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NEW QUESTION: 1
Which of the following are not BGRP data structures? (Choose all that apply.)
A. EIGRP neighbor table
B. EIGRP interface table
C. EIGRP adjacency table
D. EIGRP database table
E. EIGRP topology table
F. EIGRP CEF table
Answer: C,D,F

NEW QUESTION: 2
MJTelco Case Study
Company Overview
MJTelco is a startup that plans to build networks in rapidly growing, underserved markets around the world. The company has patents for innovative optical communications hardware. Based on these patents, they can create many reliable, high-speed backbone links with inexpensive hardware.
Company Background
Founded by experienced telecom executives, MJTelco uses technologies originally developed to overcome communications challenges in space. Fundamental to their operation, they need to create a distributed data infrastructure that drives real-time analysis and incorporates machine learning to continuously optimize their topologies. Because their hardware is inexpensive, they plan to overdeploy the network allowing them to account for the impact of dynamic regional politics on location availability and cost.
Their management and operations teams are situated all around the globe creating many-to-many relationship between data consumers and provides in their system. After careful consideration, they decided public cloud is the perfect environment to support their needs.
Solution Concept
MJTelco is running a successful proof-of-concept (PoC) project in its labs. They have two primary needs:
Scale and harden their PoC to support significantly more data flows generated when they ramp to more

than 50,000 installations.
Refine their machine-learning cycles to verify and improve the dynamic models they use to control

topology definition.
MJTelco will also use three separate operating environments - development/test, staging, and production
- to meet the needs of running experiments, deploying new features, and serving production customers.
Business Requirements
Scale up their production environment with minimal cost, instantiating resources when and where

needed in an unpredictable, distributed telecom user community.
Ensure security of their proprietary data to protect their leading-edge machine learning and analysis.

Provide reliable and timely access to data for analysis from distributed research workers

Maintain isolated environments that support rapid iteration of their machine-learning models without

affecting their customers.
Technical Requirements
Ensure secure and efficient transport and storage of telemetry data

Rapidly scale instances to support between 10,000 and 100,000 data providers with multiple flows

each.
Allow analysis and presentation against data tables tracking up to 2 years of data storing approximately

100m records/day
Support rapid iteration of monitoring infrastructure focused on awareness of data pipeline problems

both in telemetry flows and in production learning cycles.
CEO Statement
Our business model relies on our patents, analytics and dynamic machine learning. Our inexpensive hardware is organized to be highly reliable, which gives us cost advantages. We need to quickly stabilize our large distributed data pipelines to meet our reliability and capacity commitments.
CTO Statement
Our public cloud services must operate as advertised. We need resources that scale and keep our data secure. We also need environments in which our data scientists can carefully study and quickly adapt our models. Because we rely on automation to process our data, we also need our development and test environments to work as we iterate.
CFO Statement
The project is too large for us to maintain the hardware and software required for the data and analysis.
Also, we cannot afford to staff an operations team to monitor so many data feeds, so we will rely on automation and infrastructure. Google Cloud's machine learning will allow our quantitative researchers to work on our high-value problems instead of problems with our data pipelines.
You create a new report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. It is company policy to ensure employees can view only the data associated with their region, so you create and populate a table for each region. You need to enforce the regional access policy to the data.
Which two actions should you take? (Choose two.)
A. Ensure all the tables are included in global dataset.
B. Adjust the settings for each view to allow a related region-based security group view access.
C. Adjust the settings for each dataset to allow a related region-based security group view access.
D. Adjust the settings for each table to allow a related region-based security group view access.
E. Ensure each table is included in a dataset for a region.
Answer: B,E

NEW QUESTION: 3
ある会社がAWSにデプロイされたVoIPアプリケーションを持っています。アプリケーションはリモートオフィスの従業員によってアクセスされ、待ち時間やパケット損失に非常に敏感です。待ち時間とパケットループを最小限に抑えることは、コストを最小限に抑えることよりも優先順位が高くなります。
従業員がアプリケーションにアクセスするときどきの困難を報告しています。 Local Network EngineerはLAN上で徹底的なトラブルシューティングを完了しました、そして問題を引き起こしているかもしれない混雑または機器故障のどんな徴候でも識別することができません。リモートオフィスとアプリケーション間の接続の問題に対処するための最良の方法は何ですか？
A. VPCへのVPN接続を構成するパブリックインターネット経由のVPN接続を介してすべてのトラフィックをアプリケーションにルーティングする
B. VPCへの直接接続を確立します。直接接続接続を介してすべてのトラフィックをアプリケーションにルーティングします。
C. VPCピアリングを有効にしてインスタンス間の待ち時間を短縮しますピアリング接続でQoSを有効にします
D. パブリックインターネットトラフィックを介してリモートオフィスに割り当てられるIPに高い優先順位を付けるようにAmazon Trusted Advisorを設定します。
Answer: B
Explanation:
https://docs.aws.amazon.com/vpc/latest/peering/create-vpc-peering-connection.html

NEW QUESTION: 4
An LTM Specialist has been asked to configure a virtual server to distribute connections between a pool of two application servers with addresses 172.16.20.1 and 172.16.20.2. The application servers are listening on TCP ports 80 and 443. The application administrators have asked that clients be directed to the same node for both HTTP and HTTPS requests within the same session.
Virtual servers vs_http and vs_https have been created, listening on 1.2.3.100:80 and 1.2.3.100:443, respectively.
Which configuration option will result in the desired behavior?
A. Create pool app_pool with members 172.16.20.1:any and 172.16.20.2:any Assign app_pool as the default pool for both vs_http and vs_https Disable port translation for vs_http and vs_https
B. Create pool http_pool with members 172.16.20.1:80 and 172.16.20.2:80 Create pool https_pool with members 172.16.20.1:443 and 172.16.20.2:443 Assign http_pool as the default pool for vs_http Assign https_pool as the default pool for vs_https Create an SSL persistence profile with "match across virtual servers" enabled Assign the persistence profile to vs_http
C. Create pool http_pool with members 172.16.20.1:80 and 172.16.20.2:80 Create pool https_pool with members 172.16.20.1:443 and 172.16.20.2:443 Assign http_pool as the default pool for vs_http Assign https_pool as the default pool for vs_https Create a source address persistence profile with "match across services" enabled Assign the persistence profile to vs_http and vs_https
D. Create pool http_pool with members 172.16.20.1:80 and 172.16.20.2:80 Assign pool http_pool as the default pool for both vs_https and vs_https Disable port translation for vs_https Create an SSL persistence profile with "match across virtual servers" enabled Assign the persistence profile to vs_http.
Answer: C