DVA-C02 Practice Exam Questions with Answers AWS Certified Developer - Associate Certification

This solution will ensure that all orders and updates are stored to Amazon S3 with the least development effort because it uses DynamoDB Streams to capture changes in the DynamoDB table and trigger a Lambda function to write those changes to the S3 bucket. This way, the original Lambda function and API Gateway API endpoint do not need to be modified, and no additional services are required. Option A is not optimal because it will require more development effort to create a new Lambda function and a new API Gateway API endpoint, and to modify the original Lambda function to post updates to the new API endpoint. Option B is not optimal because it will introduce additional costs and complexity to use Amazon Kinesis Data Streams to create a new data stream, and to modify the Lambda function to publish orders to the data stream. Option D is not optimal because it will require more development effort to modify the Lambda function to publish to a new Amazon SNS topic, and to create and subscribe a new Lambda function to the topic.

References: Using DynamoDB Streams, Using AWS Lambda with Amazon S3

• CloudFormation and Lambda Environment Variables:
• CloudFormation Template Modification:

YAML

Environment:

Variables:

LOG_GROUP_ARN:!RefLogGroupResourceName

Use code with caution.

content_copy

• uk.co.certification.simulator.questionpool.PList@7dccd0e0
• Using the ARN in Your Lambda Function:

References:

• AWS Lambda Environment Variables: https://docs.aws.amazon.com/lambda/latest/dg/configuration-envvars.html
• CloudFormation !Ref Intrinsic Function: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/intrinsic-function-reference-ref.html

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.

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. DynamoDB Streams is a feature that captures data modification events in DynamoDB tables. The developer can enable DynamoDB Streams on the table and create a trigger to connect the DynamoDB stream to the Lambda function. This solution will enable the Lambda function to detect changes to the DynamoDB table in near real time.

References:

• [Amazon DynamoDB]
• [DynamoDB Streams - Amazon DynamoDB]
• [Using AWS Lambda with Amazon DynamoDB - AWS Lambda]

• IAM Roles for EC2 (A): The most secure way to provide AWS permissions from EC2.
• Pre-signed URLs (C): Temporary, authenticated URLs for specific S3 actions.

References:

• IAM Roles for EC2: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_use_switch-role-ec2.html
• Generating Presigned URLs: https://docs.aws.amazon.com/AmazonS3/latest/userguide/ShareObjectPreSignedURL.htm

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.

References:

• [ProvisionedThroughputExceededException - Amazon Kinesis Data Streams Service API Reference]
• [Best Practices for Handling Kinesis Data Streams Errors]

• Amazon EFS: A network file system (NFS) providing shared, scalable storage across multiple Lambda functions and other AWS resources.
• Lambda Mounting: EFS file systems can be mounted within Lambda functions to access a shared storage space.
• Log Appending: EFS supports appending data to existing files, making it ideal for the log file scenario.

References:

• Amazon EFS Documentation: https://docs.aws.amazon.com/efs/
• Using Amazon EFS with AWS Lambda: https://docs.aws.amazon.com/lambda/latest/dg/services-efs.html

• Default SSE in DynamoDB: DynamoDB tables are encrypted at rest by default using an AWS owned key (SSE-S3).
• No Additional Action Needed: Creating a table without explicitly specifying a KMS key will use this default encryption.

References:

• DynamoDB Server-Side Encryption: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Encryption

This solution will meet the requirements by using IAM database authentication for Aurora, which enables using IAM roles or users to authenticate with Aurora databases instead of using passwords or other secrets. The developer can use IAM database authentication for Aurora to enable secure database connections for all the Lambda functions that access Aurora DB instance. The developer can create an IAM role with permission to connect to Aurora DB instance and attach it to each Lambda function. The developer can also configure Aurora DB instance to use IAM database authentication and enable encryption in transit using SSL certificates. This way, the Lambda functions can use a single securely encrypted database connection string to access Aurora without needing any secrets or passwords. Option B is not optimal because it will store the credentials and read them from an encrypted Amazon RDS DB instance, which may introduce additional costs and complexity for managing and accessing another RDS DB instance. Option C is not optimal because it will store the credentials in AWS Systems Manager Parameter Store as a secure string parameter, which may require additional steps or permissions to retrieve and decrypt the credentials from Parameter Store. Option D is not optimal because it will use Lambda environment variables with a shared AWS Key Management Service (AWS KMS) key for encryption, which may not be secure or scalable as environment variables are stored as plain text unless encrypted with AWS KMS.

References: [IAM Database Authentication for MySQL and PostgreSQL], [Using SSL/TLS to Encrypt a Connection to a DB Instance]

This solution will meet the requirements by creating a Lambda function execution role, which is an IAM role that grants permissions to a Lambda function to access AWS resources such as Amazon S3 objects. The developer can attach a policy to the role that grants access to specific objects in the S3 bucket that are required by the application, following the principle of least privilege. Option A is not optimal because it will hardcode the credentials that are required to access S3 objects in the application code, which is insecure and difficult to maintain. Option B is not optimal because it will create a secret access key and access key ID with permission to access the S3 bucket, which will introduce additional security risks and complexity for storing and managing credentials. Option D is not optimal because it will store the secret access key and access key ID as environment variables in Lambda, which is also insecure and difficult to maintain.

References: [AWS Lambda Execution Role], [Using AWS Lambda with Amazon S3]

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. The developer can store each employee’s contact information in a DynamoDB table along with the object keys for the photos stored in Amazon S3. Amazon S3 is an object storage service that offers industry-leading scalability, data availability, security, and performance. The developer can use AWS APIs to search and retrieve the employee details and photos from DynamoDB and S3.

References:

• [Amazon DynamoDB]
• [Amazon Simple Storage Service (S3)]

• 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

This solution will meet the requirements by using a rolling with additional batch deployment method, which deploys the new version of the application to a separate group of instances and then shifts traffic to those instances in batches. This way, the application maintains full capacity and avoids service interruption during deployment, as well as minimizes the cost of additional resources that support the deployment. Option A is not optimal because it will use an all at once deployment method, which deploys the new version of the application to all instances simultaneously, which may cause service interruption or downtime during deployment. Option C is not optimal because it will use a blue/green deployment method, which deploys the new version of the application to a separate environment and then swaps URLs with the original environment, which may incur more costs for additional resources that support the deployment. Option D is not optimal because it will use an immutable deployment method, which deploys the new version of the application to a fresh group of instances and then redirects traffic to those instances, which may also incur more costs for additional resources that support the deployment.

References: AWS Elastic Beanstalk Deployment Policies

• 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.

AWS Secrets Manager is a service that helps you protect secrets needed to access your applications, services, and IT resources. Secrets Manager enables you to store, retrieve, and rotate secrets such as database credentials, API keys, and passwords. Secrets Manager supports a secret type for RDS databases, which allows you to select an existing RDS database instance and generate credentials for it. Secrets Manager encrypts the secret using AWS Key Management Service (AWS KMS) keys and enables automatic rotation of the secret at a specified interval. A Lambda function can use the AWS SDK or CLI to retrieve the secret from Secrets Manager and use it to connect to the database. Reference: Rotating your AWS Secrets Manager secrets

• Visibility Timeout:When an SQS message is processed by a consumer (here, the Lambda function), it's temporarily hidden from other consumers. Visibility timeout controls this duration.
• How It Helps:

References:

• SQS Visibility Timeout: https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-visibility-timeout.html

This solution allows the Lambda function to be invoked by the DynamoDB stream whenever updates are made to items in the DynamoDB table. Event source mapping is a feature of Lambda that enables a function to be triggered by an event source, such as a DynamoDB stream, an Amazon Kinesis stream, or an Amazon Simple Queue Service (SQS) queue. The developer can configure event source mapping for the Lambda function using the AWS Management Console, the AWS CLI, or the AWS SDKs. Changing the StreamViewType parameter value to NEW_AND_OLD_IMAGES for the DynamoDB table will not affect the invocation of the Lambda function, but only change the information that is written to the stream record. Mapping an Amazon Simple Notification Service (Amazon SNS) topic to the DynamoDB stream will not invoke the Lambda function directly, but require an additional subscription from the Lambda function to the SNS topic. Increasing the maximum runtime (timeout) setting of the Lambda function will not affect the invocation of the Lambda function, but only change how long the function can run before it is terminated.

• TTL for Automatic Deletion: DynamoDB's Time-to-Live effortlessly deletes expired items without manual intervention.
• DynamoDB Stream: Captures changes to the table, including deletions of expired items, triggering downstream actions.
• Lambda for Processing: A Lambda function connected to the stream provides custom logic for handling the deleted items.
• Code Efficiency: This solution leverages native DynamoDB features and stream-based processing, minimizing the need for custom code.

References:

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

This solution is the most efficient method to grant users access to AWS resources without requiring them to log in. Amazon Cognito is a service that provides user sign-up, sign-in, and access control for web and mobile applications. Amazon Cognito identity pools support both authenticated and unauthenticated users. Unauthenticated users receive access to your AWS resources even if they aren’t logged in with any of your identity providers (IdPs). You can use Amazon Cognito to associate unauthenticated users with an IAM role that has limited access to resources, such as Amazon S3 buckets or DynamoDB tables. This degree of access is useful to display content to users before they log in or to allow them to perform certain actions without signing up. Using an identity provider to securely authenticate with the application will require users to log in, which does not meet the requirement. Creating an AWS Lambda function to create an IAM user when a user accesses the application will incur unnecessary costs and complexity, and may pose security risks if not implemented properly. Creating credentials using AWS KMS and applying them to users when using the application will also incur unnecessary costs and complexity, and may not provide fine-grained access control for resources.

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 solution that will meet the requirements is to use an AWS Step Functions state machine to monitor API failures. Use the Wait state to delay calling the Lambda function. This way, the developer can refactor the serverless application to accommodate the change in a way that is automated and scalable. The developer can use Step Functions to orchestrate the Lambda function and handle any errors or retries. The developer can also use the Wait state to pause the execution for a specified duration or until a specified timestamp, which can help avoid exceeding the API limits. The other options either involve using additional services that are not necessary or appropriate for this scenario, or do not address the issue of API failures.

• 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.

https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_examples_lambda-access-dynamodb.html

This solution will solve the deployment issue by deploying the new version of the application to one new EC2 instance at a time, while keeping the old version running on the existing instances. This way, there will always be at least four instances serving traffic during the deployment, and no downtime or performance degradation will occur. Option A is not optimal because it will increase the cost of running the Elastic Beanstalk environment without solving the deployment issue. Option B is not optimal because it will split the traffic between two versions of the application, which may cause inconsistency and confusion for the customers. Option D is not optimal because it will deploy the new version of the application to two existing instances at a time, which may reduce the capacity below four instances during the deployment.

References: AWS Elastic Beanstalk Deployment Policies

This solution will meet the requirements by creating an advanced parameter in AWS Systems Manager Parameter Store, which is a secure and scalable service for storing and managing configuration data and secrets. The advanced parameter allows setting expiration and expiration notification policy types, which enable specifying an expiration date and time for the configuration and receiving notifications before the configuration expires. The Lambda code will be refactored to load the Root CA Cert from the parameter store and modify the runtime trust store outside the Lambda function handler, which will improve performance and reduce latency by avoiding repeated calls to Parameter Store and trust store modifications for each invocation of the Lambda function. Option A is not optimal because it will create a standard parameter in AWS Systems Manager Parameter Store, which does not support expiration and expiration notification policy types. Option B is not optimal because it will create a secret access key and access key ID with permission to access the S3 bucket, which will introduce additional security risks and complexity for storing and managing credentials. Option D is not optimal because it will create a Docker container from Node.js base image to invoke Lambda functions, which will incur additional costs and overhead for creating and running Docker containers.

References: AWS Systems Manager Parameter Store, [Using SSL/TLS to Encrypt a Connection to a DB Instance]

The UnprocessedKeys element indicates that the BatchGetItem operation did not process all of the requested items in the current response. This can happen if the response size limit is exceeded or if the table’s provisioned throughput is exceeded. To handle this situation, the developer should retry the batch operation with exponential backoff and randomized delay to avoid throttling errors and reduce the load on the table. The developer should also use an AWS SDK to make the requests, as the SDKs automatically retry requests that return UnprocessedKeys.

References:

• [BatchGetItem - Amazon DynamoDB]
• [Working with Queries and Scans - Amazon DynamoDB]
• [Best Practices for Handling DynamoDB Throttling Errors]

Using Amazon ElastiCache for Memcached to store and manage the session data will reduce the memory load and improve the performance of the web server. Using Amazon RDS for MySQL DB instance to store the application data will provide a scalable, reliable, and managed database service. Option A is not optimal because it does not address the memory issue of the web server. Option C is not optimal because it does not provide a persistent storage for the application data. Option D is not optimal because it does not provide a high availability and durability for the session data.

References: Amazon ElastiCache, Amazon RDS

• 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

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 itusing 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.

• Pseudo Parameters: CloudFormation provides pseudo parameters that reference runtime context, including the current AWS Region.
• Operational Efficiency: The AWS::Region pseudo parameter offers the most direct and self-contained way to obtain the Region dynamically within the template.

References:

• CloudFormation Pseudo Parameters: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/pseudo-parameter-reference.html

This solution meets the requirements in the most operationally efficient manner because it does not require any infrastructure provisioning or management. The developer can create a Lambda function that makes the API call and configure an EventBridge rule that triggers the function once a day at a designated time. This is a serverless solution that scales automatically and only charges for the execution time of the function.

The amount of memory you allocate to your Lambda function also determines how much CPU and network bandwidth it gets. Increasing the memory size can improve the performance of CPU-bound functions by giving them more CPU power. The CPU allocation is proportional to the memory allocation, so a function with 1 GB of memory has twice the CPU power of a function with 512 MB of memory. Reference: AWS Lambda execution environment

https://docs.aws.amazon.com/lambda/latest/dg/nodejs-context.html https://docs.aws.amazon.com/lambda/latest/dg/nodejs-logging.html

There is no explicit information for the runtime, the code is written in Node.js.

AWS Lambda is a service that lets developers run code without provisioning or managing servers. The developer can use the AWS request ID field in the context object to obtain a unique identifier for each function invocation. The developer can configure the application to write logs to standard output, which will be captured by Amazon CloudWatch Logs. This solution will meet the requirement of logging key events with a unique identifier.

References:

• [What Is AWS Lambda? - AWS Lambda]
• [AWS Lambda Function Handler in Node.js - AWS Lambda]
• [Using Amazon CloudWatch - AWS Lambda]

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.

• 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]

• 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

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]

https://aws.amazon.com/premiumsupport/knowledge-center/secrets-manager-share-between-accounts/ https://docs.aws.amazon.com/secretsmanager/latest/userguide/auth-and-access_examples_cross.html

• Instance Metadata Service: EC2 instances have access to an internal metadata service. It provides instance-specific information like instance ID, security groups, and public IP address.
• Accessing Metadata:

References:

• Instance Metadata and User Data: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html

• HTTP Status Codes: Each HTTP status code has a specific meaning in RESTful APIs.
• HTTP 405 (Method Not Allowed): Indicates that the request method (e.g., POST) is not supported for the specified resource.
• HTTP 401 (Unauthorized): Represents a failure to authenticate, which is the appropriate response for invalid login credentials.

References:

• HTTP Status Codes: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status

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]

• Containerization: Packaging the application as a container image promotes portability and standardization. Docker is the standard tool for containerization.
• Amazon ECR: ECR is a managed container registry designed to work seamlessly with AWS container services.
• Fargate: ECS Fargate provides serverless container orchestration, minimizing operational overhead for this proof-of-concept.

References:

• Docker: https://www.docker.com/
• Amazon ECR: https://aws.amazon.com/ecr/

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.

AWS CloudFormation is a service that enables developers to model and provision AWS resources using templates. The developer can add a CloudFormation Deletion Policy attribute with the Retain value to the database resource. This will prevent the database from being deleted when the stack is deleted or updated. The developer can also update the CloudFormation stack policy to prevent updates to the database. This will prevent accidental changes to the database configuration or properties.

References:

• [What Is AWS CloudFormation? - AWS CloudFormation]
• [DeletionPolicy Attribute - AWS CloudFormation]
• [Protecting Resources During Stack Updates - AWS CloudFormation]

This solution will meet the requirements by using AWS X-Ray to analyze and debug the performance issues with the distributed Lambda applications. 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 use AWS X-Ray to identify the root cause of the performance issues by examining the segments and errors that show the details of each request and the components that make up the applications. Option A is not optimal because it will use logging statements and Amazon CloudWatch, which may not provide enough information or visibility into the distributed applications. Option B is not optimal because it will use AWS CloudTrail, which is a service that records API calls and events for AWS services, not application performance data. Option D is not optimal because it will use Amazon Inspector, which is a service that helps improve the security and compliance of applications on Amazon EC2 instances, not Lambda functions.

References: AWS X-Ray, Using AWS X-Ray with AWS Lambda

Amazon Cognito user pools support Lambda triggers, which are custom functions that can be executed at various stages of the user pool workflow. A post authentication Lambda trigger can be used to perform custom actions after a user is authenticated, such as sending an email notification. Amazon SES is a cloud-based email sending service that can be used to sendtransactional or marketing emails. A Lambda function can use the Amazon SES API to send an email to the user’s email address after the user logs in successfully. Reference: Post authentication Lambda trigger

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 EC2 instances can send the state-change notification events to Amazon EventBridge. https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/monitoring-instance-state-changes.html Amazon EventBridge can send and receive events between event buses in AWS accounts. https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-cross-account.html

• Maximum concurrency for SQS as an event source allows customers to control the maximum concurrent invokes by the SQS event source1. When multiple SQS event sources are configured to a function, customers can control the maximum concurrent invokes of individual SQS event source1.
• In this scenario, the developer needs to resolve the issue of the third-party API frequently returning an HTTP 429 Too Many Requests error message, which prevents a significant number of messages from being processed successfully. To achieve this, the developer can follow these steps:
• By using this solution, the developer can reduce the frequency of HTTP 429 errors and improve the message processing success rate. The developer can also avoid throttling or blocking by the third-party API.

• CloudFormation and Dynamic References: The DefinitionSubstitutions property in CloudFormation allows you to pass values into Step Functions state machines at runtime.
• Cost-Effectiveness: This solution is cost-effective as it leverages CloudFormation's built-in capabilities, avoiding the need for additional services like Secrets Manager or AppConfig.

References:

• AWS Step Functions State Machine: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-stepfunctions-statemachine.html
• CloudFormation DefinitionSubstitutions: https://github.com/aws-cloudformation/aws-cloudformation-resource-providers-stepfunctions/issues/14

• 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

The solution that will meet the requirements is to use multiple stages in API Gateway. Create a Lambda function for each environment. Configure API Gateway stage variables to route traffic to the Lambda function in different environments. This way, the company can test the code in a dedicated, monitored test environment before releasing it to the production environment. The company can also use stage variables to specify the Lambda function version or alias for each stage, and avoid hard-coding the Lambda function name in the API Gateway integration. The other options either involve using a single stage in API Gateway, which does not allow testing in different environments, or adding different code blocks for different environments in the Lambda function, which increases complexity and maintenance.

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]