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| Certification Vendor: | Amazon AWS |
|---|---|
| Exam Name: | AWS Certified Developer - Associate |
| Exam Number: | DVA-C02 |
| Real Exam Qty: | 65 (50 scored, 15 unscored) |
| Related Certifications: | AWS Certified SysOps Administrator - Associate AWS Certified Solutions Architect - Associate |
| Passing Score: | 720 (scaled score 100–1000) |
| Certificate Validity Period: | 3 years |
| Exam Price: | 150 USD |
| Exam Duration: | 130 minutes |
| Exam Format: | Multiple-response, Multiple-choice |
| Available Languages: | Japanese, English, Simplified Chinese, Portuguese (Brazil), Korean, Spanish (Latin America) |
| Recommended Training: | AWS Skill Builder AWS Certified Developer - Associate Exam Prep |
| Exam Registration: | AWS Certification Registration Pearson VUE Registration |
| Sample Questions: | Amazon DVA-C02 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE testing centers |
| Pre Condition: | Recommended: 1+ year of hands-on experience developing applications on AWS, familiarity with AWS core services, basic understanding of cloud architecture |
| Official Syllabus URL: | https://docs.aws.amazon.com/aws-certification/latest/developer-associate-02/developer-associate-02.html |
他の同様の教育プラットフォームとは異なり、DVA-C02クイズガイドは、分類なしのランダムな蓄積ではなく、マルチプレート配布用の資料を割り当てます。 DVA-C02準備トレントは、さまざまな文化レベルのユーザーにより適したDVA-C02テスト資料を開発するために、従来の学習プラットフォームの利点に吸収され、その欠点を認識しています。そして、DVA-C02試験材料は、プレートの多くの研究部分がユーザーの熱意を喚起するのに十分であり、ユーザーが集中力を維持できるようにします。
Amazon DVA-C02（AWS Certified Developer - Associate）試験は、Amazon Web Services（AWS）プラットフォーム上でアプリケーションを開発および展開する専門知識を証明したい個人向けに設計された認定試験です。この認定は、Python、Java、およびRubyなどのプログラミング言語の経験を持ち、AWSサービスを使用してアプリケーションを構築、展開、および管理することを目指す開発者に最適です。
DVA-C02試験は、AWSベースのアプリケーションの開発と維持に最低1年の経験を持つ開発者向けに設計されています。候補者は、Python、Java、C＃など、少なくとも1つのプログラミング言語を十分に理解する必要があります。また、AWS Elastic BeanStalk、AWS CloudFormation、AWS CodeCommit、AWS CodePipeline、AWS CodeBuildなどのAWSサービスの使用の経験も必要です。
質問 # 499
An organization is using Amazon CloudFront to ensure that its users experience low-latency access to its web application. The organization has identified a need to encrypt all traffic between users and CloudFront, and all traffic between CloudFront and the web application.
How can these requirements be met? (Choose two.)
正解：A、C
解説：
B: Setting the Origin Protocol Policy to "HTTPS Only" ensures that CloudFront always uses HTTPS to connect to the origin, which is the web application in this scenario.
D: Setting the Viewer Protocol Policy to "HTTPS Only" ensures that CloudFront will only serve requests over HTTPS. Setting it to "Redirect HTTP to HTTPS" ensures that any HTTP request from viewers is redirected to HTTPS.
質問 # 500
A company has a web application that runs on Amazon EC2 instances with a custom Amazon Machine Image (AMI) The company uses AWS CloudFormation to provision the application The application runs in the us- east-1 Region, and the company needs to deploy the application to the us-west-1 Region An attempt to create the AWS CloudFormation stack in us-west-1 fails. An error message states that the AMI ID does not exist. A developer must resolve this error with a solution that uses the least amount of operational overhead Which solution meets these requirements?
正解：D
解説：
* Problem:CloudFormation can't find the custom AMI in the target region (us-west-1) because AMIs are region-specific.
* Copying AMIs:
* AMIs can be copied across regions, maintaining their configuration.
* This approach minimizes operational overhead as the existing CloudFormation template can be reused with a minor update.
* Updating the Template:
* Modify the CloudFormation template in us-west-1 to reference the newly copied AMI's ID in that region.
質問 # 501
An ecommerce company is developing a serverless application to track user activities. The company needs to track each type of activity with a timestamp and a unique product ID. The company also must track actions that are associated with each activity, such as product views, shopping cart actions, purchases, and checkout processes.
The company is planning a marketing campaign based on each user's activity. A developer needs to implement a partitioning strategy for an Amazon DynamoDB table to meet the data storage and access requirements for the application. The strategy must maximize provisioned throughput efficiency while minimizing the risk of throttling.
Which solution will meet these requirements?
正解：D
解説：
For this workload, the access pattern is centered on each user's activity history over time (the company is planning a marketing campaign based on each user's activity). In DynamoDB, the most effective way to store and query time-ordered events per entity is to use a composite primary key where the entity identifier is the partition key and a time attribute is the sort key. Therefore, using user ID as the partition key groups all events for a given user together, and using timestamp as the sort key allows efficient retrieval in chronological order and supports range queries (for example, "activities in the last 7 days" or "between two dates").
This design also helps maximize provisioned throughput efficiency and reduce throttling risk because it distributes data across partitions based on the partition key values (user IDs). With many users, writes and reads naturally spread across multiple partition key values rather than concentrating on a small set. The sort key further enables multiple activity records per user without overwriting items and supports precise queries without scanning.
Option B (product ID as partition key) does not align with the stated marketing need (per-user activity). It would cluster all users' actions for a popular product into the same partition key, increasing the chance of hot partitions and throttling. Option C also risks hot partitions for popular product IDs; auto scaling helps capacity management but does not fix poor key distribution or hot-key access patterns. Option D (monotonic counter as partition key) is particularly problematic: sequential keys can create uneven distribution and a throughput bottleneck pattern, and it does not support user-centric queries efficiently.
Thus, A best matches the data model (user events over time), supports efficient queries, and reduces throttling risk by distributing workload across user IDs.
質問 # 502
A developer is modifying a large-scale IoT application that stores device telemetry data in an Amazon DynamoDB table. The telemetry data is valuable only for a limited time, but the application stores the data indefinitely. Data storage is slowing the application down. The developer needs a solution to improve the performance of the application.
Which solution will meet this requirement in the MOST operationally efficient way?
正解：B
解説：
The most operationally efficient way to remove time-bound data from a DynamoDB table is to use Time to Live (TTL). TTL is a DynamoDB feature that lets you define an attribute (typically a Unix epoch timestamp) that represents an item's expiration time. After the timestamp has passed, DynamoDB automatically marks the item as expired and later deletes it in the background. This directly satisfies the requirement because the telemetry is only valuable for a limited time, yet it is currently stored indefinitely.
Enabling TTL (option C) improves performance and operational efficiency by preventing the table from growing without bounds. As the item count grows, access patterns that rely on scans, large partitions, or indexes can degrade, and storage-related overhead increases. TTL helps keep the dataset "fresh" by automatically removing stale telemetry, reducing the amount of data the application must work around and decreasing overall storage footprint.
Option A is operationally heavier: scanning and deleting items with a scheduled Lambda introduces ongoing maintenance, costs, and risk of throttling (table scans can be expensive and disruptive). It also requires custom logic, error handling, and retries. Option B addresses cost optimization for archived data but does not fix the DynamoDB table size or the performance degradation caused by keeping old data in the table; archiving is useful, but you still need an efficient deletion mechanism from DynamoDB. Option D (on-demand capacity mode) changes how capacity is managed, not how much data is stored; it does not remove stale items and therefore does not address the core problem.
Therefore, the best and most operationally efficient solution is C: add a TTL attribute to each telemetry item and enable TTL on the DynamoDB table so DynamoDB automatically expires and deletes old telemetry.
質問 # 503
A company's developer has deployed an application in AWS by using AWS CloudFormation. The CloudFormation stack includes parameters in AWS Systems Manager Parameter Store that the application uses as configuration settings. The application can modify the parameter values.
When the developer updated the stack to create additional resources with tags, the developer noted that the parameter values were reset and that the values ignored the latest changes made by the application. The developer needs to change the way the company deploys the CloudFormation stack. The developer also needs to avoid resetting the parameter values outside the stack.
Which solution will meet these requirements with the LEAST development effort?
正解：C
解説：
The issue occurs because the SSM Parameter Store parameters are managed by CloudFormation as stack resources. When CloudFormation performs a stack update, it will attempt to ensure the deployed resources match the template. If the template includes a parameter value, CloudFormation can overwrite the current value during updates, which explains why the application's runtime modifications are lost.
The developer's requirement is to continue deploying the stack (including adding resources/tags) without resetting parameter values that are modified outside CloudFormation. The lowest-effort way to do this is to prevent CloudFormation from updating those specific Parameter Store resources during stack updates.
A CloudFormation stack policy can explicitly deny update actions on selected resources (in this case, the SSM parameters). Stack policies are designed to protect critical resources from being unintentionally modified during stack updates. With an update-deny policy applied to the SSM parameter resources, CloudFormation can still update other resources (such as adding tags or creating new components), but it will not overwrite the parameter values that the application has changed.
Option A (DeletionPolicy: Retain) only affects what happens when a resource is deleted or replaced, not whether CloudFormation updates the resource in place. It will not reliably prevent stack updates from resetting values.
Options B and C are larger architecture changes and require migrating configuration storage to DynamoDB or RDS-much more development effort and operational overhead.
Therefore, applying a stack policy to deny updates on Parameter Store parameters is the best and least-effort solution.
質問 # 504
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DVA-C02テスト内容: https://www.topexam.jp/DVA-C02_shiken.html
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