Amazon Web Services DVA-C02 - AWS Certified Developer - Associate

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

1. Understanding the Use Case:

The goal is to store objects in an S3 bucket while optimizing storage costs. The key conditions are:

Objects are accessed infrequently after 1 week.

Objects must remainimmediately accessibleat all times.

2. AWS S3 Storage Classes Overview:

Amazon S3 offers various storage classes, each optimized for specific use cases:

S3 Standard:Best for frequently accessed data with low latency and high throughput needs.

S3 Standard-Infrequent Access (S3 Standard-IA):Optimized for infrequently accessed data but requires the same availability and immediate access as Standard storage. It provides lower storage costs but incurs retrieval charges.

S3 Glacier Flexible Retrieval (formerly S3 Glacier):Designed for archival data with retrieval latency ranging from minutes to hours. This does not meet the requirement for "immediate access."

S3 Glacier Deep Archive:Lowest-cost storage, suitable for rarely accessed data with retrieval times of hours.

3. Explanation of the Options:

Option A:"Create an S3 Lifecycle rule to expire objects after 7 days."Expiring objects after 7 days deletes them permanently, which does not fulfill the requirement of retaining the objects for later infrequent access.

Option B:"Create an S3 Lifecycle rule to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 7 days."This is the correct solution. S3 Standard-IA is ideal for objects accessed infrequently but still need to be available immediately. Transitioning objects to this storage class reduces storage costs while maintaining availability and low latency.

Option C:"Create an S3 Lifecycle rule to transition objects to S3 Glacier Flexible Retrieval after 7 days."S3 Glacier Flexible Retrieval is a low-cost archival solution. However, it does not provideimmediate accessas retrieval requires minutes to hours. This option does not meet the requirement.

Option D:"Create an S3 Lifecycle rule to delete objects that have delete markers."This option is irrelevant to the given use case, as it addresses versioning cleanup, which is not enabled in the described S3 bucket.

4. Implementation Steps for Option B:

To transition objects to S3 Standard-IA after 7 days:

Navigate to the S3 Console:

Sign in to theAWS Management Consoleand open the S3 service.

Select the Target Bucket:

Choose the bucket where the objects are stored.

Set Up a Lifecycle Rule:

Go to theManagementtab.

UnderLifecycle Rules, clickCreate lifecycle rule.

Define the Rule Name and Scope:

Provide a descriptive name for the rule.

Specify whether the rule applies to the entire bucket or a subset of objects (using a prefix or tag filter).

Configure Transitions:

ChooseAdd transition.

Specify that objects should transition toS3 Standard-IAafter7 days.

Review and Save the Rule:

Review the rule configuration and clickSave.

5. Cost Optimization Benefits:

Transitioning to S3 Standard-IA results in cost savings as it offers:

Lower storage costs compared to S3 Standard.

Immediate access to objects when required.However, remember that there is a retrieval cost associated with S3 Standard-IA, so it is best suited for data with low retrieval frequency.

Why Option A is Correct:DynamoDB supports incremental exports to Amazon S3 natively, making data analytics-ready with minimal operational overhead.

Why Other Options are Incorrect:

Option B:DynamoDB Streams require additional processing logic to write to S3, increasing complexity.

Option C & D:Using EMR for data movement adds unnecessary operational overhead compared to native exports.

AWS Documentation References:

DynamoDB Exports to S3

Comprehensive and Detailed Step-by-Step Explanation:

To confirm that the HTTP headers, body, and responses meet expectations, you need to test the specific HTTP Task state in isolation and inspect the details.

Option A: TestState API with TRACE:

The TestState API allows developers to test individual states in a state machine without executing the entire workflow.

Setting the inspection level to TRACE provides detailed information about the HTTP request and response, including headers, body, and status codes.

This option provides the precise and granular testing required to verify the HTTP Task functionality.

Why Other Options Are Incorrect:

Option B:The DEBUG inspection level provides less detailed information than TRACE and focuses on general debugging, not a detailed view of HTTP interactions.

Option C:Step Functions does not have a "data flow simulator" to test individual tasks; this option is not valid.

Option D:Changing the state machine’s log level to ALL increases logging granularity for the entire state machine but does not allow isolated testing of a specific HTTP Task.

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

Step-by-Step Breakdown:

Requirement Summary:

UseAWS SAMto deploy:

1 Lambda Function

1 S3 Bucket

Lambda needsread-only accessto the S3 bucket

Solution must be expressed viaAWS SAM template

Option A: Reference a second Lambda authorizer function

❌Incorrect: Lambda authorizers are used inAPI Gateway for authentication, not for granting S3 permissions.

Option B: Add a custom S3 bucket policy to the Lambda function

❌Incorrect: Bucket policiescontrol who can access the bucket, not what the Lambda function can do.

The permission must be granted to the Lambda’sIAM execution role.

Option C: Create an Amazon SQS topic for only S3 object reads

❌Incorrect: SQS cannot read objects from S3 and is not relevant to this scenario.

Option D: Add the S3ReadPolicy template to the Lambda function's execution role

✅Correct: AWS SAM providesmanaged policy templateslike AmazonS3ReadOnlyAccess andshortcuts like S3ReadPolicy.

You can apply these to the Lambda’s execution role using the Policies: section in your SAM template.

Example SAM YAML:

yaml

CopyEdit

Resources:

MyFunction:

Type: AWS::Serverless::Function

Properties:

CodeUri: my-code/

Handler: app.handler

Runtime: python3.11

Policies:

- S3ReadPolicy:

BucketName: !Ref MyBucket

MyBucket:

Type: AWS::S3::Bucket

Properties:

BucketName: my-personal-bucket-name

SAM Policy Templates:https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-policy-templates.html

Example using S3ReadPolicy:https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/serverless-policy-templates.html#s3-readpolicy

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.

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 optimalbecause 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.

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.