DVA-C02 Exam Dumps - AWS Certified Developer - Associate

This solution will meet the requirements by using Amazon RDS Proxy, which is a fully managed, highly available database proxy for Amazon RDS that makes applications more scalable, more resilient to database failures, and more secure. The developer can create a proxy in Amazon RDS Proxy, which sits between the application and the DB instance and handles connection management, pooling, and routing. The developer can query the proxy instead of the DB instance, which reduces the number of open connections to the DB instance and avoids errors for too many connections. Option A is not optimal because it will create a read replica for the DB instance, which may not solve the problem of too many connections as read replicas also have connection limits and may incur additional costs. Option B is not optimal because it will migrate the data to an Amazon DynamoDB database, which may introduce additional complexity and overhead for migrating and accessing data from a different database service. Option C is not optimal because it will configure the Amazon Aurora MySQL DB instance for Multi-AZ deployment, which may improve availability and durability of the DB instance but not reduce the number of connections.

References: [Amazon RDS Proxy], [Working with Amazon RDS Proxy]

AWS X-Ray SDK: The primary way to enable X-Ray tracing within applications. The SDK sends data about requests and subsegments to the X-Ray daemon for service map generation.

Instrumenting All Services: To visualize a complete microservice architecture on the service map, each relevant service must include the X-Ray SDK.

References:

AWS X-Ray Documentation: https://docs.aws.amazon.com/xray/

X-Ray SDK for Python: https://docs.aws.amazon.com/xray/latest/devguide/xray-sdk-python.html

Understand the Problem: The existing DynamoDB table has email_address as the partition key. Searching by customer_type requires a different data access pattern. We need an efficient way to query for partial matches on email_address based on customer_type.

Why Global Secondary Index (GSI):

GSIs allow you to define a different partition key and sort key from the main table, enabling new query patterns.

In this case, having customer_type as the GSI's partition key lets you group all emails with the same customer type together.

Using email_address as the sort key allows ordering within each customer type, facilitating the partial matching.

Querying the GSI:

You'll perform a query operation on the GSI, not the original table.

Use the begins_with key condition expression on the GSI's sort key (email_address) to find partial matches as the user types in the customer_type field.

References:

DynamoDB Global Secondary Indexes: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/GSI.html

DynamoDB Query Operation: [invalid URL removed]

Key Condition Expressions: [invalid URL removed]

Amazon CloudWatch is a service that monitors AWS resources and applications. The developer can publish custom metrics to CloudWatch that record the failures of the external payment processing API calls. The developer can configure a CloudWatch alarm to notify the existing SNS topic when the error rate exceeds 5% of the total number of transactions in an hour. This solution will meet the requirements in a near real-time and scalable way.

References:

[What Is Amazon CloudWatch? - Amazon CloudWatch]

[Publishing Custom Metrics - Amazon CloudWatch]

[Creating Amazon CloudWatch Alarms - Amazon CloudWatch]

This solution allows the developer to test the changes without affecting the production environment. Cloning an API creates a copy of the API definition that can be modified independently. The developer can then add request validation to the new API and test it using a testing tool. After verifying that the changes work as expected, the developer can apply the same changes to the existing API and deploy it to production.

Why Option B is Correct:

Amazon S3 Standard provides immediate access to files and is cost-effective for files that need to be accessed within 5 minutes.

By adding the S3 location to the SQS queue, you avoid transferring large files directly, which is both more efficient and scalable.

Why Other Options are Incorrect:

Option A: S3 Glacier Deep Archive is designed for archival storage with retrieval times ranging from minutes to hours, which does not meet the 5-minute requirement.

Option C: Amazon EBS is designed for block storage attached to EC2 instances, which adds unnecessary complexity and cost.

Option D: SQS is not designed to handle large file content directly and has message size limits (256 KB).

AWS Documentation References:

Amazon S3 Overview

Amazon SQS Best Practices