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NEW QUESTION: 1
Which two events occur when a packet is decapsulated in a GRE tunnel? (Choose two.)
A. The TTL of the payload packet is decremented.
B. The TTL of the payload packet is incremented.
C. The destination IPv4 address in the IPv4 payload is used to forward the packet.
D. The GRE keepalive mechanism is reset.
E. The source IPv4 address in the IPv4 payload is used to forward the packet.
F. The version field in the GRE header is incremented.
Answer: A,C
Explanation:
Explanation/Reference:
Explanation:
After the GRE encapsulated packet reaches the remote tunnel endpoint router, the GRE packet is decapsulated. The destination address lookup of the outer IP header (this is the same as the tunnel destination address) will find a local address (receive) entry on the ingress line card.
The first step in GRE decapsulation is to qualify the tunnel endpoint, before admitting the GRE packet into the router, based on the combination of tunnel source (the same as source IP address of outer IP header) and tunnel destination (the same as destination IP address of outer IP header). If the received packet fails tunnel admittance qualification check, the packet is dropped by the decapsulation router. On successful tunnel admittance check, the decapsulation strips the outer IP and GRE header off the packet, then starts processing the inner payload packet as a regular packet.
When a tunnel endpoint decapsulates a GRE packet, which has an IPv4/IPv6 packet as the payload, the destination address in the IPv4/IPv6 payload packet header is used to forward the packet, and the TTL of the payload packet is decremented.
Reference. http://www.cisco.com/c/en/us/td/docs/routers/asr9000/software/asr9k_r5-3/addr- serv/ configuration/guide/b-ipaddr-cg53asr9k/b-ipaddr-cg53asr9k_chapter_01001.html
NEW QUESTION: 2
You plan to build a team data science environment. Data for training models in machine learning pipelines will be over 20 GB in size.
You have the following requirements:
* Models must be built using Caffe2 or Chainer frameworks.
* Data scientists must be able to use a data science environment to build the machine learning pipelines and train models on their personal devices in both connected and disconnected network environments.
* Personal devices must support updating machine learning pipelines when connected to a network.
You need to select a data science environment.
Which environment should you use?
A. Azure Machine Learning Studio
B. Azure Kubernetes Service (AKS)
C. Azure Machine Learning Service
D. Azure Databricks
Answer: C
Explanation:
The Data Science Virtual Machine (DSVM) is a customized VM image on Microsoft's Azure cloud built specifically for doing data science. Caffe2 and Chainer are supported by DSVM.
DSVM integrates with Azure Machine Learning.
Incorrect Answers:
B: Use Machine Learning Studio when you want to experiment with machine learning models quickly and easily, and the built-in machine learning algorithms are sufficient for your solutions.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/overview
NEW QUESTION: 3
What percentage of corporate data lives at the edge of mobility?
A. 155%
B. 15%
C. 27%
D. 82%
Answer: D
NEW QUESTION: 4
What are valid service states that represent the availability of an eDisk?
A. Ready, Not Ready, Degraded
B. Failed, Ready, Not Ready
C. Failed, Degraded, Normal
D. Failed, Not Ready, Degraded
Answer: C