COF-C02 Fragen&Antworten, COF-C02 Online Test & COF-C02 Prüfungsvorbereitung - Assogba
SnowPro Core Certification Exam
- Exam Number/Code : COF-C02
- Exam Name : SnowPro Core Certification Exam
- Questions and Answers : 213 Q&As
- Update Time: 2019-01-10
- Price:
$ 99.00$ 39.00
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NEW QUESTION: 1
Refer to the exhibit.
The administrator expects the AP to connect to a cluster, but the AP fails to connect. The administrator
examines the configuration of an AP from apboot mode shown in the exhibit. What can the administrator
determine about the configuration of the AP?
A. The AP is configured to terminate on a Mobility Controller in a cluster.
B. The AP is configured to terminate on a non-cluster Mobility Controller.
C. The AP is configured as a RAP to terminate on a Mobility Master.
D. The AP is configured as a RAP to terminate on a stand-alone controller.
Answer: C
NEW QUESTION: 2
You are designing a microservices architecture that will support a web application.
The solution must meet the following requirements:
Allow independent upgrades to each microservice.
*
Deploy the solution on-premises and to Azure.
*
Set policies for performing automatic repairs to the microservices.
*
Support low-latency and hyper-scale operations.
You need to recommend a technology.
What should you recommend?
A. Azure Virtual Machine Scale Set
B. Azure Container Service
C. Azure Service Fabric
D. Azure Container Instance
Answer: C
Explanation:
References:
https://msdn.microsoft.com/en-us/magazine/mt595752.aspx
==========================================
Topic 4, Lucerne PublishingBackground
Overview
Lucerne Publishing creates, stores, and delivers online media for advertising companies.
This media is streamed to computers by using the web, and to mobile devices around the world by using native applications. The company currently supports the iOS, Android, and Windows Phone 8.1 platform.
Lucerne Publishing uses proprietary software to manage its media workflow. This software has reached the end of its lifecycle. The company plans to move its media workflows to the cloud. Lucerne Publishing provides access to its customers, who are third-party companies, so that they can download, upload, search, and index media that is stored on Lucerne Publishing servers.
Apps and Applications
Lucerne Publishing develops the applications that customers use to deliver media. The company currently provides the following media delivery applications:
*
Lucerne Media W - a web application that delivers media by using any browser
*
Lucerne Media M - a mobile app that delivers media by using Windows Phone 8.1
*
Lucerne Media A - a mobile app that delivers media by using an iOS device
*
Lucerne Media N - a mobile app that delivers media by using an Android device
*
Lucerne Media D - a desktop client application that customer's install on their local computer Business Requirements Lucerne Publishing's customers and their consumers have the following requirements:
*
Access to media must be time-constricted once media is delivered to a consumer.
*
The time required to download media to mobile devices must be minimized.
*
Customers must have 24-hour access to media downloads regardless of their location or time zone.
*
Lucerne Publishing must be able to monitor the performance and usage of its customer-facing app.
Lucerne Publishing wants to make its asset catalog searchable without requiring a database redesign.
*
Customers must be able to access all data by using a web application. They must also be able to access data by using a mobile app that is provided by Lucerne Publishing.
*
Customers must be able to search for media assets by key words and media type.
*
Lucerne Publishing wants to move the asset catalog database to the cloud without formatting the source data.
Other Requirements
Development
Code and current development documents must be backed up at all times. All solutions must be automatically built and deployed to Azure when code is checked in to source control.
Network Optimization
Lucerne Publishing has a .NET web application that runs on Azure. The web application analyzes storage and the distribution of its media assets. It needs to monitor the utilization of the web application. Ultimately, Lucerne Publishing hopes to cut its costs by reducing data replication without sacrificing its quality of service to its customers. The solution has the following requirements:
*
Optimize the storage location and amount of duplication of media.
*
Vary several parameters including the number of data nodes and the distance from node to customers.
*
Minimize network bandwidth.
*
Lucerne Publishing wants be notified of exceptions in the web application.
Technical Requirements
Data Mining
Lucerne Publishing constantly mines its data to identify customer patterns. The company plans to replace the existing on-premises cluster with a cloud-based solution. Lucerne Publishing has the following requirements:
Virtual machines:
*
The data mining solution must support the use of hundreds to thousands of processing cores.
*
Minimize the number of virtual machines by using more powerful virtual machines.
Each virtual machine must always have eight or more processor cores available.
*
Allow the number of processor cores dedicated to an analysis to grow and shrink automatically based on the demand of the analysis.
*
Virtual machines must use remote memory direct access to improve performance.
Task scheduling:
The solution must automatically schedule jobs. The scheduler must distribute the jobs based on the demand and available resources.
Data analysis results:
The solution must provide a web service that allows applications to access the results of analyses.
Other Requirements
Feature Support
*
Ad copy data must be searchable in full text.
*
Ad copy data must indexed to optimize search speed.
*
Media metadata must be stored in Azure Table storage.
*
Media files must be stored in Azure BLOB storage.
*
The customer-facing website must have access to all ad copy and media.
*
The customer-facing website must automatically scale and replicate to locations around the world.
*
Media and data must be replicated around the world to decrease the latency of data transfers.
*
Media uploads must have fast data transfer rates (low latency) without the need to upload the data offline.
Security
*
Customer access must be managed by using Active Directory.
*
Media files must be encrypted by using the PlayReady encryption method.
*
Customers must be able to upload media quickly and securely over a private connection with no opportunity for internet snooping.
NEW QUESTION: 3
You are designing a service that aggregates clickstream data in batch and delivers reports to subscribers via email only once per week. Data is extremely spikey, geographically distributed, high-scale, and unpredictable.
How should you design this system?
A. Use a CloudFront distribution with access log delivery to S3. Clicks should be recorded as querystring GETs to the distribution. Reports are built and sent by periodically running EMRjobs over the access logs in S3.
C Use API Gateway invoking Lambdas which PutRecords into Kinesis, and EMR running Spark performing GetRecords on Kinesis to scale with spikes. Spark on EMR outputs the analysis to S3, which are sent out via email.
D- Use AWS Elasticsearch service and EC2 Auto Scaling groups. The Autoscaling groups scale based on click throughput and stream into the Elasticsearch domain, which is also scalable. Use Kibana to generate reports periodically.
B. Use a large RedShift cluster to perform the analysis, and a fleet of Lambdas to perform record inserts into the RedShift tables. Lambda will scale rapidly enough for the traffic spikes.
Answer: A
Explanation:
Explanation
When you look at building reports or analyzing data from a large data set, you need to consider CMR because this service is built on the Hadoop framework which is used to processes large data sets.
The ideal approach to getting data onto CMR is to use S3. Since the Data is extremely spikey and geographically distributed, using edge locations via Cloudfront distributions is the best way to fetch the data.
Option A is invalid because RedShift is more of a petabyte storage cluster.
Option C is invalid because having both Kinesis and CMR for the job analysis is redundant.
Option D is invalid because Elastic Search is not an option for processing records.
For more information on Amazon CMR, please visit the below URL:
* https://aws.amazon.com/emr/