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NEW QUESTION: 1
Refer to the exhibit.

A customer currently has a large EIGRP-based network with several remote sites attached. All remote sites connect to the two corporate data centers, depicted as 10.1.1.0 and 10.1.2.0. The customer has experienced several network-wide failures where neighbors were stuck-in-active and had other network stability issues due to some links flapping. Which two redesign options increase stability and reduce the load on the remote site routers, still maintaining optimal routing between remote sites and the two data centers? (Choose two)
A. Set the hello interval timer to be larger than the hold interval
B. Perform summarization at the remote sites, selectively leaking routes sent to the data centers
C. Perform summarization at the data centers, selectively leaking routes sent to the remote sites
D. Set the data center routers as stub-routers
E. Increase the hold interval to accommodate lost hello packets on error-prone links
Answer: C,D

NEW QUESTION: 2
Case Study: 1 - Flowlogistic
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 wants to use Google BigQuery as their primary analysis system, but they still have Apache Hadoop and Spark workloads that they cannot move to BigQuery. Flowlogistic does not know how to store the data that is common to both workloads. What should they do?
A. Store the common data in BigQuery and expose authorized views.
B. Store he common data in the HDFS storage for a Google Cloud Dataproc cluster.
C. Store the common data encoded as Avro in Google Cloud Storage.
D. Store the common data in BigQuery as partitioned tables.
Answer: A

NEW QUESTION: 3
IAM 사용자가 다른 루트 계정의 버킷에 속하는 객체에 대해 작업을 수행하려고 합니다.
아래 언급 된 옵션 중 AWS S3가 확인하지 않는 옵션은 무엇입니까?
A. 객체 소유자가 IAM 사용자에게 액세스 권한을 제공했습니다
B. 버킷에서 IAM 사용자의 부모가 제공 한 권한
C. 버킷 소유자가 IAM 사용자에게 제공 한 권한
D. IAM 사용자의 부모가 제공 한 권한
Answer: B
Explanation:
설명:
IAM 사용자가 다른 AWS 사용자 버킷에 속한 객체에 대해 어떤 작업을 수행하려고 하면 S3는 IAM 사용자의 소유자에게 충분한 권한을 부여했는지 확인합니다. 또한 버킷의 정책과 객체 소유자가 정의한 정책을 확인합니다.
http://docs.aws.amazon.com/AmazonS3/latest/dev/access-control-auth-workflow-object- operation.html

NEW QUESTION: 4

A. ipv6 next-hop-self eigrp
B. metric weights
C. ipv6 bandwidth-percent eigrp
D. ipv6 summary-address eigrp
Answer: D

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