DVA-C02 Sample Questions Answers

This solution will most likely solve the issues because it will grant the IAM user the necessary permission to access the DynamoDB table using the AWS CLI command. The error message indicates that the IAM user does not have sufficient access rights to perform the scan operation on the table. Option A is not optimal because it will change the command to use put-item instead of scan, which will not achieve the desired result of getting data from the table. Option B is not optimal because it will involve contacting AWS Support, which may not be necessary or efficient for this issue. Option C is not optimal because it will state that DynamoDB cannot be accessed from the AWS CLI, which is incorrect as DynamoDB supports AWS CLI commands.

References: AWS CLI for DynamoDB, [IAM Policies for DynamoDB]

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)?

This solution allows the fastest response for the query because it enables the query to use a single partition key value (the Product ID) and a range of sort key values (the Product Rating) to find the matching items. A global secondary index (GSI) is an index that has a partition key and an optional sort key that are different from those on the base table. A GSI can be created at any time and can be queried or scanned independently of the base table. A local secondary index (LSI) is an index that has the same partition key as the base table, but a different sort key. An LSI can only be created when the base table is created and must be queried together with the base table partition key. Using a GSI with Product ID as the partition key and Review ID as the sort key will not allow the query to use a range of sort key values to find the highest ratings. Using an LSI with Product ID as the partition key and Product Rating as the sort key will not work because Product ID is not the partition key of the base table. Using an LSI with Review ID as the partition key and Product ID as the sort key will not allow the query to use a single partition key value to find the matching items.

Amazon Elastic Block Store (Amazon EBS) provides block level storage volumes for use with Amazon EC2 instances1. Amazon EBS encryption offers a straight-forward encryption solution for your EBS resources associated with your EC2 instances1. When you create an encrypted EBS volume and attach it to a supported instance type, the following types of data are encrypted: Data at rest inside the volume, all data moving between the volume and the instance, all snapshots created from the volume, and all volumes created from those snapshots1. Therefore, option A is correct.

• DynamoDB TTL (Time-to-Live): A native feature that automatically deletes items after a specified expiration time.
• Efficiency: Eliminates the need for scheduled deletion jobs, optimizing write throughput by avoiding potential throttling conflicts.
• Seamless Integration: TTL works directly within DynamoDB, requiring minimal development overhead.

References:

• DynamoDB TTL Documentation: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html

AWS Serverless Application Model (AWS SAM) is an open-source framework that enables developers to build and deploy serverless applications on AWS. AWS SAM uses a template specification that extends AWS CloudFormation to simplify the definition of serverless resources such as API Gateway, DynamoDB, and Lambda. The developer can use AWS SAM to define serverless resources in YAML and deploy them using the AWS SAM CLI.

References:

• [What Is the AWS Serverless Application Model (AWS SAM)? - AWS Serverless Application Model]
• [AWS SAM Template Specification - AWS Serverless Application Model]

• Amazon ElastiCache for Memcached is a fully managed, multithreaded, and scalable in-memory key-value store that can be used to cache frequently accessed data and improve application performance1. By using Amazon ElastiCache for Memcached, the developer can reduce the load on the main database and handle high traffic surges more efficiently.
• To use Amazon ElastiCache for Memcached, the developer needs to create a cache cluster with one or more nodes, and configure the application to store and retrieve data from the cache cluster2. The developer can use any of the supported Memcached clients to interact with the cache cluster3. The developer can also use Auto Discovery to dynamically discover and connect to all cache nodes in a cluster4.
• Amazon ElastiCache for Memcached is compatible with the Memcached protocol, which means that the developer can use existing tools and libraries that work with Memcached1. Amazon ElastiCache for Memcached also supports data partitioning, which allows the developer to distribute data among multiple nodes and scale out the cache cluster as needed.
• Using Amazon ElastiCache for Memcached is a simple and effective solution that meets the requirements with the least complexity. The developer does not need to change the database schema, migrate data to a different service, or use a different caching model. The developer can leverage the existing Memcached ecosystem and easily integrate it with the application.

Amazon S3 is a service that provides highly scalable, durable, and secure object storage. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. AWS Lambda is a service that lets developers run code without provisioning or managing servers. The developer can configure an S3 event to invoke a Lambda function that inserts records into DynamoDB whenever a new file is added to the S3 bucket. This solution will meet the requirement of inserting a record into DynamoDB as soon as a new file is added to S3.

References:

• [Amazon Simple Storage Service (S3)]
• [Amazon DynamoDB]
• [What Is AWS Lambda? - AWS Lambda]
• [Using AWS Lambda with Amazon S3 - AWS Lambda]

The HTTP header that the developer should use for this analysis is the X-Forwarded-For header. This header contains the IP address of the client that made the request to the Application Load Balancer. The developer can use this header to analyze patterns for the client IP addresses that use the application. The other headers either contain information about the protocol, host, or port of the request, which are not relevant for the analysis.

• An SQS FIFO queue is a type of queue that preserves the order of messages and ensures that each message is delivered and processed only once1. This is suitable for the scenario where the developer wants to ensure that there are no out-of-order updates in the legacy system.
• The visibility timeout value is the amount of time that a message is invisible in the queue after a consumer receives it2. This prevents other consumers from processing the same message simultaneously. If the consumer does not delete the message before the visibility timeout expires, the message becomes visible again and another consumer can receive it2.
• In this scenario, the developer needs to configure the visibility timeout value to be longer than the maximum processing time of the legacy system, which is 5 minutes. This will ensure that the message remains invisible in the queue until the legacy system finishes processing it and deletes it. This will prevent duplicate or out-of-order processing of messages by the legacy system.

A function alias is a pointer to a specific Lambda function version. You can use aliases to create different environments for your function, such as development, testing, and production. You can also use aliases to perform blue/green deployments by shifting traffic between two versions of your function gradually. This way, you can easily roll back to a previous version if something goes wrong, without having to redeploy your code or change your configuration. Reference: AWS Lambda function aliases

IAM instance profiles are containers for IAM roles that can be associated with EC2 instances. An IAM role is a set of permissions that grant access to AWS resources. An IAM role can be used to allow an EC2 instance to access an S3 bucket by including the appropriate permissions in the role’s policy. The S3:ListBucket permission allows listing the objects in an S3 bucket. By updating the IAM instance profile with this permission, the application on the EC2 instance can retrieve the objects from the S3 bucket and display them to the user. Reference: Using an IAM role to grant permissions to applications running on Amazon EC2 instances

Amazon API Gateway is a service that enables developers to create, publish, maintain, monitor, and secure APIs at any scale. Amazon CloudWatch is a service that monitors AWS resources and applications. API Gateway provides several CloudWatch metrics to help developers troubleshoot issues with their APIs. Two of the metrics that can help the developer troubleshoot the issue of API Gateway timing out are:

• IntegrationLatency: This metric measures the time between when API Gateway relays a request to the backend and when it receives a response from the backend. A high value for this metric indicates that the backend is taking too long to respond and may cause API Gateway to time out.
• Latency: This metric measures the time between when API Gateway receives a request from a client and when it returns a response to the client. A high value for this metric indicates that either the integration latency is high or API Gateway is taking too long to process the request or response.

References:

• [What Is Amazon API Gateway? - Amazon API Gateway]
• [Amazon API Gateway Metrics and Dimensions - Amazon CloudWatch]
• [Troubleshooting API Errors - Amazon API Gateway]

This solution meets the requirements because it provides a caching layer that can store and retrieve encrypted data from multiple nodes. Amazon ElastiCache for Redis supports encryption at rest and in transit, and can scale horizontally to increase the cache capacity and availability. Amazon ElastiCache for Memcached does not support encryption, Amazon CloudFront is a content delivery network that is not suitable for caching database queries, and Amazon DynamoDB Accelerator (DAX) is a caching service that only works with DynamoDB tables.

The solution that will meet the requirements is to create an Amazon EventBridge rule that runs on a regular schedule to invoke the Lambda function. This way, the developer can use an automated and serverless way to invoke the function every 10 minutes. The developer can also use a cron expression or a rate expression to specify the schedule for the rule. The other options either involve using an Amazon EC2 instance, which is not serverless, or using environment variables or query parameters, which do not trigger the function.

• Tracing Distributed Systems: AWS X-Ray is designed to trace requests across services, helping identify bottlenecks in distributed applications like this one.
• No Code Changes: Enabling X-Ray tracing often requires minimal code changes, meeting the requirement.
• Identifying Bottlenecks: Analyzing X-Ray traces and logs will reveal latency in communications between different AWS services, leading to the high duration time.

References:

• AWS X-Ray: https://aws.amazon.com/xray/
• X-Ray and Lambda: https://docs.aws.amazon.com/xray/latest/devguide/xray-services-lambda.html

Amazon CloudWatch is a service that monitors AWS resources and applications. The developer can use CloudWatch to monitor and troubleshoot all applications from one place. To do so, the developer needs to download the CloudWatch agent to the on-premises server and configure the agent to use IAM user credentials with permissions for CloudWatch. The agent will collect logs and metrics from the on-premises server and send them to CloudWatch.

References:

• [What Is Amazon CloudWatch? - Amazon CloudWatch]
• [Installing and Configuring the CloudWatch Agent - Amazon CloudWatch]

This solution will ensure that the repository package’s unit tests run in the new deployment environment with the least overhead because it uses AWS CodeBuild to build and test the code in a fully managed service, and AWS CodePipeline to orchestrate the deployment stages and actions. Option A is not optimal because it will use AWS CodeCommit instead of AWS CodeBuild, which is a source control service, not a build and test service. Option C is not optimal because it will use AWS CodeDeploy instead of AWS CodeBuild, which is a deployment service, not a build and test service. Option D is not optimal because it will add an action to the source stage instead of creating a new stage, which will not follow the best practice of separating different deployment phases.

References: AWS CodeBuild, AWS CodePipeline

This benefit occurs when initializing the AWS SDK outside of the Lambda handler function because it allows the SDK instance to be reused across multiple invocations of the same function. This can improve performance and reduce latency by avoiding unnecessary initialization overhead. If the SDK is initialized inside the handler function, it will create a new SDK instance for each invocation, which can increase memory usage and execution time.

The solution that will meet the requirements most efficiently is to create a Lambda environment variable to store the table name. Use the standard method for the programming language to retrieve the variable. This way, the developer can avoid hard-coding the table name in the Lambda function code and easily change the table name by updating the environment variable. The other options either involve storing the table name in a file, which is less efficient and secure than using an environment variable, or creating a global variable, which is not recommended as it can cause concurrency issues.

This solution will meet the requirements with the least operational overhead because it uses Amazon S3 as a scalable, secure, and durable storage service for the reports. The presigned URL will allow customers to access their reports for a limited time (8 hours) without requiring additional authentication. The S3 Lifecycle configuration rules will automatically delete the reports that are older than 2 days, reducing storage costs and complying with the data retention policy. Option A is not optimal because it will incur additional costs and complexity to store the reports as DynamoDB items, which have a size limit of 400 KB. Option B is not optimal because it will not provide customers with access to their reports within one hour, as Amazon SNS email delivery is not guaranteed. Option D is not optimal because it will require more operational overhead to manage an RDS database and a Lambda function for storing and deleting the reports.

References: Amazon S3 Presigned URLs, Amazon S3 Lifecycle

This solution will meet the requirements by allowing the Lambda functions to access the DB cluster securely within the same VPC without crossing the public internet. The developer can configure a VPC endpoint for RDS in a private subnet and assign it to the Lambda functions. The developer can also configure a security group for theLambda functions that allows inbound traffic from the DB cluster on port 3306 (MySQL). Option A is not optimal because it will expose the DB cluster to public access, which may compromise its security and data integrity. Option B is not optimal because it will introduce additional latency and complexity to use an RDS database proxy for accessing the DB cluster from Lambda functions within the same VPC. Option C is not optimal because it will require additional costs and configuration to use a NAT gateway for accessing resources in private subnets from Lambda functions.

References: [Configuring a Lambda Function to Access Resources in a VPC]

The correct answer is C. The developer did not update the Docker image tag to a new version.

C. The developer did not update the Docker image tag to a new version. This is correct. When deploying an application to Amazon EKS, the developer needs to specify the Docker image tag that contains the application code and configuration. If the developer does not update the Docker image tag to a new version after making changes to the application, the EKS cluster will continue to use the old Docker image tag that references the original backend resources. To fix this issue, the developer should update the Docker image tag to a new version and redeploy the application to the EKS cluster.

A. The developer did not successfully create the new AWS account. This is incorrect. The creation of a new AWS account is not related to the application’s connection to the backend resources. The developer can use any AWS account to host the EKS cluster and the backend resources, as long as they have the proper permissions and configurations.

B. The developer added a new tag to the Docker image. This is incorrect. Adding a new tag to the Docker image is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.

D. The developer pushed the changes to a new Docker image tag. This is incorrect. Pushing the changes to a new Docker image tag is not enough to deploy the changes to the application. The developer also needs to update the Docker image tag in the EKS cluster configuration, so that the EKS cluster can pull and run the new Docker image.

References:

• 1: Amazon EKS User Guide, “Deploying applications to your Amazon EKS cluster”, https://docs.aws.amazon.com/eks/latest/userguide/deploying-applications.html
• 2: Amazon ECR User Guide, “Pushing an image”, https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html
• 3: Amazon EKS User Guide, “Updating an Amazon EKS cluster”, https://docs.aws.amazon.com/eks/latest/userguide/update-cluster.html

The command that will meet the requirements is sam sync -watch. This command enables AWS SAM Accelerate mode, which allows the developer to only redeploy the Lambda functions that have changed. The -watch flag enables file watching, which automatically detects changes in the source code and triggers a redeployment. The other commands either do not enable AWS SAM Accelerate mode, or do not redeploy the Lambda functions automatically.

AWS Lambda is a service that lets you run code without provisioning or managing servers. Lambda functions can be configured to access resources in a VPC, such as an Aurora database, by specifying one or more subnets and security groups in the VPC settings of the function. A security group acts as a virtual firewall that controls inbound and outbound traffic for the resources in a VPC. To allow a Lambda function to communicate with an Aurora database, both resources need to be associated with the same security group, and the security group rules need to allow TCP traffic on Port 3306, which is the default port for MySQL databases. Reference: [Configuring a Lambda function to access resources in a VPC]

• API Gateway Stages: Stages in API Gateway represent distinct environments (like PROD and DEV) allowing different configurations.
• Stage Variables: Stage variables store environment-specific information, including Lambda function aliases.
• Ease of Management: This solution offers a straightforward way to manage different Lambda function versions across environments.

References:

• API Gateway Stages: https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-stages.html
• API Gateway Stage Variables: https://docs.aws.amazon.com/apigateway/latest/developerguide/stage-variables.html

• Secrets Management: AWS Secrets Manager is designed specifically for storing and managing sensitive credentials.
• Built-in Rotation: Secrets Manager provides automatic secret rotation functionality, enhancing security posture significantly.
• IAM Integration: IAM policies and roles grant fine-grained access to ECS Fargate, ensuring the principle of least privilege.
• Reduced Overhead: This solution centralizes secrets management and automates rotation, reducing operational overhead compared to the other options.

References:

• AWS Secrets Manager: https://aws.amazon.com/secrets-manager/
• Secrets Manager Rotation: https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotating-secrets.html
• IAM for Secrets Manager: https://docs.aws.amazon.com/secretsmanager/latest/userguide/auth-and-access_iam-policies.html

This step should be completed prior to deploying the application because it prepares the application artifacts for deployment. The AWS Serverless Application Model (AWS SAM) is a framework that simplifies building and deploying serverless applications on AWS. The AWS SAM CLI is a command-line tool that helps you create, test, and deploy serverless applications using AWS SAM templates. The sam package command bundles the application artifacts, such as Lambda function code and API definitions, and uploads them to an Amazon S3 bucket. The command also returns a CloudFormation template that is ready to be deployed with the sam deploy command. Compressing the application to a zip file and uploading it to AWS Lambda will not work because it does not use AWS SAM templates or CloudFormation. Testing the new Lambda function by first tracing it in AWS X-Ray will not prepare the application for deployment, but only monitor its performance and errors. Creating the application environment using the eb create my-env command will not work because it is a command for AWS Elastic Beanstalk, not AWS SAM.

AWS CloudFormation is a service that enables developers to model and provision AWS resources using templates. The developer can use the following steps to avoid accidental database deletion in the future:

• Set up AWS CodeDeploy to deploy the most recent version of the application at runtime. This will ensure that the application code is always up to date and does not depend on the AMI.
• Remove any commands that perform operating system patching from the UserData script. This will reduce the time that the UserData script takes to run and speed up the instance launch process.

References:

• [What Is AWS CloudFormation? - AWS CloudFormation]
• [What Is AWS CodeDeploy? - AWS CodeDeploy]
• [Running Commands on Your Linux Instance at Launch - Amazon Elastic Compute Cloud]

• Scenario: Application needs to fetch songs and artists efficiently in a single operation.
• BatchGetItem: This DynamoDB operation retrieves multiple items across different tables based on their primary keys in a single request.
• Optimized for Request Batching: This approach reduces network traffic compared to performing multiple queries individually.
• Data Modeling: The songs table is designed appropriately for this access pattern using artistName as the sort key.

References:

• Amazon DynamoDB BatchGetItem: https://docs.aws.amazon.com/amazondynamodb/latest/APIReference/API_BatchGetItem.ht

• Mocking API Responses: API Gateway's Mock integration type enables simulating API behavior without invoking backend services.
• Testing with Sample Data: Using captured responses from the real third-party API ensures realistic testing of the integration code.
• Focus on Integration Logic: This solution allows the developer to isolate and test the application's interaction with the payment APIs, even without a test environment from the third-party providers.

References:

• Amazon API Gateway Mock Integrations: https://docs.aws.amazon.com/apigateway/latest/developerguide/how-to-mock-integration.html

This solution will limit the ability to download a premier content file in the S3 bucket to paid subscribers only because it uses a pre-signed object URL that grants temporary access to an S3 object for a specified duration. The pre-signed object URL can be generated by the company’s website when a paid subscriber requests a download, and can be verified by Amazon S3 using the signature in the URL. Option A is not optimal because it will allow anyone to download the content from the S3 bucket without verifying their subscription status. Option C is not optimal because it will require additional steps and costs to configure multi-factor authentication for accessing the S3 bucket objects, which may not be feasible or user-friendly for paid subscribers. Option D is not optimal because it will not prevent non-paying website visitors from accessing the S3 bucket objects, but only encrypt them at rest.

References: Share an Object with Others, [Using Amazon S3 Pre-Signed URLs]

Amazon Cognito user pools is a service that provides a secure user directory that scales to hundreds of millions of users. The developer can use Amazon Cognito user pools to manage user accounts and create an Amazon Cognito user pool authorizer in API Gateway to control access to the API. The developer can use the Lambda function to store the photos in Amazon S3, which is a highly scalable, durable, and secure object storage service. The developer can store the object’s S3 key as part of the photo details in the DynamoDB table, which is a fast and flexible NoSQL database service. The developer can retrieve previously uploaded photos by querying DynamoDB for the S3 key and fetching the photos from S3. This solution will meet the requirements with the least operational overhead.

References:

• [Amazon Cognito User Pools]
• [Use Amazon Cognito User Pools - Amazon API Gateway]
• [Amazon Simple Storage Service (S3)]
• [Amazon DynamoDB]

This solution meets the requirements because it uses a PostgreSQL-compatible database that can secure and regularly rotate database credentials without requiring additional programming overhead. Amazon Aurora PostgreSQL is a relational database service that is compatible with PostgreSQL and offers high performance, availability, and scalability. AWS Secrets Manager is a service that helps you protect secrets needed to access your applications, services, and IT resources. You can store database credentials in AWS Secrets Manager and use them to access your Aurora PostgreSQL database. You can also enable automatic rotation of your secrets according to a schedule or an event. AWS Secrets Manager handles the complexity of rotating secrets for you, such as generating new passwords and updating your database with the new credentials. Using Amazon DynamoDB for the database will not meet the requirements because it is a NoSQL database that is not compatible with PostgreSQL. Using AWS Systems Manager Parameter Store for storing and rotating database credentials will require additional programming overhead to integrate with your database.

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

The solution that will meet the requirements is to use the AWS SDK ssm PutParameter operation in the Lambda function from the existing custom resource to store the credentials as a parameter. Set the parameter value to reference the new credentials. Set the parameter type to SecureString. This way, the developer can store the API credentials with minimal operational overhead, as AWS Systems Manager Parameter Store provides secure and scalable storage for configuration data. The SecureString parameter type encrypts the parameter value with AWS Key Management Service (AWS KMS). The other options either involve adding additional resources to the CloudFormation template, which increases complexity and cost, or do not encrypt the parameter value, which reduces security.

• IAM Roles for EC2: IAM roles are the recommended way to provide AWS credentials to applications running on EC2 instances. Here's how this works:
• Temporary Security Credentials: When the application on the EC2 instance needs to access S3, it doesn't directly use access keys. Instead, the AWS SDK running on the instance retrieves temporary security credentials associated with the role. These are rotated automatically by AWS.

References:

• IAM Roles for Amazon EC2: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_use_switch-role-ec2.html
• Temporary Security Credentials: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp.html

Amazon Machine Images (AMIs) are encrypted snapshots of EC2 instances that can be used to launch new instances. The developer can create new AMIs from the existing instances and specify encryption parameters. The developer can copy the encrypted AMIs to the destination Region and use them to create a new application stack. The developer can delete the unencrypted AMIs after the encryption process is complete. This solution will meet the encryption requirement and allow the developer to expand the application to run in the destination Region.

References:

• [Amazon Machine Images (AMI) - Amazon Elastic Compute Cloud]
• [Encrypting an Amazon EBS Snapshot - Amazon Elastic Compute Cloud]
• [Copying an AMI - Amazon Elastic Compute Cloud]

This solution will meet the requirements by using AWS X-Ray to enable tracing of application requests to debug performance issues in the code. AWS X-Ray is a service that collects data about requests that the applications serve, and provides tools to view, filter, and gain insights into that data. The developer can install the AWS X-Ray daemon on the EC2 instances, which is a software that listens for traffic on UDP port 2000, gathers raw segment data, and relays it to the X-Ray API. The developer can also install and configure the AWS X-Ray SDK for Python in the application, which is a library that enables instrumenting Python code to generate and send trace data to the X-Ray daemon. Option A is not optimal because it will install the Amazon CloudWatch agent on the EC2 instances, which is a software that collects metrics and logs from EC2 instances and on-premises servers, not application performance data. Option C is not optimal because it will configure the application to write JSON-formatted logs to /var/log/cloudwatch, which is not a valid path or destination for CloudWatch logs. Option D is not optimal because it will configure the application to write trace data to /var/log/xray, which is also not a valid path or destination for X-Ray trace data.

References: [AWS X-Ray], [Running the X-Ray Daemon on Amazon EC2]

Amazon ElastiCache is a service that offers fully managed in-memory data stores that are compatible with Redis or Memcached. The developer can create an ElastiCache for Redis instance and enable encryption of data in transit and at rest. This will ensure that the PHI is encrypted at all times. The developer can store frequently accessed data in the cache and use Redis features such as sorting and ranking to enhance the performance of the application.

References:

• [What Is Amazon ElastiCache? - Amazon ElastiCache]
• [Encryption in Transit - Amazon ElastiCache for Redis]
• [Encryption at Rest - Amazon ElastiCache for Redis]

The solution that will meet the requirements is to add a global secondary index (GSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key. Perform a query operation on the GSI by using the begins_with key condition expression with the email_address property. This way, the developer can search for partial matches of the email_address property of a particular customer type without recreating the DynamoDB table. The other options either involve using a local secondary index (LSI), which requires recreating the table, or using a different partition key, which does not allow filtering by customer_type.

• EventBridge (formerly CloudWatch Events) is the ideal service for real-time event monitoring.
• CloudTrail logs IAM role creation.
• EventBridge rules can filter CloudTrail events and trigger SNS notifications instantly.

• SQS Delivery Behavior: Standard SQS queues guarantee at-least-once delivery, meaning messages may be processed more than once. This can lead to duplicate emails in this scenario.
• Visibility Timeout: If the visibility timeout on the SQS queue is too short, a message might become visible for another consumer before the first Lambda function finishes processing it. This can also lead to duplicates.

References:

• Amazon SQS Delivery Semantics: [invalid URL removed]
• Amazon SQS Visibility Timeout: https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-visibility-timeout.html

Amazon API Gateway is a service that enables developers to create, publish, maintain, monitor, and secure APIs at any scale. The developer can define a development stage on the API Gateway API and instruct the other developers to point the endpoints to the development stage. This way, the developer can provide beta access to the new version of the API without affecting customers who use the production stage. This solution will meet the requirements with the least operational overhead.

References:

• [What Is Amazon API Gateway? - Amazon API Gateway]
• [Set up a Stage in API Gateway - Amazon API Gateway]

• Amazon EventBridge: A service that reacts to events from various AWS sources, including S3. Rules define which events trigger actions (like invoking Lambda functions).
• S3 Object Created Events: EventBridge can detect these, providing seamless integration for automated CSV processing.
• S3 Lifecycle Rules: Allow for actions based on object age or prefixes. These can directly trigger Lambda functions for file processing.

References:

• Amazon EventBridge Documentation: https://docs.aws.amazon.com/eventbridge/
• Working with S3 Event Notifications: https://docs.aws.amazon.com/AmazonS3/latest/userguide/EventNotifications.html
• S3 Lifecycle Configuration: https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html

• Problem:Directory access without file names fails.
• S3 Static Website Hosting:
• Avoiding Public Exposure:The S3 website endpoint allows CloudFront to access content without making the bucket public.

References:

• S3 Static Website Hosting: https://docs.aws.amazon.com/AmazonS3/latest/userguide/WebsiteHosting.html

• Understand the Problem:The existing DynamoDB table hasemail_addressas the partition key. Searching bycustomer_typerequires a different data access pattern. We need an efficient way to query for partial matches onemail_addressbased oncustomer_type.
• Why Global Secondary Index (GSI):
• Querying the GSI:

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]

The best solution for this requirement is option A. Creating an Amazon EventBridge rule that has a rate expression that will run the rule every 15 minutes and adding the Lambda function as the target of the EventBridge rule is the most efficient way to invoke the Lambda function periodically. This solution does not require any additional resources or development effort, and it leverages the built-in scheduling capabilities of EventBridge1.

The immutable deployment method is the best option for this scenario, because it meets the requirements of maintaining full capacity, avoiding service interruption, and minimizing the cost of additional resources.

The immutable deployment method creates a new set of instances in a separate Auto Scaling group and deploys the new version of the application to them. Then, it swaps the new instances with the old ones and terminates the old instances. This way, the application maintains full capacity during the deployment and avoids any downtime. The cost of additional resources is also minimized, because the new instances are only created for a short time and then replaced by the old ones.

The other deployment methods do not meet all the requirements:

• The all at once method deploys the new version to all instances simultaneously, which causes a short period of downtime and reduced capacity.
• The rolling with additional batch method deploys the new version in batches, but for the first batch it creates new instances instead of using the existing ones. This increases the cost of additional resources and reduces the capacity of the original environment.
• The blue/green method creates a new environment with a new set of instances and deploys the new version to them. Then, it swaps the URLs between the old and new environments. This method maintains full capacity and avoids service interruption, but it also increases the cost of additional resources significantly, because it duplicates the entire environment.

• API Gateway Stage Variables:These are designed for configuring dynamic values for your APIs in different deployment stages (dev, test, prod). Here's how to use them for third-party endpoints:
• Why Stage Variables Excel Here:

References:

• Amazon API Gateway Stage Variables: https://docs.aws.amazon.com/apigateway/latest/developerguide/stage-variables.html

Amazon DynamoDB is a fully managed NoSQL database service that can store and retrieve any amount of data with high availability and performance. DynamoDB can handle concurrent requests from multiple IoT devices without throttling or data loss. To prevent duplicate requests from causing inconsistencies or data loss, the Lambda function can use DynamoDB conditional writes to check if the unique identifier for each request already exists in the table before processing the request. If the identifier exists, the function can skip or abort the request;otherwise, it can process the request and store the identifier in the table. Reference: Using conditional writes

This solution meets the requirements because it encrypts data at rest using AWS KMS keys and provides an audit trail of when and by whom they were used. Server-side encryption with AWS KMS managed keys (SSE-KMS) is a feature of Amazon S3 that encrypts data using keys that are managed by AWS KMS. When SSE-KMS is enabled for an S3 bucket or object, S3 requests AWS KMS to generate data keys and encrypts data using these keys. AWS KMS logs every use of its keys in AWS CloudTrail, which records all API calls to AWS KMS as events. These events include information such as who made the request, when it was made, and which key was used. The company policy canuse CloudTrail logs to audit critical events related to their data encryption and access. Server-side encryption with Amazon S3 managed keys (SSE-S3) also encrypts data at rest using keys that are managed by S3, but does not provide an audit trail of key usage. Server-side encryption with customer-provided keys (SSE-C) and server-side encryption with self-managed keys also encrypt data at rest using keys that are provided or managed by customers, but do not provide an audit trail of key usage and require additional overhead for key management.

• 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

The IAM policy shown in the image is a resource-based policy that grants or denies access to an S3 bucket based on certain conditions. The first statement allows access to any S3 action on any object in the “DOC-EXAMPLE-BUCKET” bucket when the request is made over HTTPS (the value of aws:SecureTransport is true). The second statement denies access to the s3:GetObject and s3:PutObject actions on any object in the “DOC-EXAMPLE-BUCKET/secrets” prefix when the request is made over HTTP (the value of aws:SecureTransport is false). Therefore, the policy allows access on all objects in the “DOC-EXAMPLE-BUCKET” bucket except on objects that start with “secrets”. Reference: Using IAM policies for Amazon S3

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]