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The Google Professional-Cloud-Architect exam is designed to test the candidate's ability to design and develop highly scalable, available, secure, and reliable cloud-based solutions. Professional-Cloud-Architect exam consists of multiple-choice questions, case studies, and hands-on scenarios that test the candidate's knowledge and practical skills. Professional-Cloud-Architect exam is conducted online and can be taken from anywhere in the world.
Google Certified Professional-Cloud-Architect (GCP) is a certification exam that is designed to test the knowledge and skills of professionals in the field of cloud architecture. Professional-Cloud-Architect exam is specifically designed to evaluate a candidate’s ability to design, develop, and manage secure, scalable, and highly available cloud-based solutions using Google Cloud Platform (GCP) technologies.
NEW QUESTION # 14
Your development team has installed a new Linux kernel module on the batch servers in Google Compute Engine (GCE) virtual machines (VMs) to speed up the nightly batch process. Two days after the installation,
50% of the batch servers failed the nightly batch run. You want to collect details on the failure to pass back to the development team.
Which three actions should you take? Choose 3 answers.
- A. Read the debug GCE Activity log using the API or Cloud Console
- B. Identify whether a live migration event of the failed server occurred, using in the activity log
- C. Adjust the Google Stackdriver timeline to match the failure time, and observe the batch server metrics
- D. Export a debug VM into an image, and run the image on a local server where kernel log messages will be displayed on the native screen
- E. Use Stackdriver Logging to search for the module log entries
- F. Use gcloud or Cloud Console to connect to the serial console and observe the logs
Answer: C,E,F
NEW QUESTION # 15
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.
The Dress4Win security team has disabled external SSH access into production virtual machines (VMs) on Google Cloud Platform (GCP). The operations team needs to remotely manage the VMs, build and push Docker containers, and manage Google Cloud Storage objects. What can they do?
- A. Develop a new access request process that grants temporary SSH access to cloud VMs when an operations engineer needs to perform a task.
- B. Grant the operations engineers access to use Google Cloud Shell.
- C. Configure a VPN connection to GCP to allow SSH access to the cloud VMs.
- D. Have the development team build an API service that allows the operations team to execute specific remote procedure calls to accomplish their tasks.
Answer: C
NEW QUESTION # 16
The development team has provided you with a Kubernetes Deployment file. You have no infrastructure yet and need to deploy the application. What should you do?
- A. Use gcloud to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- B. Use kubectl to create a Kubernetes cluster. Use kubectl to create the deployment.
- C. Use kubectl to create a Kubernetes cluster. Use Deployment Manager to create the deployment.
- D. Use gcloud to create a Kubernetes cluster. Use kubectl to create the deployment.
Answer: D
NEW QUESTION # 17
Case Study: 7 - Mountkirk Games
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.
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the database workloads for your company, Mountkirk Games.
Considering the business and technical requirements, what should you do?
- A. Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.
- B. Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.
- C. Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery for historical data queries.
- D. Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.
Answer: C
NEW QUESTION # 18
You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google- recommended tool for such applications?
- A. BigQuery, because it is designed for large-scale processing of tabular data
- B. Cloud Spanner, because it is globally distributed
- C. Cloud SQL, because it is a fully managed relational database
- D. Cloud Firestore, because it offers real-time synchronization across devices
Answer: A
Explanation:
Explanation/Reference: https://cloud.google.com/files/BigQueryTechnicalWP.pdf
NEW QUESTION # 19
You want to store critical business information in Cloud Storage buckets. The information is regularly changed but previous versions need to be referenced on a regular basis. You want to ensure that there is a record of all changes to any information in these buckets. You want to ensure that accidental edits or deletions can be easily roiled back. Which feature should you enable?
- A. Object change notification
- B. Object Versioning
- C. Object Lifecycle Management
- D. Bucket Lock
Answer: B
NEW QUESTION # 20
Your company captures all web traffic data in Google Analytics 260 and stores it in BigQuery.
Each country has its own dataset. Each dataset has multiple tables. You want analysts from each country to be able to see and query only the data for their respective countries.
How should you configure the access rights?
- A. Create a group per country. Add analysts to their respective country-groups. Create a single group `all_analysts', and add all country-groups as members. Grant the `all-analysis' group the IAM role of BigQuery jobUser. Share the appropriate tables with view access with each respective analyst country- group.
- B. Create a group per country. Add analysts to their respective country-groups. Create a single group `all_analysts', and add all country-groups as members. Grant the `all-analysis' group the IAM role of BigQuery dataViewer. Share the appropriate table with view access with each respective analyst country-group.
- C. Create a group per country. Add analysts to their respective country-groups. Create a single group `all_analysts', and add all country-groups as members. Grant the `all-analysis' group the IAM role of BigQuery jobUser. Share the appropriate dataset with view access with each respective analyst country-group.
- D. Create a group per country. Add analysts to their respective country-groups. Create a single group `all_analysts', and add all country-groups as members. Grant the `all-analysis' group the IAM role of BigQuery dataViewer. Share the appropriate dataset with view access with each respective analyst country-group.
Answer: C
NEW QUESTION # 21
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. Restart the affected instances on a staggered schedule.
- B. Increase the maximum number of instances in the autoscaling group.
- C. SSH to each instance and restart the application process.
- D. Change the autoscaling metric to agent.googleapis.com/memory/percent_used.
Answer: B
NEW QUESTION # 22
Your company just finished a rapid lift and shift to Google Compute Engine for your compute needs. You have another 9 months to design and deploy a more cloud-native solution. Specifically, you want a system that is no-ops and auto-scaling. Which two compute products should you choose? Choose 2 answers
- A. Compute Engine with managed instance groups
- B. Compute Engine with containers
- C. Compute Engine with custom instance types
- D. Google Kubernetes Engine with containers
- E. Google App Engine Standard Environment
Answer: D,E
Explanation:
B: With Container Engine, Google will automatically deploy your cluster for you, update, patch, secure the nodes.
Kubernetes Engine's cluster autoscaler automatically resizes clusters based on the demands of the workloads you want to run.
C: Solutions like Datastore, BigQuery, AppEngine, etc are truly NoOps.
App Engine by default scales the number of instances running up and down to match the load, thus providing consistent performance for your app at all times while minimizing idle instances and thus reducing cost.
Note: At a high level, NoOps means that there is no infrastructure to build out and manage during usage of the platform. Typically, the compromise you make with NoOps is that you lose control of the underlying infrastructure.
References:
https://www.quora.com/How-well-does-Google-Container-Engine-support-Google-Cloud-Platform%E2%80%9
NEW QUESTION # 23
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 for the next 24 hours.Authenticate users via Cloud Identity.
- 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. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
Answer: C
Explanation:
https://cloud.google.com/blog/products/storage-data-transfer/uploading-images-directly-to-cloud-storage-by-us
NEW QUESTION # 24
For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical architecture for the compute workloads for your company, Mountkirk Games. Considering the Mountkirk Games business and technical requirements, what should you do?
- A. Create network load balancers. Use preemptible Compute Engine instances.
- B. Create a global load balancer with managed instance groups and autoscaling policies. Use non-preemptible Compute Engine instances.
- C. Create a global load balancer with managed instance groups and autoscaling policies. Use preemptible Compute Engine instances.
- D. Create network load balancers. Use non-preemptible Compute Engine instances.
Answer: B
NEW QUESTION # 25
For this question, refer to the TerramEarth case study.
The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?
- A. Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.
- B. Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.
- C. Use Google Container Engine with a Django Python container. Focus on an API for the public.
- D. Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.
- E. Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.
Answer: D
Explanation:
Explanation
https://cloud.google.com/endpoints/docs/openapi/about-cloud-endpoints?hl=en_US&_ga=2.21787131.-1712523
https://cloud.google.com/endpoints/docs/openapi/architecture-overview
https://cloud.google.com/storage/docs/gsutil/commands/test
Develop, deploy, protect and monitor your APIs with Google Cloud Endpoints. Using an Open API Specification or one of our API frameworks, Cloud Endpoints gives you the tools you need for every phase of API development.
From scenario:
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.
Reference: https://cloud.google.com/certification/guides/cloud-architect/casestudy-terramearth
Topic 2, Mountkirk Games Case Study
Company Overview
Mountkirk Games makes online, session-based. multiplayer games for the most popular mobile platforms.
Company Background
Mountkirk Games builds all of their games with some server-side integration and has historically used cloud providers to lease physical servers. A few of their games were more popular than expected, and they had problems scaling their application servers, MySQL databases, and analytics tools.
Mountkirk's 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.
Technical Requirements
Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity.
2. Connect to a managed NoSQL database service.
3. Run customized Linx distro.
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
CEO Statement
Our last successful game did not scale well with our previous cloud provider, resuming 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 gams to target users.
CTO Statement
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.
CFO Statement
We are not capturing enough user demographic data usage metrics, and other KPIs. As a result, we do not engage the right users. We are not confident that our marketing is targeting the right users, and we are not selling enough premium Blast-Ups inside the games, which dramatically impacts our revenue.
NEW QUESTION # 26
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a through testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?
- A. Use the existing infrastructure to test the GCP-based backend at scale
- B. Create a scalable environment in GCP for simulating production load
- C. Build stress tests into each component of your application using resources internal to GCP to simulate load
- D. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low
Answer: B
Explanation:
From scenario: Requirements for Game Backend Platform
1. Dynamically scale up or down based on game activity
2. Connect to a managed NoSQL database service
3. Run customize Linux distro
NEW QUESTION # 27
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. Google Bigtabte with US or EU as location to store the data, and gcloud to access the data.
- B. Google Cloud Storage Nearline to store the data, and gsutil to access the data.
- C. 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. - D. Google Cloud Storage Coldline to store the data, and gsutil to access the data.
Answer: D
Explanation:
References: https://cloud.google.com/storage/docs/storage-classes
NEW QUESTION # 28
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. Protect the bucket with a password 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 using a signed URL 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: A
NEW QUESTION # 29
......
Section #4. Auditing and optimizing business as well as technical processes
The key focus areas of this domain are performing the SDLC management, continuous integration, change management, and best practices for troubleshooting or bug-finding. Verifying and testing of software solutions and infrastructure, disaster recovery, business continuity, and service catalogue are also discussed in here.
Another sub-section is all about the business process’ defining & analysing, stakeholder management, team management, and decision-making workflow.
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