Professional-Cloud-Architect Pass Guide - Exam Professional-Cloud-Architect Experience
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The Google Professional Cloud Architect certification validates the individuals’ knowledge and skills required for a successful career in the domain of Cloud architecture. Specifically, this certificate demonstrates that the candidates have the expertise in designing and planning Cloud solution architecture, managing and provisioning Cloud solution infrastructure, designing for security and compliance, and more. To earn this sought-after certification, the applicants need to take a single qualifying test.
Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q32-Q37):
NEW QUESTION # 32
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.
- A. Opex/capex allocation, LAN changes, capacity planning
- B. Capacity planning, utilization measurement, data center expansion
- C. Capacity planning, TCO calculations, opex/capex allocation
- D. Data Center expansion, TCO calculations, utilization measurement
Answer: C
NEW QUESTION # 33
Your company has multiple on-premises systems that serve as sources for reporting. The data has not been maintained well and has become degraded over time. You want to use Google- recommended practices to detect anomalies in your company data. What should you do?
- A. Upload your files into Cloud Storage. Use Cloud Datalab to explore and clean your data.
- B. Upload your files into Cloud Storage. Use Cloud Dataprep to explore and clean your data.
- C. Connect Cloud Datalab to your on-premises systems. Use Cloud Datalab to explore and clean your data.
- D. Connect Cloud Dataprep to your on-premises systems. Use Cloud Dataprep to explore and clean your data.
Answer: B
NEW QUESTION # 34
Your company sends all Google Cloud logs to Cloud Logging. Your security team wants to monitor the logs.
You want to ensure that the security team can react quickly if an anomaly such as an unwanted firewall change or server breach is detected. You want to follow Google-recommended practices. What should you do?
- A. Export logs to a Pub/Sub topic, and trigger Cloud Function with the relevant log events.
- B. Export logs to BigQuery, and trigger a query in BigQuery to process the log data for the relevant events.
- C. Export logs to a Cloud Storage bucket, and trigger Cloud Run with the relevant log events.
- D. Schedule a cron job with Cloud Scheduler. The scheduled job queries the logs every minute for the relevant events.
Answer: A
Explanation:
Explanation
https://cloud.google.com/blog/products/management-tools/automate-your-response-to-a-cloud-logging-event
NEW QUESTION # 35
Your company operates nationally and plans to use GCP for multiple batch workloads, including some that are not time-critical. You also need to use GCP services that are HIPAA-certified and manage service costs.
How should you design to meet Google best practices?
- A. Provision standard VMs in the same region to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- B. Provisioning preemptible VMs to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- C. Provision standard VMs to the same region to reduce cost. Disable and then discontinue use of all GCP services and APIs that are not HIPAA-compliant.
- D. Provisioning preemptible VMs to reduce cost. Disable and then discontinue use of all GCP and APIs that are not HIPAA-compliant.
Answer: D
Explanation:
Explanation
https://cloud.google.com/security/compliance/hipaa/
NEW QUESTION # 36
Your company is forecasting a sharp increase in the number and size of Apache Spark and Hadoop jobs being run on your local datacenter You want to utilize the cloud to help you scale this upcoming demand with the least amount of operations work and code change. Which product should you use?
- A. Google Cloud Dataflow
- B. Google Container Engine
- C. Google Compute Engine
- D. Google Cloud Dataproc
Answer: D
Explanation:
Google Cloud Dataproc is a fast, easy-to-use, low-cost and fully managed service that lets you run the Apache Spark and Apache Hadoop ecosystem on Google Cloud Platform. Cloud Dataproc provisions big or small clusters rapidly, supports many popular job types, and is integrated with other Google Cloud Platform services, such as Google Cloud Storage and Stackdriver Logging, thus helping you reduce TCO.
References: https://cloud.google.com/dataproc/docs/resources/faq
NEW QUESTION # 37
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