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NEW QUESTION: 1
A company runs a video processing platform. Files are uploaded by users who connect to a web server, which stores them on an Amazon EFS share. This web server is running on a single Amazon EC2 instance. A different group of instances, running in an Auto Scaling group, scans the EFS share directory structure for new files to process and generates new videos (thumbnails, different resolution, compression, etc.) according to the instructions file, which is uploaded along with the video files. A different application running on a group of instances managed by an Auto Scaling group processes the video files and then deletes them from the EFS share. The results are stored in an S3 bucket. Links to the processed video files are emailed to the customer.
The company has recently discovered that as they add more instances to the Auto Scaling Group, many files are processed twice, so image processing speed is not improved. The maximum size of these video files is 2GB.
What should the Solutions Architect do to improve reliability and reduce the redundant processing of video files?
A. Set up a cron job on the web server instance to synchronize the contents of the EFS share into Amazon S3. Trigger an AWS Lambda function every time a file is uploaded to process the video file and store the results in Amazon S3. Using Amazon CloudWatch Events trigger an Amazon SES job to send an email to the customer containing the link to the processed file.
B. Modify the web application to upload the video files directly to Amazon S3. Use Amazon CloudWatch Events to trigger an AWS Lambda function every time a file is uploaded, and have this Lambda function put a message into an Amazon SQS queue. Modify the video processing application to read from SQS queue for new files and use the queue depth metric to scale instances in the video processing Auto Scaling group.
C. Rewrite the web application to run directly from Amazon S3 and use Amazon API Gateway to upload the video files to an S3 bucket. Use an S3 trigger to run an AWS Lambda function each time a file is uploaded to process and store new video files in a different bucket. Using CloudWatch Events, trigger an SES job to send an email to the customer containing the link to the processed file.
D. Rewrite the web application to run from Amazon S3 and upload the video files to an S3 bucket. Each time a new file is uploaded, trigger an AWS Lambda function to put a message in an SQS queue containing the link and the instructions. Modify the video processing application to read from the SQS queue and the S3 bucket. Use the queue depth metric to adjust the size of the Auto Scaling group for video processing instances.
Answer: B

NEW QUESTION: 2
You design an Azure application that processes images. The maximum size of an image is 10 MB. The application includes a web role that allows users to upload images and a worker role with multiple instances that processes the images. The web role communicates with the worker role by using an Azure Queue service.
You need to recommend an approach for storing images that minimizes storage transactions.
What should you recommend?
A. Store images in Azure Blob service. Store references to the images in the queue.
B. Store images in the queue.
C. Store images in OneDrive attached to the worker role instances. Store references to the images in the queue.
D. Store images in local storage on the web role instance. Store references to the images in the queue.
Answer: A
Explanation:
Azure Queues provide a uniform and consistent programming model across queues, tables, and BLOBs - both for developers and for operations teams.
Microsoft Azure blob storage can be used to store the image data, the application can use a worker role in Azure to perform background processing tasks on the images, how the application may use shared access signatures to control access to the images by users.
Azure blobs provide a series of containers aimed at storing text or binary data. Block blob containers are ideal for streaming data, while page blob containers can be used for random read/write operations.
References: https://msdn.microsoft.com/en-gb/library/ff803365.aspx
https://msdn.microsoft.com/en-us/library/azure/hh767287.aspx

NEW QUESTION: 3
AWS Elastic Beanstalkアプリケーションを使用してウェブアプリケーションがデプロイされましたアプリケーション開発者は、アプリケーションの2つの異なる領域でレイテンシが高くなっていることを懸念しています。
-サードパーティAPIへのHTTPクライアント要求
-Amazon RDSデータベースへのMySQLクライアントライブラリクエリ
-DevOpsエンジニアは、問題を診断するためにトレースデータを収集する必要があります。
アプリケーションに対する変更とパフォーマンスへの影響が最も少ないトレース情報を収集する手順はどれですか。
A. アプリケーションのAWS Elastic Beanstalk管理ページで、AWS X-Rayデーモンを有効にします。
X-Rayコンソールでトレースデータを表示します。
B. アプリケーションコードにログを追加します。 Amazon CloudWatchエージェントを使用して、アプリケーションログをAmazon Elasticsearch Serviceにストリーミングします。 Amazon ESでログデータをクエリします。
C. AWS X-Ray SDKを使用してアプリケーションを計測します。アプリケーションのAWS Elastic Beanstalk管理ページで、X-Rayデーモンを有効にします。 X-Rayコンソールでトレースデータを表示します。
D. AWS X-Ray SDKを使用するようにアプリケーションをインストルメントします。トレースデータをAmazon Elasticsearch Serviceクラスターに送信します。 HTTPクライアントとMySQLクライアントへの呼び出しのトレースデータをクエリします。
Answer: C

NEW QUESTION: 4
Was müssen Sie beachten, wenn Sie Stücklisten in einem Kundenauftrag verwenden möchten? (Wähle zwei)
A. Die Verkaufsbelegart steuert, ob verkaufsrelevante Stücklisten im Verkaufsbeleg aufgelöst werden sollen oder nicht.
B. Stücklisten werden im Verkaufsbeleg als Hauptpositionen und Unterpositionen aufgelöst, basierend auf der Konfiguration des Hauptpositionstyps.
C. Die Stückliste muss durch Auswahl der Stücklistenverwendung "Vertrieb" erstellt werden.
D. Die Tiefe der Auflösung von Stücklisten im Verkaufsbeleg wird durch Angabe der Auflösungsebene im Stammsatz für die Stückliste gesteuert.
Answer: B,C