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NEW QUESTION: 1
A photo-sharing and publishing company receives 10,000 to 150,000 images daily. The company receives the images from multiple suppliers and users registered with the service. The company is moving to AWS and wants to enrich the existing metadata by adding data using Amazon Rekognition.
The following is an example of the additional data:

As part of the cloud migration program, the company uploaded existing image data to Amazon S3 and told users to upload images directly to Amazon S3.
What should the Solutions Architect do to support these requirements?
A. Trigger AWS Lambda based on an S3 event notification to create additional metadata using Amazon Rekognition. Use Amazon RDS MySQL Multi-AZ to store the metadata information and use Lambda to create an index. Use a web front-end with search capabilities backed by Lambda.
B. Use Amazon Kinesis to stream data based on an S3 event. Use an application running in Amazon EC2 to extract metadata from the images. Then store the data on Amazon DynamoDB and Amazon CloudSearch and create an index. Use a web front-end with search capabilities backed by CloudSearch.
C. Trigger AWS Lambda based on an S3 event notification to create additional metadata using Amazon Rekognition. Use Amazon DynamoDB to store the metadata and Amazon ES to create an index. Use a web front-end to provide search capabilities backed by Amazon ES.
D. Start an Amazon SQS queue based on S3 event notifications. Then have Amazon SQS send the metadata information to Amazon DynamoDB. An application running on Amazon EC2 extracts data from Amazon Rekognition using the API and adds data to DynamoDB and Amazon ES. Use a web front-end to provide search capabilities backed by Amazon ES.
Answer: C
Explanation:
https://github.com/aws-samples/lambda-refarch-imagerecognition

NEW QUESTION: 2
電力会社は、スマートメーターから5分ごとに使用状況データを収集して、使用時間の測定を容易にしたいと考えています。メーターがAWSにデータを送信すると、データはAmazon API Gatewayに送信され、AWS Lambda関数によって処理され、Amazonに保存されますDynamoDBテーブルパイロットフェーズでは、Lambda関数の完了に3〜5秒かかりました。よりスマートメーターが展開されると、エンジニアはLambda関数の完了に1〜2分かかっていることに気付きます。デバイスから収集されたメトリックの数DynamoDBでPUT操作を実行中に多くのProvisionedThroughputExceededExceptionエラーが発生し、LambdaからのTooMany Requests Exceptionエラーも多数発生します。
これらの問題を解決する変更の組み合わせはどれですか? (2つ選択)
A. DynamoDBテーブルへの書き込みキャパシティーユニットを増やす
B. スマートメーターのペイロードサイズを増やして、より多くのデータを送信します
C. Lambda関数で使用可能なメモリを増やします
D. API GatewayからAmazon Kinesisデータストリームにデータをストリーミングし、データをバッチで処理します
E. Amazon SQS FIFOキューにデータを収集し、Lambda関数をトリガーして各メッセージを処理します
Answer: A,D

NEW QUESTION: 3
ユーザーの作成と役割の割り当てを取り込むためのアーキテクチャーを設計する必要があります。キャプチャしたデータはAzure Cosmos DBに保存する必要があります。
どのAzureサービスをデザインに含めるべきですか?回答するには、適切なサービスを正しいターゲットにドラッグします。各サービスは1回使用できます。 2回以上、またはまったく違います。コンテンツを表示するには、ペイン間の分割バーをドラッグするか、スクロールする必要があります。
1ポイントの価値がある正しい選択。

Answer:
Explanation:


NEW QUESTION: 4
A university is running an internal web application on AWS that students can access from the university network to check their exam results. The web application runs on Amazon EC2 instances and pulls results from an Amazon DynamoDB table. Auto Scaling is currently configured to add a new web server when CPU is greater than 80% for 5 minutes.
DynamoDB is configured to increase both read and write capacity units by five when utilization is greater than 80%. Exam results are released at 9:00 a.m. each Monday, and
80% of students, attempt to access their unique result within the first 30 minutes. Despite Auto Scaling being enabled, students are complaining of slow response times and errors when they view the site. There are no performance complaints after 9:30 a.m. on Monday.
Which recommendation should a Solutions Architect make to improve performance in a cost-effective manner?
A. Use Amazon CloudFront to cache web request and reduce the load on EC2 and DynamoDB.
B. Scale out the EC2 instances to ensure that the environment scales up and down based on the highest load.
C. Use a scheduled job to scale out EC2 before 9:00 a.m. on Monday and to scale down after 9:30 a.m.
D. Implement Amazon DynamoDB Accelerator to improve database performance and remove the need to scale the read/write units.
Answer: C


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