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Google Professional-Cloud-Architect Exam is a certification program designed for IT professionals who have experience in designing and managing cloud solutions using Google Cloud Platform (GCP). Google Certified Professional - Cloud Architect (GCP) certification validates the knowledge and skills required to design, develop, and manage cloud solutions using GCP technologies. It is intended for individuals who are looking to advance their careers in cloud architecture and demonstrate their expertise in Google Cloud technologies.

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The second format is web-based Professional-Cloud-Architect practice exam and can be accessed through browsers and candidates can take it online. The students don’t need to install or use any plugins or software to attempt the web-based practice exam. The third and last form is the Google Professional-Cloud-Architect desktop practice test software that can be used from Windows computers. Candidates that have Windows laptops or computers can take the Professional-Cloud-Architect practice exam efficiently.

Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q80-Q85):

NEW QUESTION # 80
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. Cloud Spanner
B. BigQuery
C. Cloud Datastore
D. Cloud Bigtable

Answer: D

Explanation:
https://cloud.google.com/blog/products/databases/getting-started-with-time-series-trend-predictions-using-gcp
Topic 9, Mountkrik Games
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 # 81
You are designing a Data Warehouse on Google Cloud and want to store sensitive data in BigQuery. Your company requires you to generate the encryption keys outside of Google Cloud.
You need to implement a solution. What should you do?

A. Generate a new key in Cloud Key Management Service (Cloud KMS). Store all data in Cloud Storage using the customer-managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
B. Import a key in Cloud KMS. Store all data in Cloud Storage using the customer-managed key option and select the created key. Set up a Dataflow pipeline to decrypt the data and to store it in a new BigQuery dataset.
C. Import a key in Cloud KMS. Create a dataset in BigQuery using the customer-supplied key option and select the created key.
D. Generate a new key in Cloud KMS. Create a dataset in BigQuery using the customer-managed key option and select the created key.

Answer: C

Explanation:
For those that saying BigQuery does not support CSEK, read the below. You will need to import you CSEK and it will become CMEK. From there you can use it for BigQuery.
https://cloud.google.com/bigquery/docs/customer-managed-encryption

NEW QUESTION # 82
A news teed web service has the following code running on Google App Engine. During peak load, users report that they can see news articles they already viewed. What is the most likely cause of this problem?

A. The URL of the API needs to be modified to prevent caching.
B. The session variable is local to just a single instance.
C. The HTTP Expires header needs to be set to -1 to stop caching.
D. The session variable is being overwritten in Cloud Datastore.

Answer: D

Explanation:
https://stackoverflow.com/questions/3164280/google-app-engine-cache-list-in-session-variable?rq=1

NEW QUESTION # 83
You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified the appropriate web response is coming from each instance using the curl command. You want to ensure the backend is configured correctly. What should you do?

A. Assign a public IP to each instance and configure a firewall rule to allow the load balancer to reach the instance public IP.
B. Ensure that a firewall rule exists to allow source traffic on HTTP/HTTPS to reach the load balancer.
C. Ensure that a firewall rule exists to allow load balancer health checks to reach the instances in the instance group.
D. Create a tag on each instance with the name of the load balancer. Configure a firewall rule with the name of the load balancer as the source and the instance tag as the destination.

Answer: D

NEW QUESTION # 84
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 dependencies from requirements.txt.
B. Use larger machine types for your Google Container Engine node pools.
C. Use a slimmed-down base image like Alpine linux.
D. Copy the source after the package dependencies (Python and pip) are installed.
E. Remove Python after running pip.

Answer: C,D

Explanation:
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 # 85
......

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