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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 Certification Path
The Google Professional Cloud Architect Certification is the highest level of certification mainly focussing to the Solution Architect Professional. There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google professional Cloud Architect. You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path
To prepare for the Google Professional-Cloud-Architect exam, candidates should have experience in designing and implementing cloud solutions using GCP. They should also have a good understanding of cloud computing concepts, such as virtualization, networking, and storage. Google recommends that candidates complete the Architecting with Google Cloud Platform specialization on Coursera before taking the exam.
NEW QUESTION # 72
Mountkirk Games wants to limit the physical location of resources to their operating Google Cloud regions.
What should you do?
- A. Configure a custom alert in Cloud Monitoring so you can disable resources as they are created in other regions.
- B. Configure the quotas for resources in the regions not being used to 0.
- C. Configure an organizational policy which constrains where resources can be deployed.
- D. Configure IAM conditions to limit what resources can be configured.
Answer: C
NEW QUESTION # 73
A small number of API requests to your microservices-based application take a very long time.
You know that each request to the API can traverse many services. You want to know which service takes the longest in those cases. What should you do?
- A. Set timeouts on your application so that you can fail requests faster.
- B. Send custom metrics for each of your requests to Stackdriver Monitoring.
- C. Instrument your application with Stackdnver Trace in order to break down the request latencies at each microservice.
- D. Use Stackdriver Monitoring to look for insights that show when your API latencies are high.
Answer: C
Explanation:
https://cloud.google.com/trace/docs/overview
NEW QUESTION # 74
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections.
What should you do?
- A. Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in US, EU, and Asia. Run the ETL process using the data in the bucket
- B. Directly transfer the files to a different Google Cloud Regional Storage bucket location in US, EU, and Asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket
- C. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in US, EU, and Asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket
- D. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket
Answer: B
NEW QUESTION # 75
For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput. What are three potential bottlenecks? (Choose 3 answers.)
- A. A separate storage layer outside the VMs, which is not suited for this task
- B. A copy command that is not suited to operate over long distances
- C. A single VPN tunnel, which limits throughput
- D. Complicated internet connectivity between the on-premises infrastructure and GCP
- E. Fewer virtual machines (VMs) in GCP than on-premises machines
- F. A tier of Google Cloud Storage that is not suited for this task
Answer: A,C,D
NEW QUESTION # 76
For this question, refer to the Dress4Win case study.
Dress4Win has asked you for advice on how to migrate their on-premises MySQL deployment to the cloud. They want to minimize downtime and performance impact to their on-premises solution during the migration. Which approach should you recommend?
- A. Create a new MySQL cluster in the cloud, configure applications to begin writing to both on-premises and cloud MySQL masters, and destroy the original cluster at cutover.
- B. Create a dump of the on-premises MySQL master server, and then shut it down, upload it to the cloud environment, and load into a new MySQL cluster.
- C. Create a dump of the MySQL replica server into the cloud environment, load it into:
Google Cloud Datastore, and configure applications to read/write to Cloud Datastore at cutover. - D. Setup a MySQL replica server/slave in the cloud environment, and configure it for asynchronous replication from the MySQL master server on-premises until cutover.
Answer: D
NEW QUESTION # 77
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?
- A. Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.
- B. Use OpenVPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- C. Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- D. Configure a direct peering connection between the on-premises environment and Google Cloud.
Answer: A
Explanation:
Reference https://cloud.google.com/architecture/setting-up-private-access-to-cloud-apis-through-vpn-tunnels
NEW QUESTION # 78
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 a single G Suite account to manage users with one project for the development/test/staging environment and one project for the production environment.
- B. 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.
- C. 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.
- D. Create a single G Suite account to manage users with each stage of each application in its own project.
Answer: C
NEW QUESTION # 79
Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?
- A. Have each developer install a pre-commit hook on their workstation that tests the code and builds the container when committing on the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
- B. Create a Cloud Build trigger based on the development branch to build a new container image and store it in Container Registry. Rely on Vulnerability Scanning to ensure the code tests succeed. As the final step of the Cloud Build process, deploy the new container image on the development cluster. Ensure only Cloud Build has access to deploy new versions.
- C. Create a Cloud Build trigger based on the development branch that tests the code, builds the container, and stores it in Container Registry. Create a deployment pipeline that watches for new images and deploys the new image on the development cluster. Ensure only the deployment tool has access to deploy new versions.
- D. Install a post-commit hook on the remote git repository that tests the code and builds the container when code is pushed to the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
Answer: A
NEW QUESTION # 80
You are creating a solution to remove backup files older than 90 days from your backup Cloud Storage bucket. You want to optimize ongoing Cloud Storage spend.
What should you do?
- A. Schedule a cron script using gsutil ls -l gs://backups/**to find and remove items older than
90 days and schedule it with cron - B. Write a lifecycle management rule in JSON and push it to the bucket with gsutil
- C. Write a lifecycle management rule in XML and push it to the bucket with gsutil
- D. Schedule a cron script using gsutil ls -lr gs://backups/**to find and remove items older than 90 days
Answer: B
NEW QUESTION # 81
For this question, refer to the TerramEarth case study.
To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?
- A. Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.
- B. Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.
- C. Use one Google Container Engine cluster of FTP servers. Save the data to a Multi- Regional bucket. Run the ETL process using data in the bucket.
- D. Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.
Answer: B
NEW QUESTION # 82
Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?
- A. Use OpenVPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- B. Configure a direct peering connection between the on-premises environment and Google Cloud.
- C. Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.
- D. Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.
Answer: C
Explanation:
Reference:
Reference https://cloud.google.com/architecture/setting-up-private-access-to-cloud-apis-through-vpn-tunnels
NEW QUESTION # 83
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?
- A. Have you engineers inspect the data for patterns, and then create an algorithm with rules that make operational adjustments automatically
- B. 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
- C. Capture all operating data, train machine learning models that identify ideal operations, and run locally to make operational adjustments automatically
- D. Implement a Google Cloud Dataflow streaming job with a sliding window, and use Google Cloud Messaging (GCM) to make operational adjustments automatically
Answer: B
Explanation:
Explanation/Reference:
References: https://cloud.google.com/customers/ocado/
TerramEarth, B
Testlet 1
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 our 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.
NEW QUESTION # 84
For this question, refer to the TerramEarth case study. Considering the technical requirements, how should you reduce the unplanned vehicle downtime in GCP?
- A. Use Cloud Dataproc Hive as the data warehouse. Directly stream data into partitioned Hive tables. Use Pig scripts to analyze data.
- B. Use BigQuery as the data warehouse. Connect all vehicles to the network and stream data into BigQuery using Cloud Pub/Sub and Cloud Dataflow. Use Google Data Studio for analysis and reporting.
- C. Use Cloud Dataproc Hive as the data warehouse. Upload gzip files to a Multi-Regional Cloud Storage bucket. Upload this data into BigQuery using gcloud. Use Google Data Studio for analysis and reporting.
- D. Use BigQuery as the data warehouse. Connect all vehicles to the network and upload gzip files to a Multi- Regional Cloud Storage bucket using gcloud. Use Google Data Studio for analysis and reporting.
Answer: B
NEW QUESTION # 85
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must
meet their technical requirements.
Which combination of Google technologies will meet all of their requirements?
- A. Cloud SQL, Cloud Storage, Cloud Pub/Sub, and Cloud Dataflow
- B. Kubernetes Engine, Cloud Pub/Sub, and Cloud SQL
- C. Cloud Dataproc, Cloud Pub/Sub, Cloud SQL, and Cloud Dataflow
- D. Cloud Pub/Sub, Compute Engine, Cloud Storage, and Cloud Dataproc
- E. Cloud Dataflow, Cloud Storage, Cloud Pub/Sub, and BigQuery
Answer: E
Explanation:
Explanation/Reference:
Explanation:
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered
by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure
reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the
cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture
streaming metrics, run intensive analytics.
Requirements for Game Analytics Platform
1. Dynamically scale up or down based on game activity
2. Process incoming data on the fly directly from the game servers
3. Process data that arrives late because of slow mobile networks
4. Allow SQL queries to access at least 10 TB of historical data
5. Process files that are regularly uploaded by users' mobile devices
6. Use only fully managed services
References: https://cloud.google.com/solutions/big-data/stream-analytics/
Testlet 1
Company Overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They build all of
their games using some server-side integration. Historically, they have used cloud providers to lease
physical servers.
Due to the unexpected popularity of some of their games, they have had problems scaling their global
audience, application servers, MySQL databases, and analytics tools.
Their current model is to write game statistics to files and send them through an ETL tool that loads them
into a centralized MySQL database for reporting.
Solution Concept
Mountkirk Games is building a new game, which they expect to be very popular. They plan to deploy the
game's backend on Google Compute Engine so they can capture streaming metrics, run intensive
analytics, and take advantage of its autoscaling server environment and integrate with a managed NoSQL
database.
Business Requirements
Increase to a global footprint.
Improve uptime - downtime is loss of players.
Increase efficiency of the cloud resources we use.
Reduce latency to all customers.
Technical Requirements
Requirements for Game Backend Platform
Dynamically scale up or down based on game activity.
Connect to a transactional database service to manage user profiles and game state.
Store game activity in a timeseries database service for future analysis.
As the system scales, ensure that data is not lost due to processing backlogs.
Run hardened Linux distro.
Requirements for Game Analytics Platform
Dynamically scale up or down based on game activity
Process incoming data on the fly directly from the game servers
Process data that arrives late because of slow mobile networks
Allow queries to access at least 10 TB of historical data
Process files that are regularly uploaded by users' mobile devices
Executive Statement
Our last successful game did not scale well with our previous cloud provider, resulting in lower user
adoption and affecting the game's reputation. Our investors want more key performance indicators (KPIs)
to evaluate the speed and stability of the game, as well as other metrics that provide deeper insight into
usage patterns so we can adapt the game to target users. Additionally, our current technology stack
cannot provide the scale we need, so we want to replace MySQL and move to an environment that
provides autoscaling, low latency load balancing, and frees us up from managing physical servers.
NEW QUESTION # 86
As part of implementing their disaster recovery plan, your company is trying to replicate their production MySQL database from their private data center to their GCP project using a Google Cloud VPN connection.
They are experiencing latency issues and a small amount of packet loss that is disrupting the replication. What should they do?
- A. Restore their database daily using Google Cloud SQL.
- B. Add additional VPN connections and load balance them.
- C. Configure a Google Cloud Dedicated Interconnect.
- D. Send the replicated transaction to Google Cloud Pub/Sub.
- E. Configure their replication to use UDP.
Answer: C
NEW QUESTION # 87
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers
- A. Use larger machine types for your Google Container Engine node pools.
- B. Remove dependencies from requirements.txt.
- C. Remove Python after running pip.
- D. Copy the source after the package dependencies (Python and pip) are installed.
- E. Use a slimmed-down base image like Alpine linux.
Answer: D,E
Explanation:
The speed of deployment can be changed by limiting the size of the uploaded app, limiting the complexity of the build necessary in the Dockerfile, if present, and by ensuring a fast and reliable internet connection.
Note: Alpine Linux is built around musl libc and busybox. This makes it smaller and more resource efficient than traditional GNU/Linux distributions. A container requires no more than 8 MB and a minimal installation to disk requires around 130 MB of storage. Not only do you get a fully-fledged Linux environment but a large selection of packages from the repository.
References: https://groups.google.com/forum/#!topic/google-appengine/hZMEkmmObDU
https://www.alpinelinux.org/about/
NEW QUESTION # 88
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. Enable Cloud Identity-Aware Proxy in all projects, and add the group of Administrators as a member.
- B. Use the Activity page in the GCP Console and Stackdriver Logging to provide the required insight.
- C. Use Stackdriver Trace to create a trace list analysis.
- D. Use Stackdriver Monitoring to create a dashboard on the project's activity.
Answer: C
Explanation:
Explanation
https://cloud.google.com/logging/docs/audit/
NEW QUESTION # 89
Google Cloud Platform resources are managed hierarchically using organization, folders, and projects. When Cloud Identity and Access Management (IAM) policies exist at these different levels, what is the effective policy at a particular node of the hierarchy?
- A. The effective policy is the policy set at the node and restricted by the policies of its ancestors
- B. The effective policy is determined only by the policy set at the node
- C. The effective policy is the intersection of the policy set at the node and policies inherited from its ancestors
- D. The effective policy is the union of the policy set at the node and policies inherited from its ancestors
Answer: A
Explanation:
Reference:
l
NEW QUESTION # 90
For this question, refer to the Mountkirk Games case study. Which managed storage option meets
Mountkirk's technical requirement for storing game activity in a time series database service?
- A. BigQuery
- B. Cloud Bigtable
- C. Cloud Spanner
- D. Cloud Datastore
Answer: B
NEW QUESTION # 91
You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute. With bursts of up to 8,500 clicks per second. It must have been stored for future analysis by your data science and user experience teams.
Which storage infrastructure should you choose?
- A. Google Cloud Bigtable
- B. Google Cloud Storage
- C. Google Cloud Datastore
- D. Google Cloud SQL
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
Low-latency read/write access
High-throughput analytics
Native time series support
Common workloads:
IoT, finance, adtech
Personalization, recommendations
Monitoring
Geospatial datasets
Graphs
Incorrect Answers:
C: Google Cloud Storage is a scalable, fully-managed, highly reliable, and cost-efficient object / blob store.
Is good for:
Images, pictures, and videos
Objects and blobs
Unstructured data
D: Google Cloud Datastore is a scalable, fully-managed NoSQL document database for your web and mobile applications.
Is good for:
Semi-structured application data
Hierarchical data
Durable key-value data
Common workloads:
User profiles
Product catalogs
Game state
References: https://cloud.google.com/storage-options/
NEW QUESTION # 92
One of the developers on your team deployed their application In Google Container Engine with the Dockerfile below. They report that their application deployments are taking too long.
You want to optimize this Dockerfile for faster deployment times without adversely affecting the app's functionality. Which two actions should you take? Choose 2 answers
- A. Remove Python after running pip.
- B. Use a slimmed-down base image like Alpine linux.
- C. Use larger machine types for your Google Container Engine node pools.
- D. Remove dependencies from requirements.txt.
- E. Copy the source after the package dependencies (Python and pip) are installed.
Answer: A,E
NEW QUESTION # 93
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. Shorten the expiration time of the cached objects.
- B. Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that bucket.
- C. Customize the cache keys to omit the protocol from the key.
- D. Make sure the HTTP(S) header "Cache-Region" points to the closest region of your users.
Answer: C
Explanation:
Reference https://cloud.google.com/cdn/docs/bestpractices#
using_custom_cache_keys_to_improve_cache_hit_ratio
NEW QUESTION # 94
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