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NEW QUESTION: 1
Which QoS mechanism calculates the mean queue depth to determine its operation?
A. class-based policing
B. class-based shaping
C. LLQ/CBWFQ
D. WFQ
E. WRED
Answer: E
Explanation:
Weighted random early detection (WRED) is a queuing technique for congestion avoidance. WRED manages how packets are handled when an interface starts becoming congested. When traffic begins to exceed the interface traffic thresholds prior to any congestion, the interface starts dropping packets from selected flows. If the dropped packets are TCP, the TCP source recognizes that packets are getting dropped, and lowers its transmission rate. The lowered transmission rate then reduces the traffic to the interface, avoiding congestion. Because TCP retransmits dropped packets, no actual data loss occurs. WRED drops packets according to the following criteria: RSVP flows are given precedence over non-RSVP flows, to ensure that time-critical packets are transmitted as required. Using IP precedence or DSCP value of the packets, packets with higher precedence are less likely to be dropped. If the default settings are preventing QoS, the precedence value can be used to control how WRED determines when and how often to drop packets. The amount of bandwidth used by the traffic flow. Flows that use the most bandwidth are more likely to have packets dropped. The weight factor defined for the interface determines how frequently packets are dropped. WRED chooses the packets to drop after considering these factors in combination. The net result being that the highest priority and lowest bandwidth traffic is preserved. WRED differs from standard random early detection (RED) in that RED ignores IP precedence, and instead drops packets from all traffic flows, not selecting low precedence or high bandwidth flows. By selectively dropping packets before congestion occurs, WRED prevents an interface from getting flooded, necessitating a large number of dropped packets. This increases the overall bandwidth usage for the interface. An effective use of weighted random early detection is to avoid congestion on a predominantly TCP/IP network, one that has minimal UDP traffic and no significant traffic from other networking protocols. It is especially effective on core devices rather than edge devices, because the traffic marking performed on edge devices can then affect the WRED interfaces throughout the network. The disadvantage of WRED is that only predominantly TCP/IP networks can benefit. Other protocols, such as NetWare IPX/SPX, do not respond to dropped packets by lowering their transmission rates and just retransmit the packets at the same rate. WRED treats all non-TCP/IP packets as having precedence zero. In a mixed protocol environment, WRED might not be the best choice for queuing traffic. Weighted random early detection interfaces automatically favor high priority, low bandwidth traffic flows. No specific policies are needed. However, because WRED automatically uses the IP precedence settings in packets, consider marking all traffic that enters the device or mark the traffic at the point where it enters the network. Marking all traffic will ensure that packets receive the service level intended.
NEW QUESTION: 2
You administer a Microsoft SQL Server 2012 database instance.
The instance is running on a server with the following configuration:
1 TB RAM
SAN storage for database and log files
4 quad-core processors
64-Bit Windows 2008 R2 operating system
This instance hosts a database with large partitioned tables. Users report that complex queries are taking a long time to complete.
While troubleshooting, you discover that CPU utilization is low (less than 20 percent), disk activity is low (little or no waiting processes), and no significant blocking is occurring.
You need to ensure that the instance can process queries as quickly and efficiently as possible.
Which setting should you configure?
Answer:
Explanation:
Explanation
NEW QUESTION: 3
P is the standard deviation of the heights of NBA basketball players. R is the standard deviation of the heights of 8 weight lifters. Is the average height of the NBA players greater than the average height of the weight lifters?
(1) R>P
(2) There are 5 basketball players that are taller than the tallest weight lifter, and 2 players that are shorter than the shortest weight lifter.
A. Statement (2) BY ITSELF is sufficient to answer the question, but statement (1) by itself is not.
B. Statement (1) BY ITSELF is sufficient to answer the question, but statement (2) by itself is not.
C. Either statement BY ITSELF is sufficient to answer the question.
D. Statements (1) and (2) TAKEN TOGETHER are NOT sufficient to answer the question, requiring more data pertaining to the problem.
E. Statements (1) and (2) TAKEN TOGETHER are sufficient to answer the question, even though NEITHER statement BY ITSELF is sufficient.
Answer: D
Explanation:
Explanation/Reference:
Explanation:
Since we have no concrete info about the exact heights, or about the value of P and R, we cannot determine whether the NBA players or the weight lifters are taller. We need more data.
NEW QUESTION: 4
Note: This question is part of a series of questions that present the same scenario.
Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are migrating an on-premises Microsoft SQL Server instance to SQL Server on a Microsoft Azure virtual machine. The instance has 30 databased that consume a total of 2 TB of disk space.
The instance sustains more than 30,000 transactions per second.
You need to provision storage for the virtual machine. The storage must be able to support the same load as the on-premises deployment.
Solution: You create one storage account that has one container. You create multiple VHDs in the container.
Does this meet the goal?
A. No
B. Yes
Answer: A
Explanation:
Each Storage Account handles up to 20.000 IOPS, and 500TB of data.
References: https://www.tech-coffee.net/understand-microsoft-azure-storage-for-virtual- machines/