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Pass Guaranteed 2026 High Pass-Rate DVA-C02: AWS Certified Developer - Associate Reliable Dumps Pdf

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Amazon AWS Certified Developer - Associate Sample Questions (Q368-Q373):

NEW QUESTION # 368
A company has an application that is based on Amazon EC2. The company provides API access to the application through Amazon API Gateway and uses Amazon DynamoDB to store the application's data. A developer is investigating performance issues that are affecting the application. During peak usage, the application is overwhelmed by a large number of identical data read requests that come through APIs. What is the MOST operationally efficient way for the developer to improve the application's performance?

A. Configure Amazon EC2 Auto Scaling policies to meet fluctuating demand.
B. Enable API Gateway caching to cache API responses.
C. Use Amazon ElastiCache to cache application responses.
D. Use DynamoDB Accelerator (DAX) to cache database responses.

Answer: D

Explanation:
DynamoDB Accelerator (DAX) provides a managed caching layer specifically optimized for DynamoDB, reducing latency for repeated read requests.
Purpose-Built: DAX is designed for DynamoDB, enabling sub-millisecond response times for frequently accessed items.
Operational Efficiency: No need for additional application-level caching logic.

NEW QUESTION # 369
A developer used the AWS SDK to create an application that aggregates and produces log records for
10 services. The application delivers data to an Amazon Kinesis Data Streams stream.
Each record contains a log message with a service name, creation timestamp, and other log information. The stream has 15 shards in provisioned capacity mode. The stream uses service name as the partition key.
The developer notices that when all the services are producing logs,
ProvisionedThroughputExceededException errors occur during PutRecord requests. The stream metrics show that the write capacity the applications use is below the provisioned capacity.

A. Double the number of shards until the throttling errors stop occurring.
B. Change the partition key from service name to creation timestamp.
C. Change the capacity mode from provisioned to on-demand.
D. Use a separate Kinesis stream for each service to generate the logs.

Answer: B

Explanation:
Comprehensive and Detailed Step-by-Step Explanation:
* Issue Analysis:
* The stream uses service name as the partition key. This can cause "hot partition" issues when a few service names generate significantly more logs compared to others, causing uneven distribution of data across shards.
* Metrics show that the write capacity used is below provisioned capacity, which confirms that the throughput errors are due to shard-level limits and not overall capacity.
* Option C: Change Partition Key to Creation Timestamp:
* By changing the partition key to the creation timestamp (or a composite key including timestamp), the distribution of data across shards can be randomized, ensuring an even spread of records.
* This resolves the shard overutilization issue and eliminates
ProvisionedThroughputExceededException.
* Why Other Options Are Incorrect:
* Option A:Switching to on-demand capacity mode might temporarily alleviate the issue, but the root cause (hot partitioning) remains unresolved.
* Option B:Adding shards increases capacity but does not fix the skewed data distribution caused by using the service name as the partition key.
* Option D:Creating separate streams for each service adds unnecessary complexity and does not scale well as the number of services grows.

NEW QUESTION # 370
A company's website runs on an Amazon EC2 instance and uses Auto Scaling to scale the environment during peak times. Website users across the world ate experiencing high latency flue lo sialic content on theEC2 instance. even during non-peak hours.
When companion of steps mill resolves the latency issue? (Select TWO)

A. Host the application code on AWS lambda
B. Create an Amazon Cloudfront distribution to cache the static content
C. Double the Auto Scaling group's maximum number of servers
D. Store the application's sialic content in Amazon S3
E. Scale vertically by resizing the EC2 instances

Answer: B,D

Explanation:
Explanation
The combination of steps that will resolve the latency issue is to create an Amazon CloudFront distribution to cache the static content and store the application's static content in Amazon S3. This way, the company can use CloudFront to deliver the static content from edge locations that are closer to the website users, reducing latency and improving performance. The company can also use S3 to store the static content reliably and cost-effectively, and integrate it with CloudFront easily. The other options either do not address the latency issue, or are not necessary or feasible for the given scenario.

NEW QUESTION # 371
An application is processing clickstream data using Amazon Kinesis. The clickstream data feed into Kinesis experiences periodic spikes. The PutRecords API call occasionally fails and the logs show that the failed call returns the response shown below:

Which techniques will help mitigate this exception? (Choose two.)

A. Reduce the frequency and/or size of the requests.
B. Use a PutRecord API instead of PutRecords.
C. Reduce the number of KCL consumers.
D. Use Amazon SNS instead of Kinesis.
E. Implement retries with exponential backoff.

Answer: A,E

Explanation:
The response from the API call indicates that the ProvisionedThroughputExceededException exception has occurred. This exception means that the rate of incoming requests exceeds the throughput limit for one or more shards in a stream. To mitigate this exception, the developer can use one or more of the following techniques:
Implement retries with exponential backoff. This will introduce randomness in the retry intervals and avoid overwhelming the shards with retries.
Reduce the frequency and/or size of the requests. This will reduce the load on the shards and avoid throttling errors.
Increase the number of shards in the stream. This will increase the throughput capacity of the stream and accommodate higher request rates.
Use a PutRecord API instead of PutRecords. This will reduce the number of records per request and avoid exceeding the payload limit.
Reference:
[ProvisionedThroughputExceededException - Amazon Kinesis Data Streams Service API Reference]
[Best Practices for Handling Kinesis Data Streams Errors]

NEW QUESTION # 372
A company has a website that is developed in PHP and is launched using AWS Elastic Beanstalk. There is a new version of the website that needs to be deployed in the Elastic Beanstalk environment. The company cannot tolerate having the website offline if an update fails. Deployments must have minimal impact and rollback as soon as possible.

A. Rolling
B. Immutable
C. All at once
D. Snapshots

Answer: B

Explanation:
The Immutable deployment method is the best choice when a company requires minimal downtime and automatic rollback in case of a failure. Here's why:
* In Immutable deployments, a new set of instances is launched with the updated version. These instances are tested and validated before they replace the old instances. This ensures zero downtime and immediate rollback if the deployment fails.
* All at once (A) causes downtime because the update replaces all instances simultaneously.
* Rolling deployments (B) update a few instances at a time, but if a failure occurs midway, downtime or partial unavailability can happen.
* Snapshots (C) are not a deployment strategy in Elastic Beanstalk.

NEW QUESTION # 373
......

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