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NEW QUESTION: 1
Flowlogistic Case Study
Company Overview
Flowlogistic is a leading logistics and supply chain provider. They help businesses throughout the world
manage their resources and transport them to their final destination. The company has grown rapidly,
expanding their offerings to include rail, truck, aircraft, and oceanic shipping.
Company Background
The company started as a regional trucking company, and then expanded into other logistics market.
Because they have not updated their infrastructure, managing and tracking orders and shipments has
become a bottleneck. To improve operations, Flowlogistic developed proprietary technology for tracking
shipments in real time at the parcel level. However, they are unable to deploy it because their technology
stack, based on Apache Kafka, cannot support the processing volume. In addition, Flowlogistic wants to
further analyze their orders and shipments to determine how best to deploy their resources.
Solution Concept
Flowlogistic wants to implement two concepts using the cloud:
Use their proprietary technology in a real-time inventory-tracking system that indicates the location of
their loads
Perform analytics on all their orders and shipment logs, which contain both structured and unstructured
data, to determine how best to deploy resources, which markets to expand info. They also want to use
predictive analytics to learn earlier when a shipment will be delayed.
Existing Technical Environment
Flowlogistic architecture resides in a single data center:
Databases
8 physical servers in 2 clusters
- SQL Server - user data, inventory, static data
3 physical servers
- Cassandra - metadata, tracking messages
10 Kafka servers - tracking message aggregation and batch insert
Application servers - customer front end, middleware for order/customs
60 virtual machines across 20 physical servers
- Tomcat - Java services
- Nginx - static content
- Batch servers
Storage appliances
- iSCSI for virtual machine (VM) hosts
- Fibre Channel storage area network (FC SAN) - SQL server storage
- Network-attached storage (NAS) image storage, logs, backups
10 Apache Hadoop /Spark servers
- Core Data Lake
- Data analysis workloads
20 miscellaneous servers
- Jenkins, monitoring, bastion hosts,
Business Requirements
Build a reliable and reproducible environment with scaled panty of production.
Aggregate data in a centralized Data Lake for analysis
Use historical data to perform predictive analytics on future shipments
Accurately track every shipment worldwide using proprietary technology
Improve business agility and speed of innovation through rapid provisioning of new resources
Analyze and optimize architecture for performance in the cloud
Migrate fully to the cloud if all other requirements are met
Technical Requirements
Handle both streaming and batch data
Migrate existing Hadoop workloads
Ensure architecture is scalable and elastic to meet the changing demands of the company.
Use managed services whenever possible
Encrypt data flight and at rest
Connect a VPN between the production data center and cloud environment
SEO Statement
We have grown so quickly that our inability to upgrade our infrastructure is really hampering further growth
and efficiency. We are efficient at moving shipments around the world, but we are inefficient at moving
data around.
We need to organize our information so we can more easily understand where our customers are and
what they are shipping.
CTO Statement
IT has never been a priority for us, so as our data has grown, we have not invested enough in our
technology. I have a good staff to manage IT, but they are so busy managing our infrastructure that I
cannot get them to do the things that really matter, such as organizing our data, building the analytics, and
figuring out how to implement the CFO' s tracking technology.
CFO Statement
Part of our competitive advantage is that we penalize ourselves for late shipments and deliveries. Knowing
where out shipments are at all times has a direct correlation to our bottom line and profitability.
Additionally, I don't want to commit capital to building out a server environment.
Flowlogistic's CEO wants to gain rapid insight into their customer base so his sales team can be better
informed in the field. This team is not very technical, so they've purchased a visualization tool to simplify
the creation of BigQuery reports. However, they've been overwhelmed by all the data in the table, and are
spending a lot of money on queries trying to find the data they need. You want to solve their problem in the
most cost-effective way. What should you do?
A. Create an additional table with only the necessary columns.
B. Create a view on the table to present to the virtualization tool.
C. Create identity and access management (IAM) roles on the appropriate columns, so only they appear
in a query.
D. Export the data into a Google Sheet for virtualization.
Answer: B
NEW QUESTION: 2
Which three statements are true about BGP? (Choose three)
A. eBGP peering adds value in small networks with multiple upstream connections
B. iBGP peering adds value in large enterprise environments with multiple upstream connections
C. eBGP peering adds value in large enterprise environments with multiple upstream connections
D. iBGP peering adds value in small networks with multiple upstream connections
E. iBGP peering adds value in small networks with a single upstream connection
Answer: A,B,C
NEW QUESTION: 3
Which prefix List Matches and permits all RFC 1918 network 1 0.0.0.0 routes that have subnet marks of /16 trough /24?
A. ip prefix-list foo seq 10 perm it 10.0.0.0/16 le 24.
B. ip prefix-list foo seq 10 perm it 1 0.0.0.0/8 ge 15 le 25.
C. ip prefix-list foo seq 10 permit 10.0.0.0/8 ge 16 1e 24.
D. ip prefix-list foo seq 10 permit 10.0.0.0/16 ge 15 le 25.
Answer: C
NEW QUESTION: 4
Which key combination can you use to stop a process that runs in the foreground?
A. Ctrl + Backspace
B. Ctrl + Alt + X
C. Ctrl +Z
D. Ctrl +X
Answer: C
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