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NEW QUESTION: 1





A. Option A
B. Option B
C. Option C
D. Option D
Answer: B
Explanation:
Explanation
We create a now div element with the textbox.
We then use appendChild() method appends this node as the last child the input node divname.
Reference: HTML DOM appendChild() Method

NEW QUESTION: 2
ソリューションアーキテクトがAWSにデプロイされる新しいアプリケーションのクラウドアーキテクチャを設計しているプロセスは、処理するジョブの数に基づいて、必要に応じてアプリケーションノードを追加および削除しながら並行して実行する必要がありますプロセッサーアプリケーションはステートレスですソリューションアーキテクトは、アプリケーションは疎結合であり、ジョブアイテムは永続的に保存されます。ソリューションアーキテクトはどの設計を使用する必要がありますか？
A. 処理が必要なジョブを送信するためのAmazon SNSトピックを作成しますプロセッサーアプリケーションで構成されるAmazonマシンイメージ（AMI）を作成しますAMIを使用する起動構成を作成します起動構成セットを使用してAuto Scalingグループを作成しますCPU使用率に基づいてノードを追加および削除するAuto Scalingグループのスケーリングポリシー
B. 処理が必要なジョブを送信するためのAmazon SNSトピックを作成しますプロセッサーアプリケーションで構成されるAmazonマシンイメージ（AMI）を作成しますAMIを使用する起動テンプレートを作成します起動テンプレートセットを使用してAuto Scalingグループを作成しますSNSトピックにパブリッシュされたメッセージの数に基づいてノードを追加および削除するAuto Scalingグループのスケーリングポリシー。
C. 処理が必要なジョブを保持するAmazon SQSキューを作成します。プロセッサーアプリケーションで構成されるAmazonマシンイメージ（AMI）を作成します。AMIを使用する起動テンプレートを作成します。起動テンプレートを使用してAuto Scalingグループを作成します。 SQSキュー内のアイテム数に基づいてノードを追加および削除するAuto Scalingグループのスケーリングポリシー
D. 処理が必要なジョブを保持するAmazon SQSキューを作成しますプロセッサーアプリケーションで構成されるAmazonマシンイメージ（AMI）を作成しますAMIを使用する起動構成を作成します起動構成セットを使用してAuto Scalingグループを作成しますネットワークの使用状況に基づいてノードを追加および削除するAuto Scalingグループのスケーリングポリシー
Answer: C
Explanation:
Explanation
Amazon Simple Queue Service
Amazon Simple Queue Service (SQS) is a fully managed message queuing service that enables you to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates the complexity and overhead associated with managing and operating message oriented middleware, and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available. Get started with SQS in minutes using the AWS console, Command Line Interface or SDK of your choice, and three simple commands.
SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are processed exactly once, in the exact order that they are sent.
Scaling Based on Amazon SQS
There are some scenarios where you might think about scaling in response to activity in an Amazon SQS queue. For example, suppose that you have a web app that lets users upload images and use them online. In this scenario, each image requires resizing and encoding before it can be published. The app runs on EC2 instances in an Auto Scaling group, and it's configured to handle your typical upload rates. Unhealthy instances are terminated and replaced to maintain current instance levels at all times. The app places the raw bitmap data of the images in an SQS queue for processing. It processes the images and then publishes the processed images where they can be viewed by users. The architecture for this scenario works well if the number of image uploads doesn't vary over time. But if the number of uploads changes over time, you might consider using dynamic scaling to scale the capacity of your Auto Scaling group.
https://aws.amazon.com/sqs/#:~:text=Amazon%20SQS%20leverages%20the%20AWS,queues%20provide%20n
https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html

NEW QUESTION: 3

A. Azure Table storage
B. Service Bus queue
C. Azure Queue storage
D. Service Management API
Answer: B
Explanation:
The cost of ACS transactions is insignificant when performing messaging operations against Service Bus queues. Service Bus acquires one ACS token per a single instance of the messaging factory object. The token is then reused until it expires, after about 20 minutes. Therefore, the volume of messaging operations in Service Bus is not directly proportional to the amount of ACS transactions required to support these operations.
References: https://msdn.microsoft.com/library/azure/hh767287.aspx
Topic 8, Woodgrove Bank
Background
Overview
Woodgrove Bank has 20 regional offices and operates 1,500 branch office locations. Each regional office hosts the servers, infrastructure, and applications that support that region.
Woodgrove Bank plans to move all of their on-premises resources to Azure, including virtual machine (VM)-based, line-of-business workloads, and SQL databases. You are the owner of the Azure subscription that Woodgrove Bank is using. Your team is using Git repositories hosted on GitHub for source control.
Security
Currently, Woodgrove Bank's Computer Security Incident Response Team (CSIRT) has a problem investigating security issues due to the lack of security intelligence integrated with their current incident response tools. This lack of integration introduces a problem during the detection (too many false positives), assessment, and diagnose stages. You decide to use Azure Security Center to help address this problem.
Woodgrove Bank has several apps with regulated data such as Personally Identifiable Information (PII) that require a higher level of security. All apps are currently secured by using an on-premises Active Directory Domain Services (ADDS). The company depends on the following mission-critical apps: WGBLoanMaster, WGBLeaseLeader, and WGBCreditCruncher apps. You plan to move each of these apps to Azure as part of an app migration project.
Apps
The WGBLoanMaster app has been audited for transaction loss. Many transactions have been lost in processing and monetary write-offs have cost the bank. The app runs on two VMs that include several public endpoints.
The WGBLeaseLeader app has been audited for several data breaches. The app includes a SQL Server database and a web-based portal. The portal uses an ASP.NET Web API function to generate a monthly aggregate report from the database.
The WGBCreditCruncher app runs on a VM and is load balanced at the network level. The app includes several stateless components and must accommodate scaling of increased credit processing. The app runs on a nightly basis to process credit transactions that are batched during the day. The app includes a web-based portal where customers can check their credit information. A mobile version of the app allows users to upload check images.
Business Requirements
WGBLoanMaster app
The app audit revealed a need for zero transaction loss. The business is losing money due to the app losing and not processing loan information. In addition, transactions fail to process after running for a long time. The business has requested the aggregation processing to be scheduled for 01:00 to prevent system slowdown.
WGBLeaseLeader app
The app should be secured to stop data breaches. If the data is breached, it must not be readable. The app is continuing to see increased volume and the business does not want the issues presented in the WGBLoanMaster app. Transaction loss is unacceptable, and although the lease monetary amounts are smaller than loans, they are still an important profit center for Woodgrove Bank. The business would also like the monthly report to be automatically generated on the first of the month. Currently, a user must log in to the portal and click a button to generate the report.
WGBCreditCruncher app
The web-based portal area of the app must allow users to sign in with their Facebook credentials. The bank would like to allow this feature to enable more users to check their credit within the app.
Woodgrove Bank needs to develop a new financial risk modeling feature that they can include in the WGBCreditCruncher app. The financial risk modeling feature has not been developed due to costs associated with processing, transforming, and analyzing the large volumes of data that are collected. You need to find a way to implement parallel processing to ensure that the features run efficiently, reliably, and quickly. The feature must scale based on computing demand to process the large volumes of data and output several financial risk models.
Technical Requirements
WGBLoanMaster app
The app uses several compute-intensive tasks that create long-running requests to the system.
The app is critical to the business and must be scalable to increased loan processing demands.
The VMs that run the app include a Windows Task Scheduler task that aggregates loan information from the app to send to a third party. This task runs a console app on the VM.
The app requires a messaging system to handle transaction processing. The messaging system must meet the following requirements:
* Allow messages to reside in the queue for up to a month.
* Be able to publish and consume batches of messages.
* Allow full integration with the Windows Communication Foundation (WCF) communication stack.
* Provide a role-based access model to the queues, including different permissions for senders and receivers.
You develop an Azure Resource Manager (ARM) template to deploy the VMs used to support the app. The template must be deployed to a new resource group and you must validate your deployment settings before creating actual resources.
WGBLeaseLeader app
The app must use Azure SQL Databases as a replacement to the current Microsoft SQL Server environment. The monthly report must be automatically generated.
The app requires a messaging system to handle transaction processing. The messaging system must meet the following requirements:
* Require server-side logs of all of the transactions run against your queues.
* Track progress of a message within the queue.
* Process the messages within 7 days.
* Provide a differing timeout value per message.
WGBCreditCruncher app
The app must:
* Secure inbound and outbound traffic.
* Analyze inbound network traffic for vulnerabilities.
* Use an instance-level public IP and allow web traffic on port 443 only.
* Upgrade the portal to a Single Page Application (SPA) that uses JavaScript, Azure Active Directory (Azure AD), and the OAuth 2.0 implicit authorization grant to secure the Web API back end.
* Cache authentication and host the Web API back end using the Open Web Interface for .NET (OWIN) middleware.
* Immediately compress check images received from the mobile web app.
* Schedule processing of the batched credit transactions on a nightly basis.
* Provide parallel processing and scalable computing resources to output financial risk models.
* Use simultaneous computer nodes to enable high performance computing and updating of the financial risk models.
Key security area