Accurate Hot Selling Professional-Cloud-Architect Exam Dumps 2026 Newly Released
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The GCP certification exam covers a wide range of topics related to cloud architecture, including designing and planning a cloud solution architecture, managing and provisioning infrastructure, ensuring security and compliance, and optimizing technical and business processes. Professional-Cloud-Architect exam is designed to assess the candidate's ability to design, develop, and manage scalable, efficient, and secure cloud solutions using GCP technologies.
Google Professional-Cloud-Architect exam is a certification offered by Google Cloud for individuals who have demonstrated their expertise in designing and managing solutions on the Google Cloud Platform. Professional-Cloud-Architect exam is designed to test the knowledge and skills required to architect and deploy secure, scalable, and highly available cloud solutions that meet business and technical requirements. It is intended for professionals who work with cloud-based solutions and want to demonstrate their expertise to potential employers and clients.
Google Professional-Cloud-Architect (Google Certified Professional - Cloud Architect (GCP)) Certification Exam is designed to test the knowledge, skills and expertise of the individuals in designing, developing, and managing secure, scalable, and highly available cloud solutions using Google Cloud Platform (GCP) technologies. Google Certified Professional - Cloud Architect (GCP) certification is ideal for cloud architects, engineers, developers, and IT professionals who want to demonstrate their ability to design and deploy cloud solutions using GCP.
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?
- A. Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.
- B. Use Stackdriver Monitoring to create a dashboard on the project's activity.
- C. Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.
- D. Use Stackdriver Trace to create a trace list analysis.
Answer: A
NEW QUESTION # 171
You want to enable your running Google Container Engine cluster to scale as demand for your application changes.
What should you do?
- A. Create a new Container Engine cluster with the following command:
gcloud alpha container clusters create mycluster --enable-autocaling --min-nodes=1 --max-nodes=10
and redeploy your application. - B. Add additional nodes to your Container Engine cluster using the following command:
gcloud container clusters resize CLUSTER_NAME --size 10 - C. 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 - D. Update the existing Container Engine cluster with the following command:
gcloud alpha container clusters update mycluster --enable-autoscaling --min-nodes=1 --max-nodes=10
Answer: C
Explanation:
https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler
Cluster autoscaling
--enable-autoscaling
Enables autoscaling for a node pool.
Enables autoscaling in the node pool specified by --node-pool or the default node pool if --node-pool is not provided.
Where:
--max-nodes=MAX_NODES
Maximum number of nodes in the node pool.
Maximum number of nodes to which the node pool specified by --node-pool (or default node pool if unspecified) can scale.
Incorrect Answers:
C, D: Warning: Do not use Alpha Clusters or alpha features for production workloads.
Note: You can experiment with Kubernetes alpha features by creating an alpha cluster. Alpha clusters are short-lived clusters that run stable Kubernetes releases with all Kubernetes APIs and features enabled. Alpha clusters are designed for advanced users and early adopters to experiment with workloads that take advantage of new features before those features are production-ready. You can use Alpha clusters just like normal Kubernetes Engine clusters.
NEW QUESTION # 172
Your company pushes batches of sensitive transaction data from its application server VMs to Cloud Pub/Sub for processing and storage. What is the Google-recommended way for your application to authenticate to the required Google Cloud services?
- A. Ensure that VM service accounts do not have access to Cloud Pub/Sub, and use VM access scopes to grant the appropriate Cloud Pub/Sub IAM roles.
- B. Create a gateway to Cloud Pub/Sub using a Cloud Function, and grant the Cloud Function service account the appropriate Cloud Pub/Sub IAM roles.
- C. Ensure that VM service accounts are granted the appropriate Cloud Pub/Sub IAM roles.
- D. Generate an OAuth2 access token for accessing Cloud Pub/Sub, encrypt it, and store it in Cloud Storage for access from each VM.
Answer: C
NEW QUESTION # 173
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 using a signed URL that expires after 24 hours.
- 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. Create an App Engine web application where users can upload images for the next 24 hours. Authenticate users via Cloud Identity.
Answer: C
NEW QUESTION # 174
Your company is forecasting a sharp increase in the number and size of Apache Spark and Hadoop jobs being run on your local datacenter You want to utilize the cloud to help you scale this upcoming demand with the least amount of operations work and code change. Which product should you use?
- A. Google Cloud Dataflow
- B. Google Container Engine
- C. Google Cloud Dataproc
- D. Google Compute Engine
Answer: C
Explanation:
Google Cloud Dataproc is a fast, easy-to-use, low-cost and fully managed service that lets you run the Apache Spark and Apache Hadoop ecosystem on Google Cloud Platform. Cloud Dataproc provisions big or small clusters rapidly, supports many popular job types, and is integrated with other Google Cloud Platform services, such as Google Cloud Storage and Stackdriver Logging, thus helping you reduce TCO.
References: https://cloud.google.com/dataproc/docs/resources/faq
NEW QUESTION # 175
Your company has developed a monolithic, 3-tier application to allow external users to upload and share files. The solution cannot be easily enhanced and lacks reliability. The development team would like to re-architect the application to adopt microservices and a fully managed service approach, but they need to convince their leadership that the effort is worthwhile. Which advantage(s) should they highlight to leadership?
- A. The new approach will be significantly less costly, make it easier to manage the underlying infrastructure, and automatically manage the CI/CD pipelines.
- B. The new approach will make it easier to decouple infrastructure from application, develop and release new features, manage the underlying infrastructure, manage CI/CD pipelines and perform A/B testing, and scale the solution if necessary.
- C. The process can be automated with Migrate for Compute Engine.
- D. The monolithic solution can be converted to a container with Docker. The generated container can then be deployed into a Kubernetes cluster.
Answer: B
Explanation:
The new approach will make it easier to decouple infrastructure from an application, develop and release new features, manage the underlying infrastructure, manage CI/CD pipelines and perform A/B testing, and scale the solution if necessary.
NEW QUESTION # 176
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?
- A. 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. - B. 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. - C. 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.
- D. 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.
Answer: A
NEW QUESTION # 177
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to migrate from their current analytics and statistics reporting model to one that meets their technical requirements on Google Cloud Platform.
Which two steps should be part of their migration plan? (Choose two.)
- A. Write a schema migration plan to denormalize data for better performance in BigQuery.
- B. Integrate Cloud Armor to defend against possible SQL injection attacks in analytics files uploaded to Cloud Storage.
- C. Evaluate the impact of migrating their current batch ETL code to Cloud Dataflow.
- D. Load 10 TB of analytics data from a previous game into a Cloud SQL instance, and run test queries against the full dataset to confirm that they complete successfully.
- E. Draw an architecture diagram that shows how to move from a single MySQL database to a MySQL cluster.
Answer: A,C
Explanation:
https://cloud.google.com/bigquery/docs/loading-data#loading_denormalized_nested_and_repeated_data
NEW QUESTION # 178
For this question, refer to the JencoMart case study.
The JencoMart security team requires that all Google Cloud Platform infrastructure is deployed using a least privilege model with separation of duties for administration between production and development resources. What Google domain and project structure should you recommend?
- A. Create two G Suite accounts to manage users: one for development/test/staging and one for production. Each account should contain one project for every application.
- B. Create a single G Suite account to manage users with each stage of each application in its own project.
- C. Create two G Suite accounts to manage users: one with a single project for all development applications and one with a single project for all production applications.
- D. Create a single G Suite account to manage users with one project for the development/test/staging environment and one project for the production environment.
Answer: D
Explanation:
Note: The principle of least privilege and separation of duties are concepts that, although semantically different, are intrinsically related from the standpoint of security. The intent behind both is to prevent people from having higher privilege levels than they actually need
* Principle of Least Privilege: Users should only have the least amount of privileges required to perform their job and no more. This reduces authorization exploitation by limiting access to resources such as targets, jobs, or monitoring templates for which they are not authorized.
* Separation of Duties: Beyond limiting user privilege level, you also limit user duties, or the specific jobs they can perform. No user should be given responsibility for more than one related function. This limits the ability of a user to perform a malicious action and then cover up that action.
References:
https://cloud.google.com/kms/docs/separation-of-duties
Topic 4, Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
* Databases:
* MySQL - user data, inventory, static data
* Redis - metadata, social graph, caching
* Application servers:
* Tomcat - Java micro-services
* Nginx - static content
* Apache Beam - Batch processing
* Storage appliances:
* iSCSI for VM hosts
* Fiber channel SAN - MySQL databases
* NAS - image storage, logs, backups
* Apache Hadoop/Spark servers:
* Data analysis
* Real-time trending calculations
* MQ servers:
* Messaging
* Social notifications
* Events
* Miscellaneous servers:
* Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
* Build a reliable and reproducible environment with scaled parity of production.
* Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
* Improve business agility and speed of innovation through rapid provisioning of new resources.
* Analyze and optimize architecture for performance in the cloud.
* Migrate fully to the cloud if all other requirements are met.
Technical Requirements
* Evaluate and choose an automation framework for provisioning resources in cloud.
* Support failover of the production environment to cloud during an emergency.
* Identify production services that can migrate to cloud to save capacity.
* Use managed services whenever possible.
* Encrypt data on the wire and at rest.
* Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
NEW QUESTION # 179
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 Compute Engine with Google BigQuery
- C. Google Cloud Dataproc
- D. Google Cloud Dataflow
Answer: D
Explanation:
Dataflow is for processing both the Batch and Stream.
NEW QUESTION # 180
Case Study: 4 - Dress4Win case study
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model.
Company Background
Dress4win's application has grown from a few servers in the founder's garage to several hundred servers and appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster, Dress4win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test environments. They are also considering building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
- MySQL - user data, inventory, static data
- Redis - metadata, social graph, caching
Application servers:
- Tomcat - Java micro-services
- Nginx - static content
- Apache Beam - Batch processing
Storage appliances:
- iSCSI for VM hosts
- Fiber channel SAN - MySQL databases
- NAS - image storage, logs, backups
Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
MQ servers:
- Messaging
- Social notifications
- Events
Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- Business Requirements
Build a reliable and reproducible environment with scaled parity of production. Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud. Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud. Support failover of the production environment to cloud during an emergency. Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a new competitor could use a public cloud platform to offset their up-front investment and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than our current model.
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?
- A. In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an inbound firewall rule
- B. Install the Stackdriver agent on all of the legacy web servers.
- C. Configure their load balancer to pass through the User-Agent HTTP header when the value matches GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)
- D. 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)
Answer: A
Explanation:
https://cloud.google.com/monitoring/uptime-checks/using-uptime-
checks#monitoring_uptime_check_list_ips-console
NEW QUESTION # 181
Dress4win has end to end tests covering 100% of their endpoints.
They want to ensure that the move of cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?
- A. They should add canary tests so developers can measure how much of an impact the new release causes to latency
- B. They should add additional unit tests and production scale load tests on their cloud staging environment.
- C. They should enable google stack driver debugger on the application code to show errors in the code
- D. They should run the end to end tests in the cloud staging environment to determine if the code is working as intended.
Answer: C
NEW QUESTION # 182
For this question, refer to the TerramEarth case study. You need to implement a reliable, scalable GCP solution for the data warehouse for your company, TerramEarth. Considering the TerramEarth business and technical requirements, what should you do?
- A. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs.
- B. Replace the existing data warehouse with a Compute Engine instance with 96 CPUs. Add an additional Compute Engine pre-emptible instance with 32 CPUs.
- C. Replace the existing data warehouse with BigQuery. Use table partitioning.
- D. Replace the existing data warehouse with BigQuery. Use federated data sources.
Answer: D
Explanation:
https://cloud.google.com/solutions/bigquery-data-warehouse#external_sources
https://cloud.google.com/solutions/bigquery-data-warehouse
NEW QUESTION # 183
A development manager is building a new application. He asks you to review his requirements and identify what cloud technologies he can use to meet them. The application must:
1. Be based on open-source technology for cloud portability
2. Dynamically scale compute capacity based on demand
3. Support continuous software delivery
4. Run multiple segregated copies of the same application stack
5. Deploy application bundles using dynamic templates
6. Route network traffic to specific services based on URL
Which combination of technologies will meet all of his requirements?
- A. Google Kubernetes Engine, Jenkins, and Helm
- B. Google Kubernetes Engine, Jenkins, and Cloud Load Balancing
- C. Google Kubernetes Engine and Cloud Load Balancing
- D. Google Kubernetes Engine and Cloud Deployment Manager
Answer: B
Explanation:
Jenkins is an open-source automation server that lets you flexibly orchestrate your build, test, and deployment pipelines. Kubernetes Engine is a hosted version of Kubernetes, a powerful cluster manager and orchestration system for containers.
When you need to set up a continuous delivery (CD) pipeline, deploying Jenkins on Kubernetes Engine provides important benefits over a standard VM-based deployment Incorrect Answers:
A: Helm is a tool for managing Kubernetes charts. Charts are packages of pre-configured Kubernetes resources.
Use Helm to:
* Find and use popular software packaged as Kubernetes charts
* Share your own applications as Kubernetes charts
* Create reproducible builds of your Kubernetes applications
* Intelligently manage your Kubernetes manifest files
* Manage releases of Helm packages
Reference: https://cloud.google.com/solutions/jenkins-on-kubernetes-engine
NEW QUESTION # 184
Your company wants you to build a highly reliable web application with a few public APIs as the backend. You don't expect a lot of user traffic, but traffic could spike occasionally. You want to leverage Cloud Load Balancing, and the solution must be cost-effective for users. What should you do?
- A. Store static content such as HTML and images in Cloud CDN. Use Cloud Run to host the APIs and save the user data in Cloud SQL.
- B. Store static content such as HTML and images in a Cloud Storage bucket. Host the APIs on a zonal Google Kubernetes Engine cluster with worker nodes in multiple zones, and save the user data in Cloud Spanner.
- C. Store static content such as HTML and images in a Cloud Storage bucket. Use Cloud Functions to host the APIs and save the user data in Firestore.
- D. Store static content such as HTML and images in Cloud CDN. Host the APIs on App Engine and store the user data in Cloud SQL.
Answer: C
NEW QUESTION # 185
You have broken down a legacy monolithic application into a few containerized RESTful microservices. You want to run those microservices on Cloud Run. You also want to make sure the services are highly available with low latency to your customers. What should you do?
- A. Deploy Cloud Run services to multiple regions Create serverless network endpoint groups pointing to the services. Add the serverless NE Gs to a backend service that is used by a global HTIP(S) Load Balancing instance.
- B. Deploy Cloud Run services to multiple availability zones. Create Cloud Endpoints that point to the services. Create a global HTIP(S) Load Balancing instance and attach the Cloud Endpoints to its backend.
- C. Cloud Run services to multiple regions. In Cloud DNS, create a latency-based DNS name that points to the services.
- D. Deploy Cloud Run services to multiple availability zones. Create a TCP/IP global load balancer. Add the Cloud Run Endpoints to its backend service.
Answer: A
Explanation:
Explanation
https://cloud.google.com/run/docs/multiple-regions
NEW QUESTION # 186
You need to develop procedures to test a disaster plan for a mission-critical application. You want to use Google-recommended practices and native capabilities within GCP.
What should you do?
- A. Use gcloud scripts to automate service provisioning. Use Stackdriver to monitor and debug your tests.
- B. Use Deployment Manager to automate provisioning. Use Stackdriver to monitor and debug your tests.
- C. Use Deployment Manager to automate service provisioning. Use Activity Logs to monitor and debug your tests.
- D. Use gcloud scripts to automate service provisioning. Use Activity Logs monitor and debug your tests.
Answer: B
NEW QUESTION # 187
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.
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?
- A. 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. - B. 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.
- C. 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.
- D. 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.
Answer: B
Explanation:
Enable a bucket lifecycle management rule to delete objects older than 36 months. Use partitioned tables in BigQuery and set the partition expiration period to 36 months. is the right answer.
When you create a table partitioned by ingestion time, BigQuery automatically loads data into daily, date-based partitions that reflect the data's ingestion or arrival time.
Ref: https://cloud.google.com/bigquery/docs/partitioned-tables#ingestion_time And Google recommends you configure the default table expiration for your datasets, configure the expiration time for your tables, and configure the partition expiration for partitioned tables.
Ref: https://cloud.google.com/bigquery/docs/best-practices-
storage#use_the_expiration_settings_to_remove_unneeded_tables_and_partitions If the partitioned table has a table expiration configured, all the partitions in it are deleted according to the table expiration settings. For our specific requirement, we could set the partition expiration to 36 months so that partitions older than 36 months (and the data within) are automatically deleted.
Ref: https://cloud.google.com/bigquery/docs/managing-partitioned-tables#partition-expiration
NEW QUESTION # 188
Your company has a support ticketing solution that uses App Engine Standard. The project that contains the App Engine application already has a Virtual Private Cloud(VPC) network fully connected to the company's on-premises environment through a Cloud VPN tunnel. You want to enable App Engine application to communicate with a database that is running in the company's on-premises environment. What should you do?
- A. Configure serverless VPC access
- B. Configure private Google access
- C. Configure private Google access for on-premises hosts only
- D. Configure private services access
Answer: D
Explanation:
https://cloud.google.com/appengine/docs/standard/python3/connecting-vpc
https://cloud.google.com/appengine/docs/flexible/python/using-third-party-databases#on_premises
NEW QUESTION # 189
Your company's user-feedback portal comprises a standard LAMP stack replicated across two zones. It is deployed in the us-central1 region and uses autoscaled managed instance groups on all layers, except the database. Currently, only a small group of select customers have access to the portal. The portal meets a
99.99% availability SLA under these conditions However next quarter, your company will be making the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once they introduce additional user load. What should you do?
- A. Capture existing users input, and replay captured user load until autoscale is triggered on all layers. At the same time, terminate all resources in one of the zones.
- B. Expose the new system to a larger group of users, and increase group ' size each day until autoscale logic is tnggered on all layers. At the same time, terminate random resources on both zones.
- C. Capture existing users input, and replay captured user load until resource utilization crosses 80%. Also, derive estimated number of users based on existing users usage of the app, and deploy enough resources to handle 200% of expected load.
- D. Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce "chaos" to the system by terminating random resources on both zones.
Answer: C
NEW QUESTION # 190
You are using Cloud CDN to deliver static HTTP(S) website content hosted on a Compute Engine instance
group. You want to improve the cache hit ratio.
What should you do?
- A. Customize the cache keys to omit the protocol from the key.
- B. Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that
bucket. - C. Shorten the expiration time of the cached objects.
- D. Make sure the HTTP(S) header "Cache-Region" points to the closest region of your users.
Answer: A
Explanation:
Explanation/Reference:
Reference https://cloud.google.com/cdn/docs/best-
practices#using_custom_cache_keys_to_improve_cache_hit_ratio
NEW QUESTION # 191
For this question, refer to the Dress4Win case study.
Dress4Win has asked you to recommend machine types they should deploy their application servers to. How should you proceed?
- A. Identify the number of virtual cores and RAM associated with the application server virtual machines align them to a custom machine type in the cloud, monitor performance, and scale the machine types up until the desired performance is reached.
- B. Recommend that Dress4Win deploy into production with the smallest instances available, monitor them over time, and scale the machine type up until the desired performance is reached.
- C. Recommend that Dress4Win deploy application servers to machine types that offer the highest RAM to CPU ratio available.
- D. Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types in the cloud.
Answer: B
Explanation:
Topic 3, Dress4Win Case 2
Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a website and mobile application. The company also cultivates an active social network that connects their users with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a freemium app model. The application has grown from a few servers in the founder's garage to several hundred servers and appliances in a collocated data center. However, the capacity of their infrastructure is now insufficient for the application's rapid growth. Because of this growth and the company's desire to innovate faster. Dress4Win is committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is moving their development and test environments. They are also building a disaster recovery site, because their current infrastructure is at a single location. They are not sure which components of their architecture they can migrate as is and which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location. All servers run Ubuntu LTS v16.04.
Databases:
MySQL. 1 server for user data, inventory, static data:
- MySQL 5.8
- 8 core CPUs
- 128 GB of RAM
- 2x 5 TB HDD (RAID 1)
Redis 3 server cluster for metadata, social graph, caching. Each server is:
- Redis 3.2
- 4 core CPUs
- 32GB of RAM
Compute:
40 Web Application servers providing micro-services based APIs and static content.
- Tomcat - Java
- Nginx
- 4 core CPUs
- 32 GB of RAM
20 Apache Hadoop/Spark servers:
- Data analysis
- Real-time trending calculations
- 8 core CPUS
- 128 GB of RAM
- 4x 5 TB HDD (RAID 1)
3 RabbitMQ servers for messaging, social notifications, and events:
- 8 core CPUs
- 32GB of RAM
Miscellaneous servers:
- Jenkins, monitoring, bastion hosts, security scanners
- 8 core CPUs
- 32GB of RAM
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
- 1 PB total storage; 400 TB available
NAS - image storage, logs, backups
- 100 TB total storage; 35 TB available
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management (IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Technical Requirements
Easily create non-production environment in the cloud.
Implement an automation framework for provisioning resources in cloud.
Implement a continuous deployment process for deploying applications to the on-premises datacenter or cloud.
Support failover of the production environment to cloud during an emergency.
Encrypt data on the wire and at rest.
Support multiple private connections between the production data center and cloud environment.
Executive Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They are also concerned that a competitor could use a public cloud platform to offset their up-front investment and free them to focus on developing better features. Our traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is sitting idle.
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total cost of ownership (TCO) analysis over the next 5 years for a public cloud strategy achieves a cost reduction between 30% and 50% over our current model.
NEW QUESTION # 192
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