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AWS DVA-C02 Drill: IAM Role Permissions - Lambda Access to S3 with SAM

Jeff Taakey
Author
Jeff Taakey
21+ Year Enterprise Architect | AWS SAA/SAP & Multi-Cloud Expert.

Jeff’s Note
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Unlike generic exam dumps, ADH analyzes this scenario through the lens of a Real-World Lead Developer.

For AWS DVA-C02 candidates, the confusion often lies in how to use AWS SAM’s built-in policies versus crafting custom permissions. In production, this is about knowing exactly how to safely grant minimal privileges to your Lambda so it can interact with S3 — no more, no less — while keeping your infrastructure as code clean and maintainable. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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TechNova Solutions is building a serverless image processing pipeline. They deploy a new application using AWS Serverless Application Model (SAM). The application consists of a single AWS Lambda function and one Amazon S3 bucket containing images. The Lambda must be able to read objects from the S3 bucket but must not modify or write to them.

The Requirement:
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How should the Lead Developer configure the AWS SAM template to grant only the necessary read access permissions to the Lambda function?

The Options
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  • A) Reference a second Lambda authorizer function in the SAM template.
  • B) Attach a custom S3 bucket policy directly to the Lambda function resource.
  • C) Create an Amazon Simple Queue Service (SQS) queue for S3 object read notifications, then reference the queue in the SAM template.
  • D) Attach the AWS SAM predefined managed policy AmazonS3ReadOnlyAccess (or a similar S3 read policy) to the Lambda function’s execution role.

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Correct Answer
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D

Quick Insight: The Developer Imperative
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Using SAM’s built-in S3 read policies on the Lambda execution role is the cleanest and most maintainable approach. It leverages least privilege and avoids over-provisioning permissions or unnecessary complexity such as adding unrelated services like SQS.

Content Locked: The Expert Analysis
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You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?


The Expert’s Analysis
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Correct Answer
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Option D

The Winning Logic
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In SAM templates, you grant permissions to Lambda functions by attaching IAM managed policies or inline policies to the function’s execution role. AWS provides predefined managed policies such as AmazonS3ReadOnlyAccess that grant just the read permissions on S3 buckets and objects. Using this policy (or the equivalent S3ReadPolicy in AWS SAM’s policy templates) is the recommended way to ensure the Lambda can only read from S3 without overreaching privileges.
This approach:

  • Explicitly grants least privilege for read access.
  • Is easy to automate and maintain in infrastructure as code.
  • Avoids complex custom policies or unrelated services.

The Trap (Distractor Analysis):
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  • Why not A? Referencing a second Lambda authorizer function is not related to granting resource permissions to read from S3. It only controls invocation authorization, not access to S3 data.
  • Why not B? Attaching a bucket policy directly to the Lambda function resource is technically incorrect; bucket policies attach to the S3 bucket, and granting access via bucket policies is less flexible and can conflict with IAM role permissions. Using a role policy is standard best practice for Lambda.
  • Why not C? Creating an SQS queue for object read operations adds unnecessary complexity and does not grant permissions to the Lambda function to read directly from S3. This option confuses event-driven architecture with permissions management.

The Technical Blueprint
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B) For Developer (Code/CLI Snippet):
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A typical snippet from an AWS SAM template to grant minimal S3 read permissions looks like:

Resources:
  ImageProcessorFunction:
    Type: AWS::Serverless::Function
    Properties:
      Handler: index.handler
      Runtime: nodejs18.x
      Policies:
        - S3ReadPolicy:
            BucketName: !Ref ImageBucket
      Environment:
        Variables:
          BUCKET_NAME: !Ref ImageBucket

  ImageBucket:
    Type: AWS::S3::Bucket

This S3ReadPolicy snippet automatically attaches an IAM policy granting read-only access (s3:GetObject, s3:ListBucket) on the specified bucket to the Lambda execution role.


The Comparative Analysis (Mandatory for Associate/Pro)
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Option API Complexity Performance Use Case
A Invalid usage; relates to authorization, not resource permission No effect on S3 access Not applicable
B Contains policy misplacement risk; manual JSON syntax needed No performance gain; risk of errors Not recommended; non-standard approach
C Introduces unrelated SQS service; indirect and unnecessary Adds latency and overhead Event-driven workflows, but no direct S3 read enablement
D Direct, minimal policy attachment via SAM policy templates Optimal; minimal latency Recommended best practice for Lambda S3 read access

Real-World Application (Practitioner Insight)
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Exam Rule
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For the exam, always prefer IAM role policies attached to the Lambda execution role using SAM’s predefined policy templates whenever you see a Lambda function accessing other AWS resources like S3.

Real World
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While some teams also manage bucket policies for added control, ARM’s best practice is to rely on Lambda’s execution role permissions for fine-grained, least-privilege access. This approach aligns well with continuous integration pipelines and Infrastructure as Code (IaC) strategies.


(CTA) Stop Guessing, Start Mastering
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Disclaimer

This is a study note based on simulated scenarios for the AWS DVA-C02 exam.

The DevPro Network: Mission and Founder

A 21-Year Tech Leadership Journey

Jeff Taakey has driven complex systems for over two decades, serving in pivotal roles as an Architect, Technical Director, and startup Co-founder/CTO.

He holds both an MBA degree and a Computer Science Master's degree from an English-speaking university in Hong Kong. His expertise is further backed by multiple international certifications including TOGAF, PMP, ITIL, and AWS SAA.

His experience spans diverse sectors and includes leading large, multidisciplinary teams (up to 86 people). He has also served as a Development Team Lead while cooperating with global teams spanning North America, Europe, and Asia-Pacific. He has spearheaded the design of an industry cloud platform. This work was often conducted within global Fortune 500 environments like IBM, Citi and Panasonic.

Following a recent Master’s degree from an English-speaking university in Hong Kong, he launched this platform to share advanced, practical technical knowledge with the global developer community.


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