parameters such as oil pressure are adjustable on each of TerramEarth’s vehicles to increase their efficiency, depending on their environmental conditions. Your primary goal is to increase the operating efficiency of all 20 million cellular and unconnected vehicles in the field How can you accomplish this goal?

Have your engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically.

Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically.

Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically.

Capture all operating data, train machine learning models that identify ideal operations, and host in Google Cloud Machine Learning (ML) Platform to make operational adjustments automatically.

Q108. The database administration team has asked you to help them improve the performance of their new database server running on Google Compute Engine. The database is for importing and normalizing their performance statistics and is built with MySQL running on Debian Linux. They have an n1-standard-8 virtual machine with
80 GB of SSD persistent disk. What should they change to get better performance from this system?

Increase the virtual machine’s memory to 64 GB.

Create a new virtual machine running PostgreSQL.

Dynamically resize the SSD persistent disk to 500 GB.

Migrate their performance metrics warehouse to BigQuery.

Modify all of their batch jobs to use bulk inserts into the database.

Q109. Your customer wants to do resilience testing of their authentication layer. This consists of a regional managed instance group serving a public REST API that reads from and writes to a Cloud SQL instance.
What should you do?

Engage with a security company to run web scrapes that look your users’ authentication data om malicious websites and notify you if any if found.

Deploy intrusion detection software to your virtual machines to detect and log unauthorized access.

Schedule a disaster simulation exercise during which you can shut off all VMs in a zone to see how your application behaves.

Configure a red replica for your Cloud SQL instance in a different zone than the master, and then manually trigger a failover while monitoring KPIs for our REST API.

Q110. You want your Google Kubernetes Engine cluster to automatically add or remove nodes based on CPUload.
What should you do?

Configure a HorizontalPodAutoscaler with a target CPU usage. Enable the Cluster Autoscaler from the GCP Console.

Configure a HorizontalPodAutoscaler with a target CPU usage. Enable autoscaling on the managed instance group for the cluster using the gcloud command.

Create a deployment and set the maxUnavailable and maxSurge properties. Enable the Cluster Autoscaler using the gcloud command..

Create a deployment and set the maxUnavailable and maxSurge properties. Enable autoscaling on the cluster managed instance group from the GCP Console.

Q111. Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each tier (web, API, and database) scales independently of the others. Network traffic should flow through the web to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier.
How should you configure the network?

Add each tier to a different subnetwork

Set up software based firewalls on individual VMs

Add tags to each tier and set up routes to allow the desired traffic flow

Add tags to each tier and set up firewall rules to allow the desired traffic flow

Q112. An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a better tool to capture errors and help them analyze their historical log data.
You want to help them find a solution that meets their needs.
What should you do?

Direct them to download and install the Google StackDriver logging agent

Send them a list of online resources about logging best practices

Help them define their requirements and assess viable logging tools

Help them upgrade their current tool to take advantage of any new features

Q113. For this question, refer to the Mountkirk Games case study.
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?

Container Engine, Cloud Pub/Sub, and Cloud SQL

Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery

Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow

Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow

Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc

Q114. 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.

Port the application code to run on Google App Engine

Integrate Cloud Dataflow into the application to capture real-time metrics

Instrument the application with a monitoring tool like Stackdriver Debugger

Select an automation framework to reliably provision the cloud infrastructure

Deploy a continuous integration tool with automated testing in a staging environment

Migrate from MySQL to a managed NoSQL database like Google Cloud Datastore or Bigtable

Q115. For this question, refer to the Dress4Win case study. To be legally compliant during an audit, Dress4Win must be able to give insights in all administrative actions that modify the configuration or metadata of resources on Google Cloud.
What should you do?

Use Stackdriver Trace to create a trace list analysis.

Use Stackdriver Monitoring to create a dashboard on the project’s activity.

Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.

Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.

Q116. 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?

Ensure that a firewall rule exists to allow source traffic on HTTP/HTTPS to reach the load balancer.

Assign a public IP to each instance and configure a firewall rule to allow the load balancer to reach the instance public IP.

Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.

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.

Q117. 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?

Google Cloud Dataproc

Google Cloud Dataflow

Google Container Engine with Bigtable

Google Compute Engine with Google BigQuery

Q118. For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend
Platform architecture. The game communicates with the backend over a REST API.
You want to follow Google-recommended practices. How should you design the backend?

Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L4 load balancer.

Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L4 load balancer.

Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L7 load balancer.

Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L7 load balancer.

Q119. For this question, refer to the EHR Healthcare case study. You need to define the technical architecture for hybrid connectivity between EHR’s on-premises systems and Google Cloud. You want to follow Google’s recommended practices for production-level applications. Considering the EHR Healthcare business and technical requirements, what should you do?

Configure two Partner Interconnect connections in one metro (City), and make sure the Interconnect connections are placed in different metro zones.

Configure two VPN connections from on-premises to Google Cloud, and make sure the VPN devices on-premises are in separate racks.

Configure Direct Peering between EHR Healthcare and Google Cloud, and make sure you are peering at least two Google locations.

Configure two Dedicated Interconnect connections in one metro (City) and two connections in another metro, and make sure the Interconnect connections are placed in different metro zones.

Q120. For this question, refer to the Dress4Win case study.
Dress4Win would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

Identify self-contained applications with external dependencies as a first move to the cloud.

Identify enterprise applications with internal dependencies and recommend these as a first move to the cloud.

Suggest moving their in-house databases to the cloud and continue serving requests to on-premise applications.

Recommend moving their message queuing servers to the cloud and continue handling requests to on-premise applications.

Q121. 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. 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?

Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.

Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.

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.

Launch a cluster in each region to preprocess and compress the raw data, then move the data into a regional bucket and use a Cloud Dataproc cluster to finish the job.

Q122. Your customer is moving an existing corporate application to Google Cloud Platform from an on-premises data center. The business owners require minimal user disruption. There are strict security team requirements for storing passwords. What authentication strategy should they use?

Use G Suite Password Sync to replicate passwords into Google.

Federate authentication via SAML 2.0 to the existing Identity Provider.

Provision users in Google using the Google Cloud Directory Sync tool.

Ask users to set their Google password to match their corporate password.

Q123. Mountkirk Games wants to limit the physical location of resources to their operating Google Cloud regions.
What should you do?

Configure an organizational policy which constrains where resources can be deployed.

Configure IAM conditions to limit what resources can be configured.

Configure the quotas for resources in the regions not being used to 0.

Configure a custom alert in Cloud Monitoring so you can disable resources as they are created in other regions.

Q124. You are using Cloud Shell and need to install a custom utility for use in a few weeks. Where can you store the file so it is in the default execution path and persists across sessions?

~/bin

Cloud Storage

/google/scripts

/usr/local/bin