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NEW QUESTION: 1
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. Capacity planning, TCO calculations, opex/capex allocation
B. Capacity planning, utilization measurement, data center expansion
C. Data Center expansion, TCO calculations, utilization measurement
D. Opex/capex allocation, LAN changes, capacity planning
Answer: A

NEW QUESTION: 2

A. Option B
B. Option A
C. Option C
D. Option D
Answer: B
Explanation:
AWS CloudWatch supports the custom metrics. The user can always capture the custom data and upload
the data to CloudWatch using CLI or APIs. The user can publish data to CloudWatch as single data points
or as an aggregated set of data points called a statistic set using the command put-metric-data. It is
recommended that when the user is having multiple data points per minute, he should aggregate the data
so that it will minimize the number of calls to put-metric-data. In this case it will be single call to
CloudWatch instead of 1000 calls if the data is aggregated.
Reference:
http://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/publishingMetrics.html

NEW QUESTION: 3
After replacing a failed disk, the does not appear as a spare on any node in the cluster.
What should be done to correct this problem?
A. physically remove this disks and re-seat it firmly In the storage bay.
B. Add the disk into aggregate on either node.
C. Physically remove and re-seat each IOM in the Shelf, one at a time.
D. Assign ownership of the replaced disk to a node.
Answer: D