さらに、Japancert DVA-C02ダンプの一部が現在無料で提供されています：https://drive.google.com/open?id=1cck1KNSQ_O2zP6ub_Y8KTuXIpqiDQK1m
何事でもはじめが一番難しいです。AmazonのDVA-C02試験への復習に悩んでいますか。弊社の試験のためのソフトを買うのはあなたの必要の第一歩です。弊社の提供したのはあなたがほしいのだけではなく、試験のためにあなたの必要があるのです。あなたは決められないかもしれませんが、AmazonのDVA-C02のデモをダウンロードしてください。やってみて第一歩を進める勇気があります。
| Section | Weight | Objectives |
|---|---|---|
| Development with AWS Services | 32% | - Application development and integration
|
| Deployment | 24% | - Infrastructure as code
|
| Troubleshooting and Optimization | 18% | - Monitoring and logging
|
| Security | 26% | - Application authentication and authorization
|
Amazon DVA-C02資格認定はバッジのような存在で、あなたの所有する専業技術と能力を上司に直ちに知られさせます。次のジョブプロモーション、プロジェクタとチャンスを申し込むとき、Amazon DVA-C02資格認定はライバルに先立つのを助け、あなたの大業を成し遂げられます。
質問 # 512
A company has a web application in an Amazon ECS cluster running hundreds of secure services in AWS Fargate containers. The services are in target groups routed by an Application Load Balancer (ALB). Application users log in to the website anonymously, but they must be authenticated using any OpenID Connect protocol-compatible identity provider (IdP) to access the secure services. Which authentication approach would meet these requirements with the LEAST amount of effort?
正解：C
解説：
Configuring the Application Load Balancer (ALB) to use Amazon Cognito for authentication allows the ALB to handle user authentication via any OpenID Connect-compatible IdP before forwarding requests to the backend services. This approach requires the least effort since it centralizes authentication at the ALB without changing individual services.
質問 # 513
A company runs an application on AWS The application uses an AWS Lambda function that is configured with an Amazon Simple Queue Service (Amazon SQS) queue called high priority queue as the event source A developer is updating the Lambda function with another SQS queue called low priority queue as the event source The Lambda function must always read up to 10 simultaneous messages from the high priority queue before processing messages from low priority queue. The Lambda function must be limited to 100 simultaneous invocations.
Which solution will meet these requirements'?
正解：C
解説：
* Lambda Concurrency: The 'maximum concurrency' setting in event source mappings controls the maximum number of simultaneous invocations Lambda allows for that specific source.
* Prioritizing Queues: Setting a lower maximum concurrency for the 'high priority queue' ensures it's processed first while allowing more concurrent invocations from the 'low priority queue'.
* Batching: Batch size settings affect the number of messages Lambda retrieves from a queue per invocation, which is less relevant to the prioritization requirement.
References:
* Lambda Event Source Mappings: https://docs.aws.amazon.com/lambda/latest/dg/invocation- eventsourcemapping.html
* Lambda Concurrency: https://docs.aws.amazon.com/lambda/latest/dg/configuration-concurrency.html
質問 # 514
An ecommerce company is planning to migrate an on-premises Microsoft SQL Server database to the AWS Cloud. The company needs to migrate the database to SQL Server Always On availability groups. The cloud- based solution must be highly available.
Which solution will meet these requirements?
正解：D
解説：
* Why Option C is Correct:SQL Server Always On availability groups require a shared storage solution. Amazon FSx for Windows File Server provides the shared storage necessary to implement Always On availability groups in a highly available configuration.
* Why Other Options are Incorrect:
* Option A: A single EBS volume cannot provide shared storage for Always On availability groups.
* Option B: RDS does not support SQL Server Always On availability groups.
* Option D: S3 is not a suitable storage tier for SQL Server database operations.
* AWS Documentation References:
* Amazon FSx for Windows File Server
質問 # 515
A company has a two-tier application that consists of a frontend application and an Amazon RDS for MySQL database. The frontend application retrieves data from the database. The data consists of postal codes and their associated geographic coordinates. The application performs many more database reads than writes. The application retrieves each postal code from the database thousands of times each day.
A developer must improve the performance of the application to decrease latency.
Which change should the developer make to the application to meet these requirements?
正解：C
解説：
This workload is overwhelmingly read-heavy and repeatedly queries the same relatively static reference data (postal codes mapped to coordinates). The best way to reduce latency and offload Amazon RDS is to introduce an application-side cache using a lazy loading (cache-aside) pattern and choose a TTL that reflects how often the underlying data changes.
With lazy loading, the application first checks the cache for the postal code. If the value is present (a cache hit), the application returns the coordinates immediately with low latency and without querying the database.
If the value is absent (a cache miss), the application reads from RDS, returns the result, and then populates the cache for subsequent requests. This pattern is operationally simple and widely used because the application controls what is cached and when.
A large TTL is appropriate here because postal-code-to-coordinate mappings typically do not change frequently. A longer TTL maximizes cache hit ratio, which is critical because each postal code is requested thousands of times per day. High cache hit rates reduce database read load, decrease query contention, and substantially improve response times. In contrast, a small TTL would cause frequent expirations and repeated database lookups, reducing the performance benefit and increasing database load.
Write-through and write-behind caching (options C and B) are designed to coordinate caching with writes.
They are useful when write consistency and write performance are central concerns. Here, writes are rare; the performance issue is repeated reads. Write-behind can also introduce consistency delays, which is unnecessary for this scenario.
Therefore, the best change is D: implement a lazy loading (cache-aside) caching strategy with a large TTL to keep hot, rarely changing postal code lookups in cache and dramatically reduce read latency and database load.
質問 # 516
A developer needs to perform geographic load testing of an API. The developer must deploy resources to multiple AWS Regions to support the load testing of the API.
How can the developer meet these requirements without additional application code?
正解：C
解説：
AWS CloudFormation is a service that allows developers to model and provision AWS resources using templates. A CloudFormation template can define the load test resources, such as EC2 instances, load balancers, and Auto Scaling groups. A CloudFormation stack set is a collection of stacks that can be created and managed from a single template in multiple Regions and accounts. The AWS CLI create-stack-set command can be used to create a stack set from a template and specify the Regions where the stacks should be created. Reference: Working with AWS CloudFormation stack sets
質問 # 517
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DVA-C02テスト内容: https://www.japancert.com/DVA-C02.html
ちなみに、Japancert DVA-C02の一部をクラウドストレージからダウンロードできます：https://drive.google.com/open?id=1cck1KNSQ_O2zP6ub_Y8KTuXIpqiDQK1m