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Comprehensive and Detailed Step-by-Step Explanation:

The requirement is to query records by CustomerID, which is not the current partition key (OrderID). To achieve this efficiently:

Option A: Create a GSI with CustomerID as the Partition Key:

A Global Secondary Index (GSI) allows developers to create a different partition key and optional sort key for querying the data.

By creating a GSI with CustomerID as the partition key, the developer can query the table efficiently using CustomerID as the primary lookup key.

This avoids scanning the entire table and matches the requirement.

Why Other Options Are Incorrect:

Option B:Using CustomerID as a sort key for the GSI and performing a scan operation is inefficient. Queries are optimized, but scans are not.

Option C and D:Local Secondary Indexes (LSI) are only valid when the partition key remains the same as the base table. Since OrderID is the base table’s partition key, using CustomerID as the partition key or sort key in an LSI is not valid.

Amazon S3 supports resource-based policies, which are JSON documents that specify the permissions for accessing S3 resources. A resource-based policy can be used to enforce encryption in transit by denying access to requests that do not use HTTPS. The condition key aws:SecureTransport can be used to check if the request was sent using SSL. If the value of this key is false, the request is denied; otherwise, the request is allowed. Reference: How do I use an S3 bucket policy to require requests to use Secure Socket Layer (SSL)?

Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:

1. Understanding the Use Case:

The API needs to:

Generate responses without backend integrations:This indicates the use of mock responses for testing.

Be used by multiple internal teams during development.

Minimize operational overhead.

2. Key Features of Amazon API Gateway:

REST APIs:Fully managed API Gateway option that supports advanced capabilities like mock integrations, request/response transformation, and more.

HTTP APIs:Lightweight option for building APIs quickly. It supports fewer features but has lower operational complexity and cost.

Mock Integration:Allows API Gateway to return pre-defined responses without requiring backend integration.

3. Explanation of the Options:

Option A:"Create an Amazon API Gateway REST API. Set up a proxy resource that has the HTTP proxy integration type."A proxy integration requires a backend service for handling requests. This does not meet the requirement of "no backend integrations."

Option B:"Create an Amazon API Gateway HTTP API. Provision a VPC link, and set up a private integration on the API to connect to a VPC."This requires setting up a VPC and provisioning resources, which increases operational overhead and is unnecessary for this use case.

Option C:"Create an Amazon API Gateway HTTP API. Enable mock integration on the method of the APIresource."While HTTP APIs can enable mock integrations, they have limited support for advanced features compared to REST APIs, such as detailed request/response customization. REST APIs are better suited for development environments requiring mock responses.

Option D:"Create an Amazon API Gateway REST API. Enable mock integration on the method of the API resource."This is the correct answer. REST APIs with mock integration allow defining pre-configured responses directly within API Gateway, making them ideal for scenarios where backend services are unavailable. It provides flexibility for testing while minimizing operational overhead.

4. Implementation Steps:

To enable mock integration with REST API:

Create a REST API in API Gateway:

Open theAPI Gateway Console.

ChooseCreate API>REST API.

Define the API Resource and Methods:

Add a resource and method (e.g., GET or POST).

Set Up Mock Integration:

Select the method, and in theIntegration Type, chooseMock Integration.

Configure the Mock Response:

Define a200 OK responsewith the desired response body and headers.

Deploy the API:

Deploy the API to a stage (e.g., dev) to make it accessible.

5. Why REST API Over HTTP API?

REST APIs support detailed request/response transformations and robust mock integration features, which are ideal for development and testing scenarios.

While HTTP APIs offer lower cost and simplicity, they lack some advanced features required for fine-tuned mock integrations.

Principle of Least Privilege: Granting specific permissions through an IAM role is more secure than directly attaching policies to a function or using root user credentials.

IAM Roles for Lambda: Designed to provide temporary credentials to Lambda functions, enhancing security.

Reusability: The existing IAM policy ensures the correct S3 and DynamoDB access is granted.

Amazon CloudWatch is the service that collects and stores logs from AWS Lambda functions. The developer can use CloudWatch Logs Insights to query and analyze the logs for errors and metrics. Option A is not correct because Amazon S3 is a storage service that does not store Lambda function logs. Option B is not correct because AWS CloudTrail is a service that records API calls and events for AWS services, not Lambda function logs. Option D is not correct because Amazon DynamoDB is a database service that does not store Lambda function logs.

This solution will meet the requirements by creating a single S3 bucket policy that denies access to the S3 bucket unless the request comes from one of the specified VPC endpoints. The aws:SourceVpce condition key is used to match the ID of the VPC endpoint that is used to access the S3 bucket. The StringNotEquals condition operator is used to negate the condition, so that only requests from the listed VPC endpoints are allowed. Option A is not optimal because it will create multiple S3 bucket policies, which is not possible as only one bucket policy can be attached to an S3 bucket. Option B is not optimal because it will use the aws:SourceVpc condition key, which matches the ID of the VPC that is used to access the S3 bucket, not the VPC endpoint. Option C is not optimal because it will use the StringNotEquals condition operator with a single value, which will deny access to the S3 bucket from all VPC endpoints except one.

Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:

1. Understanding the Use Case:

The company wants to gradually release a new feature to 15% of users to perform testing. AWS AppConfig is designed to manage and deploy configurations, including feature flags, allowing controlled rollouts.

2. Key AWS AppConfig Features:

Feature Flags:Enable or disable features dynamically without redeploying code.

Variants:Define different configurations for subsets of users.

Targeting Rules:Specify rules for which users receive a particular variant.

3. Explanation of the Options:

Option A:"Set up a custom script within the application to randomly select 15% of users. Assign a flag for the new feature to the selected users."While possible, this approach requires significant operational effort to manage user selection and ensure randomness. It does not leverage AWS AppConfig's built-in capabilities, which increases overhead.

Option B:"Create separate AWS AppConfig feature flags for both groups of users. Configure the flags to target 15% of users."Creating multiple feature flags for different user groups complicates configuration management and does not optimize the use of AWS AppConfig.

Option C:"Create an AWS AppConfig feature flag. Define a variant for the new feature, and create a rule to target 15% of users."This is the correct solution. Using AWS AppConfig feature flags with variants and targeting rules is the most efficient approach. It minimizes operational overhead by leveraging AWS AppConfig's built-in targeting and rollout capabilities.

Option D:"Use AWS AppConfig to create a feature flag without variants. Implement a custom traffic splitting mechanism in the application code."This approach requires custom implementation within the application code, increasing complexity and operational effort.

4. Implementation Steps for Option C:

Set Up AWS AppConfig:

Open theAWS Systems Manager Console.

Navigate toAppConfig.

Create a Feature Flag:

Define a new configuration for the feature flag.

Add variants (e.g., "enabled" for the new feature and "disabled" for no change).

Define a Targeting Rule:

Usepercentage-based targetingto define a rule that applies the "enabled" variant to 15% of users.

Targeting rules can use attributes like user IDs or geographic locations.

Deploy the Configuration:

Deploy the configuration using a controlled rollout to ensure gradual exposure.

Problem:Directory access without file names fails.

S3 Static Website Hosting:

Configuring S3 as a static website enables automatic serving of index.html for directory requests.

Bucket policies ensure correct access permissions.

Updating the CloudFront origin simplifies routing.

Avoiding Public Exposure:The S3 website endpoint allows CloudFront to access content without making the bucket public.

Amazon RDS for MySQL supports read replicas, which are copies of the primary database instance that can handle read-only queries. Read replicas can improve the read performance ofthe database by offloading the read workload from the primary instance and distributing it across multiple replicas. To use read replicas, the application code needs to be modified to direct read queries to the URL of the read replicas, while write queries still go to the URL of the primary instance. This solution requires less current and future effort than using a multi-AZ deployment, which does not provide read scaling benefits, or using open source replication software, which requires additional configuration and maintenance. Reference: Working with read replicas