Professional-Cloud-Architect Self-Study Guide for Becoming an Google Certified Professional – Cloud Architect (GCP) Expert [Q169-Q191]

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Professional-Cloud-Architect Self-Study Guide for Becoming an Google Certified Professional – Cloud Architect (GCP) Expert

Professional-Cloud-Architect Study Guide Realistic Verified Professional-Cloud-Architect Dumps

Google Professional-Cloud-Architect Exam Syllabus Topics:

Section	Objectives
Ensuring solution and operations reliability	– Assisting with support 1. Capacity planning and scaling 2. Incident response and troubleshooting – Deployment and release management 1. Release management and versioning 2. Deployment strategies and rollback – Monitoring/logging/profiling/alerting solution 1. Cloud Monitoring and Cloud Logging 2. Performance profiling and tracing 3. Error reporting and alerting – Evaluating quality control measures
Analyzing and optimizing technical and business processes	– Analyzing and defining business processes 1. Cost management and optimization 2. Business KPIs and metrics 3. Stakeholder communication – Analyzing and defining technical processes 1. CI/CD pipeline design 2. Software development lifecycle (SDLC) 3. Incident management and troubleshooting
Designing and planning a cloud solution architecture	– Designing network, storage, and compute resources 1. Network design including load balancing and firewall rules 2. Storage options and data lifecycle management 3. Compute engine selection and configuration 4. GKE cluster and workload design – Enabling future cloud technology 1. Implementing future-proof architectures 2. Designing for scalability and elasticity – Creating a migration plan 1. Planning data migration 2. Identifying workloads for migration 3. Refactoring and rearchitecting applications – Designing solution infrastructure that meets business requirements 1. Migration planning 2. Cost optimization 3. Business use cases and product strategy 4. Networking and compute resources 5. Data and storage architecture 6. Integration with existing systems
Managing implementation	– Advising development/operation team(s) to ensure successful deployment 1. Application development best practices 2. Testing and validation 3. Deployment strategies – Interacting with Google Cloud programmatically 1. APIs and client libraries 2. Cloud SDK and gcloud CLI 3. Infrastructure as Code (IaC)
Managing and provisioning a solution infrastructure	– Configuring individual storage systems 1. Cloud Storage configuration 2. Datastore and Bigtable 3. Cloud SQL and Spanner – Configuring compute systems 1. Compute Engine configuration 2. GKE configuration and management 3. Cloud Run and Cloud Functions – Configuring network topologies 1. Hybrid and multi-cloud connectivity 2. VPC design and peering 3. Private access and VPN configuration
Designing for security and compliance	– Designing for compliance 1. Audit logging and monitoring 2. Data residency and sovereignty 3. Regulatory and compliance requirements – Designing for security 1. Data security and encryption 2. Identity and Access Management (IAM) 3. Network security 4. Application security

NEW QUESTION 169
Your company is planning to perform a lift and shift migration of their Linux RHEL 6.5+ virtual machines.
The virtual machines are running in an on-premises VMware environment. You want to migrate them to Compute Engine following Google-recommended practices. What should you do?

1. Define a migration plan based on the list of the applications and their dependencies.
2. Migrate all virtual machines into Compute Engine individually with Migrate for Compute Engine.

1. Perform an assessment of virtual machines running in the current VMware environment.
2.Create images of all disks. Import disks on Compute Engine.
3.Create standard virtual machines where the boot disks are the ones you have imported.

1. Perform an assessment of virtual machines running in the current VMware environment.
2. Define a migration plan, prepare a Migrate for Compute Engine migration RunBook, and execute the migration.

1. Perform an assessment of virtual machines running in the current VMware environment.
2.Install a third-party agent on all selected virtual machines.
3.Migrate all virtual machines into Compute Engine.

NEW QUESTION 170
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.

NEW QUESTION 171
Your company has just acquired another company, and you have been asked to integrate their existing Google Cloud environment into your company’s data center. Upon investigation, you discover that some of the RFC 1918 IP ranges being used in the new company’s Virtual Private Cloud (VPC) overlap with your data center IP space. What should you do to enable connectivity and make sure that there are no routing conflicts when connectivity is established?

Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply new IP addresses so there is no overlapping IP space.

Create a Cloud VPN connection from the new VPC to the data center, and create a Cloud NAT instance to perform NAT on the overlapping IP space.

Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply a custom route advertisement to block the overlapping IP space.

Create a Cloud VPN connection from the new VPC to the data center, and apply a firewall rule that blocks the overlapping IP space.

NEW QUESTION 172
For this question, refer to the TerramEarth case study.
You start to build a new application that uses a few Cloud Functions for the backend. One use case requires a Cloud Function func_display to invoke another Cloud Function func_query. You want func_query only to accept invocations from func_display. You also want to follow Google’s recommended best practices. What should you do?

Create a token and pass it in as an environment variable to func_display. When invoking func_query, include the token in the request Pass the same token to func _query and reject the invocation if the tokens are different.

Make func_query ‘Require authentication.’ Create a unique service account and associate it to func_display. Grant the service account invoker role for func_query. Create an id token in func_display and include the token to the request when invoking func_query.

Make func _query ‘Require authentication’ and only accept internal traffic. Create those two functions in the same VPC. Create an ingress firewall rule for func_query to only allow traffic from func_display.

Create those two functions in the same project and VPC. Make func_query only accept internal traffic.Create an ingress firewall for func_query to only allow traffic from func_display. Also, make sure both functions use the same service account.

NEW QUESTION 173
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)

NEW QUESTION 174
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?

Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.

Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.

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.

Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity.

NEW QUESTION 175
Case Study: 9 – Helicopter Racing League
Company overview
Helicopter Racing League (HRL) is a global sports league for competitive helicopter racing. Each year HRL holds the world championship and several regional league competitions where teams compete to earn a spot in the world championship. HRL offers a paid service to stream the races all over the world with live telemetry and predictions throughout each race.
Solution concept
HRL wants to migrate their existing service to a new platform to expand their use of managed AI and ML services to facilitate race predictions. Additionally, as new fans engage with the sport, particularly in emerging regions, they want to move the serving of their content, both real-time and recorded, closer to their users.
Existing technical environment
HRL is a public cloud-first company; the core of their mission-critical applications runs on their current public cloud provider. Video recording and editing is performed at the race tracks, and the content is encoded and transcoded, where needed, in the cloud. Enterprise-grade connectivity and local compute is provided by truck-mounted mobile data centers. Their race prediction services are hosted exclusively on their existing public cloud provider. Their existing technical environment is as follows:
– Existing content is stored in an object storage service on their existing public cloud provider.
– Video encoding and transcoding is performed on VMs created for each job.
– Race predictions are performed using TensorFlow running on VMs in the current public cloud
provider.
Business requirements
HRL’s owners want to expand their predictive capabilities and reduce latency for their viewers in emerging markets. Their requirements are:
– Support ability to expose the predictive models to partners.
– Increase predictive capabilities during and before races:
*Race results
*Mechanical failures
*Crowd sentiment
– Increase telemetry and create additional insights.
– Measure fan engagement with new predictions.
– Enhance global availability and quality of the broadcasts.
– Increase the number of concurrent viewers.
– Minimize operational complexity.
– Ensure compliance with regulations.
– Create a merchandising revenue stream.
Technical requirements
– Maintain or increase prediction throughput and accuracy.
– Reduce viewer latency.
– Increase transcoding performance.
– Create real-time analytics of viewer consumption patterns and engagement.
– Create a data mart to enable processing of large volumes of race data.
Executive statement
Our CEO, S. Hawke, wants to bring high-adrenaline racing to fans all around the world. We listen to our fans, and they want enhanced video streams that include predictions of events within the race (e.g., overtaking). Our current platform allows us to predict race outcomes but lacks the facility to support real-time predictions during races and the capacity to process season-long results.
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?

Store the card data in Secret Manager after running a query to identify duplicates.

Encrypt the card data with a deterministic algorithm stored in Firestore using Datastore mode.

Encrypt the card data with a deterministic algorithm and shard it across multiple Memorystore instances.

Use column-level encryption to store the data in Cloud SQL.

NEW QUESTION 176
Your team is redacting a new application that is about to go into production. During testing, it emerges that a developer code allows user input to be used to modify the application and execute commands.This event has thrown everyone into despair and has generated the fear that there are other problems of this type in the system. Which of the following services may help you?

Cloud Armor

Web Security Scanner

Security Command Center

Shielded GKE nodes

NEW QUESTION 177
You need to migrate Hadoop jobs for your company’s Data Science team without modifying the underlying infrastructure. You want to minimize costs and infrastructure management effort. What should you do?

Create a Dataproc cluster using standard worker instances.

Create a Dataproc cluster using preemptible worker instances.

Manually deploy a Hadoop cluster on Compute Engine using standard instances.

Manually deploy a Hadoop cluster on Compute Engine using preemptible instances.

NEW QUESTION 178
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?

Help the engineer to convert his websocket code to use HTTP streaming

Review the encryption requirements for websocket connections with the security team

Meet with the cloud operations team and the engineer to discuss load balancer options

Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.

NEW QUESTION 179
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

NEW QUESTION 180
You want to store critical business information in Cloud Storage buckets. The information is regularly changed but previous versions need to be referenced on a regular basis. You want to ensure that there is a record of all changes to any information in these buckets. You want to ensure that accidental edits or deletions can be easily roiled back. Which feature should you enable?

Bucket Lock

Object Versioning

Object change notification

Object Lifecycle Management

NEW QUESTION 181
For this question, refer to the TerramEarth case study.
TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?

Have the vehicle’ computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.

Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.

Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.

Have the vehicle’s computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.

NEW QUESTION 182
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. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

Create a BigQuery table for the European data, and set the table retention period to 36 months.
For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of 36 months.

Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.

NEW QUESTION 183
A lead engineer wrote a custom tool that deploys virtual machines in the legacy data center. He wants to migrate the custom tool to the new cloud environment You want to advocate for the adoption of Google Cloud Deployment Manager What are two business risks of migrating to Cloud Deployment Manager?
Choose 2 answers

Cloud Deployment Manager uses Python.

Cloud Deployment Manager APIs could be deprecated in the future.

Cloud Deployment Manager is unfamiliar to the company’s engineers.

Cloud Deployment Manager requires a Google APIs service account to run.

Cloud Deployment Manager can be used to permanently delete cloud resources.

Cloud Deployment Manager only supports automation of Google Cloud resources.

NEW QUESTION 184
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?

Configure their replication to use UDP.

Configure a Google Cloud Dedicated Interconnect.

Restore their database daily using Google Cloud SQL.

Add additional VPN connections and load balance them.

Send the replicated transaction to Google Cloud Pub/Sub.

NEW QUESTION 185
For this question, refer to the Cymbal Retail case study. Cymbal has a centralized project that supports large video files for Vertex Al model training. Standard storage costs have suddenly increased this month, and you need to determine why. What should you do?

Investigate if the project owner disabled a soft-delete policy on the bucket holding the video files.

Investigate if the project owner moved from dual-region storage to region storage

Investigate If the project owner enabled a soft-delete policy on the bucket holding the video files.

Investigate if the project owner moved from multi-region storage to region stotage.

NEW QUESTION 186
You want to enable your running Google Kubernetes Engine cluster to scale as demand for your application changes.
What should you do?

Add additional nodes to your Kubernetes Engine cluster using the following command:gcloud container clusters resizeCLUSTER_Name – -size 10

Add a tag to the instances in the cluster with the following command:gcloud compute instances add-tagsINSTANCE – -tags enable-autoscaling max-nodes-10

Update the existing Kubernetes Engine cluster with the following command:gcloud alpha container clustersupdate mycluster – -enable-autoscaling – -min-nodes=1 – -max-nodes=10

Create a new Kubernetes Engine cluster with the following command:gcloud alpha container clusterscreate mycluster – -enable-autoscaling – -min-nodes=1 – -max-nodes=10and redeploy your application

NEW QUESTION 187
Case Study: 13 – KnightMotives Automotive
Company Overview
KnightMotives is a car manufacturer specializing in autonomous, self-driving vehicles, including Battery Electric Vehicles (BEVs), hybrids and traditional internal combustion engine (ICE) vehicles. While KnightMotives has made strides with the in-vehicle experience in their BEV fleet, the hybrid and ICE vehicles have yet to implement these new systems and are viewed poorly by critics and drivers. The lack of modern in-vehicle technology in hybrid and ICE vehicles has resulted in declining sales and customer satisfaction.
KnightMotives wants to modernize the consumer experience across all vehicles within five years Artificial Intelligence offers a unique opportunity to revolutionize the in-vehicle experience, as well as the shopping buying and service/maintenance experience. Investment in this new technology will require a shift in financial priorities on a global scale.
KnightMotives also wants to improve their online ordering system, which is unreliable. Systems for customers to build their vehicle online for acquisition through a dealer are not delivering the data or reliability that dealers need, causing. A strain in the relationship between KnightMotives and dealers. Service technicians and sales staff need better tooling to enhance dealer successes, including built-to-order vehicles.
Solution Concept
KnightMotives wants to shift from manufacturing cars to creating a complete and compelling
“automotive experience.” Then strategy prioritizes delivering a consistent experience across all models, developing AI-powered features, generating new revenue from data monetization, adopting a digital focus to differentiate their brand from competitors, and developing better tools for mechanics and salespeople.
Existing Technical Environment
KnightMotives’s IT is largely on-premises with some applications on major cloud platforms. Their supply chain runs on an outdated mainframe, and Enterprise Resource Planning (ERP) is also outdated, making new promotions and dealer discounts difficult to implement. Dealers have no budget for new equipment. There is fragmentation across vehicles with multiple code bases, and significant technical debt from supporting backwards compatibility. Network connectivity to manufacturing plants and vehicle connectivity in rural areas are challenges.
Business Requirements
Key business requirements include fostering a personalized relationship with the driver and delivering a cohesive experience across all models. Creating a better build-to-order model will reduce time on the lot and provide transparency for both dealers and customers. Additionally, KnightMotives seeks to monetize corporate data to finance new technology investments, as their current AI infrastructure is obsolete and corporate data remains siloed. Security is a paramount concern due to past data breaches Adherence to European Union (EU) data protection regulations, especially for emerging autonomous platforms, is critical.
KnightMotives plans to make significant investments in fully autonomous driving capabilities, with initial implementation targeting regions with favorable regulatory environments. Prioritizing employee upskilling, attracting top-tier talent, and fostering better communication between business and technical teams are also critical objectives.
Technical Requirements
– Modernizing the in-vehicle experience includes developing a consistent user experience (UX)
that seamlessly integrates AI-powered features across all models, updating in-vehicle hardware and software in legacy models to support new UX features and AI capabilities, and ensuring reliable network connectivity, especially in rural areas, to support real-time AI features and data transmission.
– Network upgrades are necessary to support increased data traffic and improve connectivity
between plants and headquarters.
– IT infrastructure modernization requires adopting a hybrid cloud strategy to leverage the
benefits of both on-premises and cloud infrastructure, and gradually modernizing or replacing legacy systems to improve efficiency and agility.
– Autonomous vehicle development and testing requires investing in cutting-edge AI and machine
learning technologies, building a robust simulation environment, and ensuring compliance with evolving regulations related to autonomous vehicles.
– Data monetization and insights requires implementing a robust data management platform,
strict data security and privacy measures, and a scalable AI/ML infrastructure.
– Increased focus on security and risk management involves implementing a comprehensive
security framework to protect against cyber threats and data breaches, developing an incident response plan, and providing security awareness training to employees.
– Providing a delightful experience for dealers and customers requires improving the online build-
to-order system; developing modern dealer tools to streamline dealer operations, including sales, service, and inventory management; and implementing a comprehensive Customer Relationship Management (CRM) system to track customer interactions personalize experiences, and improve customer satisfaction.
Executive Statement
KnightMotives is committed to enhancing safety and saving lives by leveraging an extensive body of data – encompassing driving, road conditions, behavioral studies, and crash safety statistics – to create compelling digital experiences for drivers. Our AI consistently outperforms national safety statistics, ensuring the unique and coveted KnightMotives experience is aligned across all our vehicle models.
Michael Knight, KnightMotives CEO
For this question, refer to the KnightMotives Automotive case study, KnightMotives has deployed their new Dealer Tools on Google Kubernetes Engine (GKE). You are supporting KnightMotives in the performance of the GKE workloads. Some of the Pods are Statefull. To ensure these Pods do not consume an unlimited amount of CPU, you have configured resource limits on the Deployments. You have identified that these Pods were allocated too much CPU and are actually consuming drastically less some of the time. You want to optimize resource usage and allow maximum flexibility in case of higher load. What should you do?

Configure resource requests per Deployment. Set resource requests slightly above the typical CPU usage observed during monitoring.

Configure resource requests per Deployment. Ensure the requests are equal to the current limits.

Enable vertical Pod autoscaling on each Deployment. Ensure the autoscaling mode is set to Auto.

Enable horizontal Pod autoscaling on each Deployment. Ensure the minimum number of Pods is lower than the currently configured amount in the Deployment.

NEW QUESTION 188
What is the command for creating a storage bucket that has once per month access and is named ‘archive_bucket’?

gsutil rm -coldline gs://archive_bucket

gsutil mb -c coldline gs://archive_bucket

gsutil mb -c nearline gs://archive_bucket

gsutil mb gs://archive_bucket

NEW QUESTION 189
For this question, refer to the Dress4Win case study. You are responsible for the security of data stored in
Cloud Storage for your company, Dress4Win. You have already created a set of Google Groups and
assigned the appropriate users to those groups. You should use Google best practices and implement the
simplest design to meet the requirements.
Considering Dress4Win’s business and technical requirements, what should you do?

Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.
Encrypt data with a customer-supplied encryption key when storing files in Cloud Storage.

Assign custom IAM roles to the Google Groups you created in order to enforce security requirements.
Enable default storage encryption before storing files in Cloud Storage.

Assign predefined IAM roles to the Google Groups you created in order to enforce security
requirements. Utilize Google’s default encryption at rest when storing files in Cloud Storage.

Assign predefined IAM roles to the Google Groups you created in order to enforce security
requirements. Ensure that the default Cloud KMS key is set before storing files in Cloud Storage.

NEW QUESTION 190
TerramEarth has equipped all connected trucks with servers and sensors to collect telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs.
What should they do?

Have the vehicle’s computer compress the data in hourly snapshots, and store it in a Google Cloud Storage (GCS) Nearline bucket

Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery

Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable

Have the vehicle’s computer compress the data in hourly snapshots, and store it in a GCS Coldline bucket

NEW QUESTION 191
You are analyzing and defining business processes to support your startup’s trial usage of GCP, and you don’t yet know what consumer demand for your product will be. Your manager requires you to minimize GCP service costs and adhere to Google best practices. What should you do?

Utilize free tier and sustained use discounts. Provision a staff position for service cost management.

Utilize free tier and sustained use discounts. Provide training to the team about service cost management.

Utilize free tier and committed use discounts. Provision a staff position for service cost management.

Utilize free tier and committed use discounts. Provide training to the team about service cost management.

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Professional-Cloud-Architect Self-Study Guide for Becoming an Google Certified Professional – Cloud Architect (GCP) Expert [Q169-Q191]

Google Professional-Cloud-Architect Exam Syllabus Topics:

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