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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q11-Q16):

NEW QUESTION # 11
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?

Answer: B

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-ca
https://cloud.google.com/solutions/iot/

NEW QUESTION # 12
The current Dress4win system architecture has high latency to some customers because it is located in one data center.
As of a future evaluation and optimizing for performance in the cloud, Dresss4win wants to distribute it's system architecture to multiple locations when Google cloud platform.
Which approach should they use?

A. Use regional managed instance groups and a global load balancer to increase performance because the regional managed instance group can grow instances in each region separately based on traffic.
B. Use regional managed instance groups and a global load balancer to increase reliability by providing automatic failover between zones in different regions.
C. Use a global load balancer with a set of virtual machines that forward the requests to a closer group of virtual machines as part of a separate managed instance groups.
D. Use a global load balancer with a set of virtual machines that forward the requests to a closer group of virtual machines managed by your operations team.

Answer: A

Explanation:
Reference:

NEW QUESTION # 13
You are deploying a PHP App Engine Standard service with SQL as the backend. You want to minimize the number of queries to the database.
What should you do?

A. Set the memcache service level to dedicated. Create a cron task that runs every minute to populate the cache with keys containing query results.
B. Set the memcache service level to shared. Create a key called "cached-queries", and return database values from the key before using a query to Cloud SQL.
C. Set the memcache service level to shared. Create a cron task that runs every minute to save all expected queries to a key called "cached-queries".
D. Set the memcache service level to dedicated. Create a key from the hash of the query, and return database values from memcache before issuing a query to Cloud SQL.

Answer: D

Explanation:
Explanation
https://cloud.google.com/appengine/docs/standard/php/memcache/using

NEW QUESTION # 14
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. TerramEarth's CTO wants to use the raw data from connected vehicles to help identify approximately when a vehicle in the field will have a catastrophic failure. You want to allow analysts to centrally query the vehicle data. Which architecture should you recommend?
A:

B:

C:

D:

A. Option D
B. Option A
C. Option B
D. Option C

Answer: B

Explanation:
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-data
https://cloud.google.com/solutions/iot/

NEW QUESTION # 15
You have developed an application using Cloud ML Engine that recognizes famous paintings from uploaded images. You want to test the application and allow specific people to upload images for the next 24 hours.
Not all users have a Google Account. How should you have users upload images?

A. Create an App Engine web application where users can upload images. Configure App Engine to disable the application after 24 hours. Authenticate users via Cloud Identity.
B. Create an App Engine web application where users can upload images for the next 24 hours.
Authenticate users via Cloud Identity.
C. Have users upload the images to Cloud Storage using a signed URL that expires after 24 hours.
D. Have users upload the images to Cloud Storage. Protect the bucket with a password that expires after
24 hours.

Answer: C

NEW QUESTION # 16
......

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