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The Google Professional Cloud Architect test is timed. The exact number of questions has not been revealed by the vendor. But, it is known that candidates will be given 2 hours to complete the exam, and the questions will be based on multiple-choice and multiple select types. Available languages are English and Japanese, and one should pay $200 as a registration fee. Note that there can be an additional tax.
When it comes to the exam delivery formats, there are two choices for an aspirant. They can either sit for it in a testing center near them or can avail of the online proctoring facility. In both methods, the content and pattern of the test will be the same.
For this exam, a beta version is offered as well. Anyone who wants to save 40% on the total fee or willing to recertify can take it. The cost in this case is $120, the length increases to 3 hours, and some questions may be provided in the form of case studies. Also, pay attention to the fact that the results will be known after 6-8 weeks only.
Google Professional-Cloud-Architect Exam is a certification that verifies the expertise of an individual in the field of cloud computing with a focus on Google Cloud Platform (GCP). Professional-Cloud-Architect exam is designed for professionals who are responsible for designing, developing, and managing cloud solutions using GCP. Google Certified Professional - Cloud Architect (GCP) certification validates the skills required to handle complex enterprise-level solutions that are secure, scalable, and reliable.
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To become a Google Certified Professional - Cloud Architect, candidates must pass the Google Professional-Cloud-Architect exam, which consists of multiple-choice and scenario-based questions. Professional-Cloud-Architect exam covers a wide range of topics, including cloud architecture, storage and data management, compute and networking, security, and business continuity. Passing Professional-Cloud-Architect Exam demonstrates that the candidate has the necessary knowledge and skills to design and implement solutions on the Google Cloud Platform, making them a valuable asset for any organization looking to leverage cloud technology to drive innovation and growth.
NEW QUESTION # 237
You need to deploy a stateful workload on Google Cloud. The workload can scale horizontally, but each instance needs to read and write to the same POSIX filesystem. At high load, the stateful workload needs to support up to 100 MB/s of writes. What should you do?
Answer: D
Explanation:
Filestore is fully managed network attached storage and it scales to 100s of TBs for high- performance workloads. Gcsfuse is a user-space file system for interacting with Google Cloud Storage. As with the other access methods, Cloud Storage does not support concurrency and locking. For example, if multiple Cloud Storage FUSE clients are writing to the same file, the last flush wins.
https://cloud.google.com/storage/docs/gcs-fuse
NEW QUESTION # 238
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants to set up a real-time analytics platform for their new game. The new platform must meet their technical requirements. Which combination of Google technologies will meet all of their requirements?
Answer: A
Explanation:
A real time requires Stream / Messaging so Pub/Sub, Analytics by Big Query.
Ingest millions of streaming events per second from anywhere in the world with Cloud Pub/Sub, powered by Google's unique, high-speed private network. Process the streams with Cloud Dataflow to ensure reliable, exactly-once, low-latency data transformation. Stream the transformed data into BigQuery, the cloud-native data warehousing service, for immediate analysis via SQL or popular visualization tools.
From scenario: They plan to deploy the game's backend on Google Compute Engine so they can capture streaming metrics, run intensive analytics.
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 SQL queries to access at least 10 TB of historical data
* Process files that are regularly uploaded by users' mobile devices
* Use only fully managed services
References:
https://cloud.google.com/solutions/big-data/stream-analytics/
NEW QUESTION # 239
For this question, refer to the JencoMart case study.
JencoMart has decided to migrate user profile storage to Google Cloud Datastore and the application servers to Google Compute Engine (GCE). During the migration, the existing infrastructure will need access to Datastore to upload the dat a. What service account key-management strategy should you recommend?
Answer: A
Explanation:
https://cloud.google.com/iam/docs/understanding-service-accounts
Migrating data to Google Cloud Platform
Let's say that you have some data processing that happens on another cloud provider and you want to transfer the processed data to Google Cloud Platform. You can use a service account from the virtual machines on the external cloud to push the data to Google Cloud Platform. To do this, you must create and download a service account key when you create the service account and then use that key from the external process to call the Cloud Platform APIs.
Reference:
https://cloud.google.com/iam/docs/understanding-service-accounts#migrating_data_to_google_cloud_platform
NEW QUESTION # 240
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 web application deployed in the same
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
Answer: A,D,E
Explanation:
Explanation
https://www.flexera.com/blog/cloud/2013/12/google-compute-engine-live-migration-passes-the-test/
"With live migration, the virtual machines are moved without any downtime or noticeable service degradation"
NEW QUESTION # 241
Your company is running its application workloads on Compute Engine. The applications have been deployed in production, acceptance, and development environments. The production environment is business-critical and is used 24/7, while the acceptance and development environments are only critical during office hours.
Your CFO has asked you to optimize these environments to achieve cost savings during idle times . What should you do?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Exact Extract: The most effective way to achieve significant cost savings for non-production environments that are only needed during business hours is to stop the instances when they are idle. When an instance is stopped, you are only charged for the persistent disks and not for the CPU/RAM.
Instance Schedules are the native, managed Google Cloud feature designed specifically for this purpose:
automating the starting and stopping of Compute Engine instances on a recurring schedule.
* Option D (Use Instance Schedules to stop the development and acceptance environments after office hours, and start them just before office hours) directly addresses the need for cost optimization during idle times with the recommended native solution.
* Option A (Spot VMs) are cheap but can be preempted at any time, which isn ' t suitable for critical during office hours environments.
* Option B (Autoscaling) scales down when demand is low, but typically won ' t scale completely to zero instances, and will still incur minimum running costs.
* Option C (Custom Shell Script) is a manual, non-native solution that requires maintenance and is more complex than the built-in Instance Schedules.
Exact Extract Principle:
From the Google Cloud documentation on Compute Engine Cost Optimization :
" Instance schedules allow you to schedule when Compute Engine virtual machine instances start and stop.
Use instance schedules to automatically start and stop your instances at predefined times. This is a highly recommended practice for cost optimization of non-production environments (development, testing, or staging) that are not needed 24/7, as you are not billed for the instance ' s machine type when it is stopped. " Reference: Google Cloud Compute Engine Instance Schedules Documentation and Compute Engine Pricing
/Cost Optimization Guide.
NEW QUESTION # 242
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