Free Google Professional-Cloud-Architect Test Practice Test Questions Exam Dumps [Q83-Q106]

Q83. Your company runs several databases on a single MySQL instance. They need to take backups of a specific database at regular intervals. The backup activity needs to complete as quickly as possible and cannot be allowed to impact disk performance. How should you configure the storage?

Q84. 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?

Q85. Case Study: 1 – 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.
For this question, refer to the Mountkirk Games case study. Mountkirk Games wants to set up a continuous delivery pipeline. Their architecture includes many small services that they want to be able to update and roll back quickly. Mountkirk Games has the following requirements:
– Services are deployed redundantly across multiple regions in the US
and Europe.
– Only frontend services are exposed on the public internet.
– They can provide a single frontend IP for their fleet of services.
– Deployment artifacts are immutable.
Which set of products should they use?

Q86. For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an automated daily basis while managing cost.
What should you do?

Q87. Your company has a Google Cloud project that uses BigQuery for data warehousing They have a VPN tunnel between the on-premises environment and Google Cloud that is configured with Cloud VPN. The security team wants to avoid data exfiltration by malicious insiders, compromised code, and accidental oversharing. What should they do?

Q88. 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 would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

Q89. 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?

Q90. 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?

Q91. You are building a continuous deployment pipeline for a project stored in a Git source repository and want to ensure that code changes can be verified deploying to production. What should you do?

Q92. You want to establish a Compute Engine application in a single VPC across two regions. The application must communicate over VPN to an on-premises network. How should you deploy the VPN?

Q93. Case Study: 2 – TerramEarth Case Study
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 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.
TerramEarth 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 IP 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 tower 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.
For this question refer to the TerramEarth case study.
Which of TerramEarth’s legacy enterprise processes will experience significant change as a result of increased Google Cloud Platform adoption.

Q94. Your customer wants to capture multiple GBs of aggregate real-time key performance indicators (KPIs) from their game servers running on Google Cloud Platform and monitor the KPIs with low latency. How should they capture the KPIs?

Q95. 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. 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?

Q96. A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?

Q97. For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough 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?

Q98. Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?

Q99. Your company is migrating its on-premises data center into the cloud. As part of the migration, you want to integrate Kubernetes Engine for workload orchestration. Parts of your architecture must also be PCI DSScompliant.
Which of the following is most accurate?

Q100. 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?

Q101. You want to create a private connection between your instances on Compute Engine and your on- premises data center. You require a connection of at least 20 Gbps. You want to follow Google- recommended practices. How should you set up the connection?

Q102. You are implementing a single Cloud SQL MySQL second-generation database that contains business-critical transaction dat a. You want to ensure that the minimum amount of data is lost in case of catastrophic failure. Which two features should you implement? (Choose two.)

Q103. You want to create a private connection between your instances on Compute Engine and your on-premises data center. You require a connection of at least 20 Gbps. You want to follow Google-recommended practices.
How should you set up the connection?

Q104. 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?

Q105. For this question, refer to the Dress4Win case study. You want to ensure that your on-premises architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?

Q106. 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?