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NEW QUESTION: 1
The following statement on the correct route aggregation is
A. Dynamic routing aggregation can be a dynamic routing protocol implementation, but a variety of different dynamic routing protocols for route summarization is not the same degree of support
B. routing aggregation technology can be an organization for all IP addresses as a routing routing convergence routing tables thus reducing the number of routing entries
C. External routing aggregation technology can be screened subnet topology change within the
D. routing aggregation technology can only address the hierarchical structure of the system to use, the address for the planar structure is not
Answer: A,B,C,D
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 need to compose visualizations for operations teams with the following requirements:
* The report must include telemetry data from all 50,000 installations for the most resent 6 weeks (sampling once every minute).
* The report must not be more than 3 hours delayed from live data.
* The actionable report should only show suboptimal links.
* Most suboptimal links should be sorted to the top.
* Suboptimal links can be grouped and filtered by regional geography.
* User response time to load the report must be <5 seconds.
Which approach meets the requirements?
A. Load the data into Google Cloud Datastore tables, write a Google App Engine Application that queries all rows, applies a function to derive the metric, and then renders results in a table using the Google charts and visualization API.
B. Load the data into Google BigQuery tables, write Google Apps Script that queries the data, calculates the metric, and shows only suboptimal rows in a table in Google Sheets.
C. Load the data into Google Sheets, use formulas to calculate a metric, and use filters/sorting to show only suboptimal links in a table.
D. Load the data into Google BigQuery tables, write a Google Data Studio 360 report that connects to your data, calculates a metric, and then uses a filter expression to show only suboptimal rows in a table.
Answer: A
NEW QUESTION: 3
Overview
In the following tasks, you will demonstrate your ability to work in Google Docs. Cascara is a furniture wholesaler with warehouses located in Europe. You will be filling out a form to ship a load of goods to one of the warehouses. Use the Carriage of Goods by Road (CGR) for all the tasks in this scenario.
Insert the electronic signature, carrier_signature.png, in the cell titled, 17 Signature or stamp of the carrier.
Answer:
Explanation:
NEW QUESTION: 4
ゾーンベースのファイアウォールで「すべて拒否」ポリシーが例外となるのはいつですか
A. トラフィックが同じゾーン内の2つのインターフェイスを通過する
B. トラフィックは自己ゾーン経由でルータ上で終了する
C. トラフィックは、異なるゾーンの2つのインターフェイスを通過します。
D. トラフィックは自己ゾーン経由でルータ上で終了する
E. 自ゾーン経由でルータからのトラフィックソース
Answer: A
Explanation:
+ There is a default zone, called the self zone, which is a logical zone. For any packets directed to the router directly (the destination IP represents the packet is for the router), the router automatically considers that traffic to be entering the self zone. In addition, any traffic initiated by the router is considered as leaving the self zone.
By default, any traffic to or from the self zone is allowed, but you can change this policy.
+ For the rest of the administrator-created zones, no traffic is allowed between interfaces in different zones.
+ For interfaces that are members of the same zone, all traffic is permitted by default.
Source: Cisco Official Certification Guide, Zones and Why We Need Pairs of Them, p.380