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Introduction to Google Professional Cloud Architect Exam
Google Professional Cloud Architect Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud Architect in the IT industry.
After passing this exam, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud Architect to their clients and employers.
How to Prepare For Google Professional Cloud Architect Exam
Preparation Guide for Google Professional Cloud Architect Exam
Introduction
Google has designed a track for IT professionals to endorse as a cloud architect on the GCP platform. This accreditation program gives Google cloud professionals a way to endorse their skills. The evaluation relies on a meticulous exam using industry standard methodology to conclude whether or not a aspirant meets Google's proficiency standards.
According to Google, a Google Certified Professional Cloud Architect facilitate organizations to influence Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
Certification is evidence of your skills, expertise in those areas in which you like to work. If candidate wants to work on Google Professional Cloud Architect and prove his knowledge, Certification offered by Google. This Google Professional Cloud Architect Certification helps a candidate to validates his skills in Google Professional Cloud Architect Technology.
In this guide, we will cover the Google Professional Cloud Architect Exam, Google Professional Cloud Architect Certified Professionals salary and all aspects of the Google Professional Cloud Architect Certification.
NEW QUESTION 73
A recent audit revealed that a new network was created in your GCP project. In this network, a GCE instance has an SSH port open to the world. You want to discover this network's origin.
What should you do?
- A. In the Logging section of the console, specify GCE Network as the logging section. Search for the Create Insert entry
- B. Navigate to the Activity page in the Home section. Set category to Data Access and search for Create VM entry
- C. Connect to the GCE instance using project SSH keys. Identify previous logins in system logs, and match these with the project owners list
- D. Search for Create VM entry in the Stackdriver alerting console
Answer: A
Explanation:
Explanation/Reference:
Explanation:
Incorrect Answers:
A: To use the Stackdriver alerting console we must first set up alerting policies.
B: Data access logs only contain read-only operations.
Audit logs help you determine who did what, where, and when.
Cloud Audit Logging returns two types of logs:
Admin activity logs
Data access logs: Contains log entries for operations that perform read-only operations do not modify
any data, such as get, list, and aggregated list methods.
NEW QUESTION 74
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants you to design a way to test the analytics platform's resilience to changes in mobile network latency. What should you do?
- A. Add the ability to introduce a random amount of delay before beginning to process analytics files uploaded from mobile devices.
- B. Deploy failure injection software to the game analytics platform that can inject additional latency to mobile client analytics traffic.
- C. Build a test client that can be run from a mobile phone emulator on a Compute Engine virtual machine, and run multiple copies in Google Cloud Platform regions all over the world to generate realistic traffic.
- D. Create an opt-in beta of the game that runs on players' mobile devices and collects response times from analytics endpoints running in Google Cloud Platform regions all over the world.
Answer: D
Explanation:
Topic 8, Mountkrik Games Case 3
Company overview
Mountkirk Games makes online, session-based, multiplayer games for mobile platforms. They have recently started expanding to other platforms after successfully migrating their on-premises environments to Google Cloud.
Their most recent endeavor is to create a retro-style first-person shooter (FPS) game that allows hundreds of simultaneous players to join a geo-specific digital arena from multiple platforms and locations. A real-time digital banner will display a global leaderboard of all the top players across every active arena.
Solution concept
Mountkirk Games is building a new multiplayer game that they expect to be very popular. They plan to deploy the game's backend on Google Kubernetes Engine so they can scale rapidly and use Google's global load balancer to route players to the closest regional game arenas. In order to keep the global leader board in sync, they plan to use a multi-region Spanner cluster.
Existing technical environment
The existing environment was recently migrated to Google Cloud, and five games came across using lift-and-shift virtual machine migrations, with a few minor exceptions. Each new game exists in an isolated Google Cloud project nested below a folder that maintains most of the permissions and network policies. Legacy games with low traffic have been consolidated into a single project. There are also separate environments for development and testing.
Business requirements
Support multiple gaming platforms.
Support multiple regions.
Support rapid iteration of game features.
Minimize latency.
Optimize for dynamic scaling.
Use managed services and pooled resources.
Minimize costs.
Technical requirements
Dynamically scale based on game activity.
Publish scoring data on a near real-time global leaderboard.
Store game activity logs in structured files for future analysis.
Use GPU processing to render graphics server-side for multi-platform support.
Support eventual migration of legacy games to this new platform.
Executive statement
Our last game was the first time we used Google Cloud, and it was a tremendous success. We were able to analyze player behavior and game telemetry in ways that we never could before. This success allowed us to bet on a full migration to the cloud and to start building all-new games using cloud-native design principles. Our new game is our most ambitious to date and will open up doors for us to support more gaming platforms beyond mobile. Latency is our top priority, although cost management is the next most important challenge. As with our first cloud-based game, we have grown to expect the cloud to enable advanced analytics capabilities so we can rapidly iterate on our deployments of bug fixes and new functionality.
NEW QUESTION 75
You have an application deployed on Google Kubernetes Engine using a Deployment named echo- deployment. The deployment is exposed using a Service called echo-service. You need to perform an update to the application with minimal downtime to the application. What should you do?
- A. Update the deployment yaml file with the new container image. Use kubectl delete deployment/ echo-deployment and kubectl create -f <yaml-file>
- B. Update the service yaml file which the new container image. Use kubectl delete service/echo- service and kubectl create -f <yaml-file>
- C. Use kubectl set image deployment/echo-deployment <new-image>
- D. Use the rolling update functionality of the Instance Group behind the Kubernetes cluster
Answer: C
NEW QUESTION 76
You need to design a solution for global load balancing based on the URL path being requested. You need to ensure operations reliability and end-to-end in-transit encryption based on Google best practices.
What should you do?
- A. Create a global forwarding rule. Configure SSL proxy balancing.
- B. Create appropriate instance groups and instances. Configure SSL proxy load balancing.
- C. Create an HTTPS load balancer with URL maps.
- D. Create a cross-region load balancer with URL Maps.
Answer: C
Explanation:
Explanation/Reference: https://cloud.google.com/load-balancing/docs/https/url-map
NEW QUESTION 77
Your company has announced that they will be outsourcing operations functions. You want to allow developers to easily stage new versions of a cloud-based application in the production environment and allow the outsourced operations team to autonomously promote staged versions to production. You want to minimize the operational overhead of the solution. Which Google Cloud product should you migrate to?
- A. Google Kubernetes Engine
- B. GKE On-Prem
- C. App Engine
- D. Compute Engine
Answer: A
Explanation:
Topic 2, 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 78
You want your Google Kubernetes Engine cluster to automatically add or remove nodes based on CPUload. What should you do?
- A. Configure a HorizontalPodAutoscaler with a target CPU usage. Enable the Cluster Autoscaler from the GCP Console.
- B. Create a deployment and set the maxUnavailable and maxSurge properties. Enable the Cluster Autoscaler using the gcloud command.
- C. Create a deployment and set the maxUnavailable and maxSurge properties. Enable autoscaling on the cluster managed instance group from the GCP Console.
- D. Configure a HorizontalPodAutoscaler with a target CPU usage. Enable autoscaling on the managed instance group for the cluster using the gcloud command.
Answer: D
NEW QUESTION 79
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 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. - 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 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: D
NEW QUESTION 80
For this question, refer to the Mountkirk Games case study. You are in charge of the new Game Backend
Platform architecture. The game communicates with the backend over a REST API.
You want to follow Google-recommended practices. How should you design the backend?
- A. Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L7 load balancer. - B. Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L7 load balancer. - C. Create an instance template for the backend. For every region, deploy it on a multi-zone managed
instance group. Use an L4 load balancer. - D. Create an instance template for the backend. For every region, deploy it on a single-zone managed
instance group. Use an L4 load balancer.
Answer: C
Explanation:
Explanation/Reference:
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.
Company background
TerramEarth was formed in 1946, when several small, family owned companies combined to retool after
World War II. The company cares about their employees and customers and considers them to be
extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their
customers' needs change. For the past 20 years, trends in the industry have been largely toward
increasing productivity by using larger vehicles with a human operator.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is
stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is
downloaded via a maintenance port. This same port can be used to adjust operational parameters,
allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data
directly. At a rate of 120 fields of data per second with 22 hours of operation per day, Terram Earth collects
a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux-based systems that reside in a data center.
These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, and place
the data in their data warehouse. Because this process takes time, aggregated reports are based on data
that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned
downtime of their vehicles by 60%. However, because the data is stale, some customers are without their
vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week, without increasing the cost of carrying
surplus inventory
Support the dealer network with more data on how their customers use their equipment 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.
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of
our customers. Technological change is occurring rapidly, and TerramEarth has taken advantage of
connected devices technology to provide our customers with better services, such as our intelligent
farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using
past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our
agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better
vehicles for 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. Unfortunately, our CEO doesn't take technology obsolescence seriously
and he considers the many new companies in our industry to be niche players. My goals are to build our
skills while addressing immediate market needs through incremental innovations.
NEW QUESTION 81
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 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. - 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 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. - D. 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.
Answer: C
NEW QUESTION 82
You have an application deployed on Kubernetes Engine using a Deployment named echo-deployment. The deployment is exposed using a Service called echo-service. You need to perform an update to the application with minimal downtime to the application. What should you do?
- A. Use kubectl set image deployment/echo-deployment <new-image>
- B. Update the service yaml file which the new container image. Use kubectl delete service/echoservice and kubectl create -f <yaml-file>
- C. Use the rolling update functionality of the Instance Group behind the Kubernetes cluster
- D. Update the deployment yaml file with the new container image. Use kubectl delete deployment/ echo-deployment and kubectl create -f <yaml-file>
Answer: C
Explanation:
Reference: https://cloud.google.com/kubernetes-engine/docs/how-to/updating-apps
https://cloud.google.com/kubernetes-engine/docs/tutorials/hello-app
NEW QUESTION 83
Your operations team has asked you to help diagnose a performance issue in a production application that runs on Compute Engine. The application is dropping requests that reach it when under heavy load. The process list for affected instances shows a single application process that is consuming all available CPU, and autoscaling has reached the upper limit of instances. There is no abnormal load on any other related systems, including the database. You want to allow production traffic to be served again as quickly as possible. Which action should you recommend?
- A. Increase the maximum number of instances in the autoscaling group.
- B. Restart the affected instances on a staggered schedule.
- C. SSH to each instance and restart the application process.
- D. Change the autoscaling metric to agent.googleapis.com/memory/percent_used.
Answer: A
NEW QUESTION 84
Your company is developing a new application that will allow globally distributed users to upload pictures and share them with other selected users. The application will support millions of concurrent users. You want to allow developers to focus on just building code without having to create and maintain the underlying infrastructure. Which service should you use to deploy the application?
- A. App Engine
- B. Cloud Endpoints
- C. Compute Engine
- D. Google Kubernetes Engine
Answer: A
Explanation:
Reference:
https://cloud.google.com/appengine/docs/standard/go/how-requests-are-handled
NEW QUESTION 85
For this question, refer to the Dress4Win case study.
As part of Dress4Win's plans to migrate to the cloud, they want to be able to set up a managed logging and monitoring system so they can handle spikes in their traffic load.
They want to ensure that:
* The infrastructure can be notified when it needs to scale up and down to handle the ebb and flow of usage throughout the day
* Their administrators are notified automatically when their application reports errors.
* They can filter their aggregated logs down in order to debug one piece of the application across many hosts Which Google StackDriver features should they use?
- A. Logging, Alerts, Insights, Debug
- B. Monitoring, Logging, Alerts, Error Reporting
- C. Monitoring, Trace, Debug, Logging
- D. Monitoring, Logging, Debug, Error Report
Answer: C
NEW QUESTION 86
For this question, refer to the Dress4Win case study.
You want to ensure Dress4Win's sales and tax records remain available for infrequent viewing by auditors for at least 10 years. Cost optimization is your top priority. Which cloud services should you choose?
- A. BigQuery to store the data, and a web server cluster in a managed instance group to access the data. Google Cloud SQL mirrored across two distinct regions to store the data, and a Redis cluster in a managed instance group to access the data.
- B. Google Bigtabte with US or EU as location to store the data, and gcloud to access the data.
- C. Google Cloud Storage Coldline to store the data, and gsutil to access the data.
- D. Google Cloud Storage Nearline to store the data, and gsutil to access the data.
Answer: C
Explanation:
Explanation: References: https://cloud.google.com/storage/docs/storage-classes
NEW QUESTION 87
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?
- A. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.
- B. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.
- C. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
- D. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
Answer: A
Explanation:
https://cloud.google.com/solutions/building-a-serverless-ml-model
NEW QUESTION 88
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours. Not all users have a Google Account. How should you have users upload images?
- A. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
- B. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after 24 hours.
- C. Create an App Engine web application where users can upload images for the next 24 hours. Authenticate users via Cloud Identity.
- D. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
Answer: D
Explanation:
Explanation/Reference:
NEW QUESTION 89
You have created several pre-emptible Linux virtual machine instances using Google Compute Engine.
You want to properly shut down your application before the virtual machines are preempted.
What should you do?
- A. Create a shutdown script and use it as the value for a new metadata entry with the key shutdown-
scriptin the Cloud Platform Console when you create the new virtual machine instance - B. Create a shutdown script named k99.shutdown in the /etc/rc.6.d/directory
- C. Create a shutdown script registered as a xinetdservice in Linux and configure a Stackdriver endpoint
check to call the service - D. Create a shutdown script, registered as a xinetd service in Linux, and use the gcloud compute
instances add-metadatacommand to specify the service URL as the value for a new metadata
entry with the key shutdown-script-url
Answer: A
Explanation:
Explanation/Reference:
Explanation:
A startup script, or a shutdown script, is specified through the metadata server, using startup script
metadata keys.
Reference: https://cloud.google.com/compute/docs/startupscript
NEW QUESTION 90
......
Professionals willing to become a part of Google and excel at every career front can make this happen if they earn the Google Professional Cloud Architect certification. Passing its associated exam is the easiest way to leverage their abilities in Google Cloud Technologies and cement feet in the industry.
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