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NEW QUESTION: 1
以下の各ステートメントについて、そのステートメントが正しい場合は「はい」を選択してください。そうでなければ、いいえを選択します。
注:それぞれ正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/china/overview-operations
https://docs.microsoft.com/en-us/azure/azure-government/documentation-government-welcome

NEW QUESTION: 2
Which three statements about OTV are true? (Choose three.)
A. An internal interface is a Layer 2 interface on the edge device that connects to the VLANs that are to be extended. These VLANs typically form a Layer 2 domain known as a site and can contain site-based switches or site-based routers. The internal interface is a Layer 2 access or trunk interface regardless of whether the internal interface connects to a switch or a router.
B. An external interface is a Layer 2 interface on the edge device that connects to the VLANs that are to be extended. These VLANs typically form a Layer 2 domain known as a site and can contain site-based switches or site-based routers. The external interface is a Layer 2 access or trunk interface regardless of whether the external interface connects to a switch or a router.
C. An overlay interface is a logical multiaccess multicast-capable interface. The overlay interface encapsulates Layer 3 frames in IP unicast or multicast headers.
D. The join interface is one of the uplink interfaces of the edge device. The join interface is a point-to-point routed interface. The edge device joins an overlay network through this interface. The IP address of this interface is used to advertise reachability of a MAC address that is present in this site.
E. The join interface is one of the uplink interfaces of the edge device. The join interface is a point-to-point routed interface. The edge device joins an overlay VLAN through this interface. The IP address of this interface is used to advertise reachability of a MAC address that is present in this VLAN.
F. An overlay interface is a logical multiaccess multicast-capable interface. The overlay interface encapsulates Layer 2 frames in IP unicast or multicast headers.
Answer: A,D,F

NEW QUESTION: 3
You work for a company that automatically tags photographs using artificial neural networks (ANNs), which
run on GPUs using C++. You receive millions of images at a time, but only 3 times per day on average. These
images are loaded into an AWS S3 bucket you control for you in a batch, and then the customer publishes a
JSON-formatted manifest into another S3 bucket you control as well. Each image takes 10 milliseconds to
process using a full GPU. Your neural network software requires 5 minutes to bootstrap. Image tags are JSON
objects, and you must publish them to an S3 bucket. Which of these is the best system architectures for this
system?
A. Create an Auto Scaling Load Balanced Elastic Beanstalk worker tier Application and Environment.
Deploy the artificial neural network code to G2 instances in this tier. Set the desired capacity to 1. Make
the code periodically check S3 for new manifests. When a new manifest is detected, push all of the
images in the manifest into the SQS queue associated with the Elastic Beanstalk worker tier.
B. Deploy your artificial neural network code to AWS Lambda as a bundled binary for the C++ extension.
Make an S3 notification configuration on the manifest, which publishes to another AWS Lambda
running controller code. This controller code publishes all the images in the manifest to AWS Kinesis.
Your ANN code Lambda Function uses the Kinesis as an Event Source. The system automatically scales
when the stream contains image events.
C. Make an S3 notification configuration which publishes to AWS Lambda on the manifest bucket. Make
the Lambda create a CloudFormation Stack which contains the logic to construct an autoscaling worker
tier of EC2 G2 instances with the artificial neural network code on each instance. Create an SQS queue
of the images in the manifest. Tear the stack down when the queue is empty.
D. Create an OpsWorks Stack with two Layers. The first contains lifecycle scripts for launching and
bootstrapping an HTTP API on G2 instances for image processing, and the second has an always-on
instance which monitors the S3 manifest bucket for new files. When a new file is detected, request
instances to boot on the artificial neural network layer. When the instances are booted and the HTTP
APIs are up, submit processing requests to individual instances.
Answer: C
Explanation:
Explanation
The best way to get notified when the images get sent to the bucket is the S3 Events. Here you don't need to
provision infrastructure beforehand, and also since the source of S3 provides Event Handling, this should be
used.
The AWS Documentation mentions the following on AWS S3 and Lambda
Amazon S3 can publish events (for example, when an object is created in a bucket) to AWS Lambda and
invoke your Lambda function by passing the event data as a parameter. This integration enables you to write
Lambda functions that process Amazon S3 events. In Amazon S3, you add bucket notification configuration
that identifies the type of event that you want Amazon S3 to publish and the Lambda function that you want to
invoke.
For more information on AWS Lambda and S3 Events, please visit the link:
* http://docs.aws.amazon.com/lambda/latest/dg/with-s3, html

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