PASS GUARANTEED QUIZ PROFESSIONAL-CLOUD-ARCHITECT - RELIABLE GOOGLE CERTIFIED PROFESSIONAL - CLOUD ARCHITECT (GCP) EXAM STUDY SOLUTIONS

Pass Guaranteed Quiz Professional-Cloud-Architect - Reliable Google Certified Professional - Cloud Architect (GCP) Exam Study Solutions

Pass Guaranteed Quiz Professional-Cloud-Architect - Reliable Google Certified Professional - Cloud Architect (GCP) Exam Study Solutions

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Google Professional-Cloud-Architect is a certification exam that tests the knowledge and skills of an individual in designing and managing solutions on the Google Cloud Platform. Professional-Cloud-Architect exam is designed for professionals who want to demonstrate their expertise in cloud architecture and showcase their ability to design, develop, and manage secure, scalable, and reliable cloud-based solutions.

Google Professional-Cloud-Architect Certification Exam is a rigorous and comprehensive test of an individual's knowledge and skills in cloud architecture and GCP. Becoming certified can bring numerous benefits, including enhanced career prospects, organizational recognition, and access to a community of experts.

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q92-Q97):

NEW QUESTION # 92
You are developing your microservices application on Google Kubernetes Engine. During testing, you want to validate the behavior of your application in case a specific microservice should suddenly crash. What should you do?

  • A. Destroy one of the nodes of the Kubernetes cluster to observe the behavior.
  • B. Configure Istio's traffic management features to steer the traffic away from a crashing microservice.
  • C. Use Istio's fault injection on the particular microservice whose faulty behavior you want to simulate.
  • D. Add a taint to one of the nodes of the Kubernetes cluster. For the specific microservice, configure a pod anti-affinity label that has the name of the tainted node as a value.

Answer: C

Explanation:
Microservice runs on all nodes. The Micro service runs on Pod, Pod runs on Nodes. Nodes is nothing but Virtual machines. Once deployed the application microservices will get deployed across all Nodes.
Destroying one node may not mimic the behaviour of microservice crashing as it may be running in other nodes.
link: https://istio.io/latest/docs/tasks/traffic-management/fault-injection/


NEW QUESTION # 93
Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?

  • A. Verify that the database is online
  • B. Verify that the new feature code did not introduce any performance bugs
  • C. Verify that the load-testing team is not running their tool against production
  • D. Verify that the project quota hasn't been exceeded

Answer: D

Explanation:
Explanation: 503 is service unavailable error. If the database was online everyone would get the 503 error.


NEW QUESTION # 94
You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also want to reliably deploy new versions of the application. Which set of steps should you take?

  • A. Perform the following:
    1. Create a GKE cluster with n1-standard-4 type machines.
    2. Build a Docker image from the master branch with all of the dependencies, and tag it with 'latest'.
    3. Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to 'Always'.
    Restart the pods to automatically deploy new production releases.
  • B. Perform the following:
    1. Create a Google Kubernetes Engine (GKE) cluster with n1-standard-1 type machines.
    2. Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
    3. Create a Kubernetes Deployment with the imagePullPolicy set to 'IfNotPresent' in the staging namespace, and then promote it to the production namespace after testing.
  • C. Perform the following:
    1. Create a managed instance group with n1-standard-1 type machines.
    2. Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
    3. Rebuild the Compute Engine image, and update the instance template to deploy new production releases.
  • D. Perform the following:
    1. Create a managed instance group with f1-micro type machines.
    2. Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
    3. Restart the instances to automatically deploy new production releases.

Answer: C


NEW QUESTION # 95
Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual
machines. The full test suite takes several hours to complete, running on a limited number of on-premises
servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce
the amount of time it takes to fully test a change to the system, while changing the tests as little as
possible.
Which cloud infrastructure should you recommend?

  • A. Google App Engine with Google StackDriver for logging
  • B. Google Compute Engine unmanaged instance groups and Network Load Balancer
  • C. Google Compute Engine managed instance groups with auto-scaling
  • D. Google Cloud Dataproc to run Apache Hadoop jobs to process each test

Answer: C

Explanation:
Explanation/Reference:
Explanation:
Google Compute Engine enables users to launch virtual machines (VMs) on demand. VMs can be
launched from the standard images or custom images created by users.
Managed instance groups offer autoscaling capabilities that allow you to automatically add or remove
instances from a managed instance group based on increases or decreases in load. Autoscaling helps
your applications gracefully handle increases in traffic and reduces cost when the need for resources is
lower.
Incorrect Answers:
B: There is no mention of incoming IP data traffic for the custom C++ applications.
C: Apache Hadoop is not fit for testing C++ applications. Apache Hadoop is an open-source software
framework used for distributed storage and processing of datasets of big data using the MapReduce
programming model.
D: Google App Engine is intended to be used for web applications.
Google App Engine (often referred to as GAE or simply App Engine) is a web framework and cloud
computing platform for developing and hosting web applications in Google-managed data centers.
References: https://cloud.google.com/compute/docs/autoscaler/


NEW QUESTION # 96
For this question, refer to the TerramEarth case study.
TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the development team to focus their failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?

  • A.
  • B.
  • C.
  • D.

Answer: D

Explanation:
Explanation
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-conne cted-car-data
https://cloud.google.com/solutions/iot/
The push endpoint can be a load balancer.
A container cluster can be used.
Cloud Pub/Sub for Stream Analytics

References: https://cloud.google.com/pubsub/
https://cloud.google.com/solutions/iot/
https://cloud.google.com/solutions/designing-connected-vehicle-platform
https://cloud.google.com/solutions/designing-connected-vehicle-platform#data_ingestion
http://www.eweek.com/big-data-and-analytics/google-touts-value-of-cloud-iot-core-for-analyzing-connected-car
https://cloud.google.com/solutions/iot/


NEW QUESTION # 97
......

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