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NEW QUESTION: 1
計画段階で、プロジェクトマネージャーはプロジェクトチームと会って、タスクチームを決定し、タスクとその関係を決定します。
プロジェクトマネージャーは、チームメンバーから次のうちどれを受け取る必要がありますか？ （2つ選択してください。）
A. ベースライン
B. 期間
C. リソース
D. 依存関係
E. 開始/終了日
Answer: B,D
NEW QUESTION: 2
An RSA key pair consists of a public key and a private key and is used to set up PKI.
Which statement applies to RSA and PKI?
A. The public key must be included in the certificate enrollment request.
B. When a router that does not have an RSA key pair requests a certificate, the certificate request is sent, but a warning is shown to generate the RSA key pair before a CA signed certificate is received.
C. The RSA key-pair is a symmetric cryptography.
D. It is possible to determine the RSA key-pair private key from its corresponding public key.
Answer: A
Explanation:
An RSA key pair consists of a public key and a private key. When setting up your PKI, you must include the public key in the certificate enrollment request. After the certificate has been granted, the public key will be included in the certificate so that peers can use it to encrypt data that is sent to the router. The private key is kept on the router and used both to decrypt the data sent by peers and to digitally sign transactions when negotiating with peers.
Reference: http://www.cisco.com/c/en/us/td/docs/iosxml/ios/sec_conn_pki/configuration/xe-3s/sec-pki-xe-3s-book/sec-pki-overview.html
NEW QUESTION: 3
A Solutions Architect is responsible for redesigning a legacy Java application to improve its availability, data durability, and scalability. Currently, the application runs on a single high-memory Amazon EC2 instance. It accepts HTTP requests from upstream clients, adds them to an in-memory queue, and responds with a 200 status. A separate application thread reads items from the queue, processes them, and persists the results to an Amazon RDS MySQL instance. The processing time for each item takes 90 seconds on average., most of which is spent waiting on external service calls, but the application is written to process multiple items in parallel.
Traffic to this service is unpredictable. During periods of high load, items may sit in the internal queue for over an hour while the application processes the backing. In addition, the current system has issues with availability and data if the single application node fails.
Clients that access this service cannot be modified. They expect to receive a response to each HTTP request they send within 10 seconds before they will time out and retry the request.
Which approach would improve the availability and durability of the system while decreasing the processing latency and minimizing costs?
A. Create an Amazon API Gateway REST API that uses Lambda proxy integration to pass requests to an AWS Lambda function. Migrate the core processing code to a Lambda function and write a wrapper class that provides a handler method that converts the proxy events to the internal application data model and invokes the processing module.
B. Create an Amazon API Gateway REST API that uses a service proxy to put items in an Amazon SQS queue. Extract the core processing code from the existing application and update it to pull items from Amazon SQS queue. Extract the core processing code from the existing application and update it to pull items from Amazon SQS instead of an in-memory queue. Deploy the new processing application to smaller EC2 instances within an Auto Scaling group that scales dynamically based on the approximate number of messages in the Amazon SQS queue.
C. Update the application to use a Redis task queue instead of the in-memory queue. Build a Docker container image for the application. Create an Amazon ECS task definition that includes the application container and a separate container to host Redis. Deploy the new task definition as an ECS service using AWS Fargate and enable Auto Scaling.
D. Modify the application to use Amazon DynamoDB instead of Amazon RDS. Configure Auto Scaling for the DynamoDB table. Deploy the application within an Auto Scaling group with a scaling policy based on CPU utilization. Back the in-memory queue with a memory-mapped file to an instance store volume and periodically write that file to Amazon S3.
Answer: D