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NEW QUESTION: 1
Refer to the exhibit.
The self-service Webex Teams bot is failing when many users attempt to interact with it at the same time. Drag and drop the code snippets from the left onto the correct item numbers on the right that match the missing sections in the exhibit to complete this code to handle this high-load situation.
Answer:
Explanation:
NEW QUESTION: 2
Which of the following is an advantage of implementing QoS features in hardware, instead of in software?
A. increased QoS feature support
B. consistent cross-platform QoS feature support
C. reduced CPU processing load
D. consistent cross-platform QoS configuration syntax
Answer: C
Explanation:
Explanation/Reference:
Section: Considerations for Expanding an Existing Network Explanation
Explanation:
Reduced CPU processing load is an advantage of implementing Quality of Service (QoS) in hardware instead of in software. Cisco platforms implement QoS features in either hardware or software, depending on the specific platform. For example, most Cisco switches implement QoS features only in hardware, whereas most Cisco routers implement QoS features in software. A limited number of Cisco platforms can implement QoS features in either hardware or software. Best practice dictates that hardware-based QoS features should be preferred over software-based QoS features when feasible.
When QoS features are implemented in software, the CPU must dedicate a portion of available processing power to the configured QoS policies. Depending on the volume of traffic and the number and complexity of configured QoS policies, it is possible for QoS features to be responsible for a significant portion of the CPU processing load on a software-based QoS platform. If the CPU processing load becomes too high, it could impact other operations on the affected platform, such as responding to network events. In order to ensure that the CPU processing load does not become too high, Cisco recommends using hardware- based QoS features when available. Hardware-based QoS features reduce the CPU processing load by offloading QoS-related processing from the CPU to dedicated hardware, such as QoS-oriented application- specific integrated circuits (ASICs).
Reference:
CCDA 200-310 Official Cert Guide, Chapter 3, Campus LAN QoS Considerations, pp. 111-112 Cisco: Medianet WAN Aggregation QoS Design 4.0: Hardware versus Software QoS
NEW QUESTION: 3
Refer to the exhibit.
Which prefixen will have their dintance changed?
A. all internal prefixen in the range 10.1.12.0-10.1.12.255 learned from peern matching accenn-lint 10.
B. all prefixen matching accenn-lint 10 learned from peern in the range 10.1.12.0-10.1.12.255
C. all internal prefixen matching accenn-lint 10 learned from peern in the range 10.1.12.0-10.1.12.255
D. all prefixen in the range 10.1.12.0-10.1.12.255 learned from peern matching accenn-lint 10
Answer: C
NEW QUESTION: 4
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft Azure SQL Database instance. The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations
You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view
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