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NEW QUESTION: 1
The internetwork infrastructure of company XYZ consists of a single OSPF area as shown in the graphic. There is concern that a lack of router resources is impeding internetwork performance.
As part of examining the router resources, the OSPF DRs need to be known. All the router OSPF priorities are at the default and the router IDs are shown with each router.
Which routers are likely to have been elected as DR? (Choose two.)

A. Corp-3
B. Corp-2
C. Branch-1
D. Corp-1
E. Corp-4
F. Branch-2
Answer: E,F
Explanation:
Explanation
There are 2 segments on the topology above which are separated by Corp-3 router. Each segment will have a DR so we have 2 DRs.
To select which router will become DR they will compare their router-IDs. The router with highest (best) router-ID will become DR. The router-ID is chosen in the order below:
+ The highest IP address assigned to a loopback (logical) interface.
+ If a loopback interface is not defined, the highest IP address of all active router's physical interfaces will be chosen.
In this question, the IP addresses of loopback interfaces are not mentioned so we will consider IP addresses of all active router's physical interfaces. Router Corp-4 (10.1.40.40) & Branch-2 (10.2.20.20) have highest "active" IP addresses so they will become DRs.

NEW QUESTION: 2
There are three phases of Non Disruptive Volume Movement (NDVM). What is the correct sequence of these phases?
A. Setup Phase, Data Copy Phase, Cutover Phase
B. Begin Phase, Move Phase, Complete Phase
C. Initialization phase, Copy Phase, Migrate Phase
D. Setup Phase, Mirror Phase, Cutover Phase
Answer: A
Explanation:
Explanation/Reference:
Explanation:
https://communities.netapp.com/servlet/JiveServlet/previewBody/9734-102-1-17848/ PDF_Tips_Data_Motion_0211.pdf
Non-disruptive Volume Movement is called DataMotion. DataMotion uses SnapMirror for volume migration.
A DataMotion migration occurs in three phases:
1. Setup
2. Data copy
3. Cutover

NEW QUESTION: 3
Case Study: 6 - TerramEarth
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.
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 and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, 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.

Support the dealer network with more data on how their customers use their equipment to 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.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east

coast.
Create a backup strategy.

Increase security of data transfer from equipment to the datacenter.

Improve data in the data warehouse.

Use customer and equipment data to anticipate customer needs.

Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2

- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs

- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server

- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower 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. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow Google-recommended practices.
Considering the technical requirements, which components should you use for the ingestion of the data?
A. Google Kubernetes Engine with an SSL Ingress
B. Compute Engine with specific SSH keys
C. Compute Engine with project-wide SSH keys
D. Cloud IoT Core with public/private key pairs
Answer: A

NEW QUESTION: 4
Using the following assumptions, calculate the stock price at which investors Helen Alba, who shorts the stock on margin, and Kobin Lubis, who purchases the stock on margin, will receive a margin call.
Which of the following choices is closest to the correct answer? Alba will receive a margin call at a stock price of:
A. $33.00 and Lubis will receive a margin call at a stock price of $53.45.
B. $46.85 and Lubis will receive a margin call at a stock price of $33.00.
C. $37.66 and Lubis will receive a margin call at a stock price of $53.45.
D. $33.00 and Lubis will receive a margin call at a stock price of $37.66.
Answer: B
Explanation:
Explanation/Reference:
Explanation:
Calculations are as follows:
Since Alba is short(sold the stock), the formula for the margin call price is:
Margin Call = (original price) * (1 + initial margin) / (1 + maintenance margin)
= $42 * (1 + 0.45) / (1 + 0.30) =$46.85
Since Lubis is long(purchased the stock), the formula for the margin call price is:
Margin Call = (original price) * (1 - initial margin) / (1 - maintenance margin)
= $42 * (1 - 0.45) / (1 - 0.30) =$33.00