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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
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 is rolling out their real-time inventory tracking system. The tracking devices will all send package-tracking messages, which will now go to a single Google Cloud Pub/Sub topic instead of the Apache Kafka cluster. A subscriber application will then process the messages for real-time reporting and store them in Google BigQuery for historical analysis. You want to ensure the package data can be analyzed over time.
Which approach should you take?
A. Use the NOW () function in BigQuery to record the event's time.
B. Attach the timestamp on each message in the Cloud Pub/Sub subscriber application as they are received.
C. Use the automatically generated timestamp from Cloud Pub/Sub to order the data.
D. Attach the timestamp and Package ID on the outbound message from each publisher device as they are sent to Clod Pub/Sub.
Answer: D
NEW QUESTION: 2
You have business services that run on an on-premises mainframe server.
You must provide an intermediary configuration to support existing business services and
Azure. The business services cannot be rewritten. The business services are not exposed externally.
You need to recommend an approach for accessing the business services.
What should you recommend?
A. Expose the business services to the Azure Service Bus by using a custom service that uses relay binding.
B. Connect to the on-premises server by using a custom service in Azure.
C. Move all business service functionality to Azure.
D. Expose the business services externally.
Answer: A
Explanation:
The Service Bus relay service enables you to build hybrid applications that run in both an
Azure datacenter and your own on-premises enterprise environment. The Service Bus relay facilitates this by enabling you to securely expose Windows Communication
Foundation (WCF) services that reside within a corporate enterprise network to the public cloud, without having to open a firewall connection, or require intrusive changes to a corporate network infrastructure.
References: http://azure.microsoft.com/en-gb/documentation/articles/service-bus-dotnet- how-to-use-relay/
NEW QUESTION: 3
Sie haben einen Hyper-V-Host mit dem Namen Server1, auf dem Windows Server 2016 ausgeführt wird. Server1 verfügt über mehrere Netzwerkadapter, für die VMQ (Virtual Machine Queue) aktiviert ist.
Auf Server1 erstellen Sie eine virtuelle Maschine mit dem Namen VM1 (siehe Abbildung).
Sie müssen sicherstellen, dass Sie Virtual Receive-Side Scaling (vRSS) auf VM1 verwenden können.
Was tun?
A. Fügen Sie zusätzliche Netzwerkadapter hinzu.
B. Zusätzlichen Speicher hinzufügen.
C. Aktivieren Sie den Data Exchange-Integrationsdienst.
D. Fügen Sie zusätzliche Prozessoren hinzu.
Answer: D
Explanation:
References: https://docs.microsoft.com/en-us/windows-server/networking/technologies/vrss/vrss-top
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