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AWS DVA-C02 Drill: Lambda Deployment Methods - Navigating Package Upload Constraints

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 DVA-C02 candidates, the confusion often lies in the Lambda deployment methods — especially handling package size limits and deployment formats. In production, knowing exactly how to properly publish code (via CLI, Console, or container images) can save crucial troubleshooting time. Let’s drill down.

The Certification Drill (Simulated Question)
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Scenario
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NimbusApps, a fast-growing software startup, has a development team that builds serverless microservices with AWS Lambda. A developer has compiled a Lambda function and packaged the deployment artifact as a .zip file locally. The developer attempts to upload this .zip directly using the AWS Lambda Console’s function page. However, the console returns an error indicating the package cannot be uploaded.

The Requirement:
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Determine the valid solutions for publishing the Lambda function code under these constraints, considering AWS Lambda package size limits and deployment options.

The Options
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  • A) Upload the .zip package to Amazon S3, then use the Lambda Console to import the package from the S3 location.
  • B) Create an AWS Support ticket to request an increase in the maximum deployment package size.
  • C) Use the AWS CLI update-function-code command with the --publish parameter to upload the code directly.
  • D) Repackage the Lambda function as a Docker container image, upload this image to Amazon Elastic Container Registry (ECR), then create a new Lambda function in the Console referencing this image.
  • E) Digitally sign the .zip file, then create a new Lambda function in the Console and reference the code signing configuration ARN.

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Correct Answer
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A) Upload the .zip package to Amazon S3, then use the Lambda Console to import the package from the S3 location.
C) Use the AWS CLI update-function-code command with the --publish parameter to upload the code directly.

Quick Insight: The Developer Imperative
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  • The AWS Lambda Console has a direct .zip upload size limit (50 MB compressed). Larger deployment artifacts must leverage S3 or container images.
  • The update-function-code CLI command can circumvent some console limitations and includes the --publish flag to create new published versions.
  • Container images via ECR are valid but require a shift to container packaging rather than .zip, which is a different approach (valid but not necessarily required here).

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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Options A and C

The Winning Logic
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  • Option A: Uploading large packages directly via the Lambda Console UI is limited by a 50 MB compressed size cap. Using S3 as an intermediary bypasses this limitation—Lambda can import the code from the S3 bucket regardless of size (up to Lambda’s overall limits). This method is also recommended when working with deployment tools like Serverless Framework.
  • Option C: The aws lambda update-function-code CLI command supports uploading packages up to the Lambda limit and using --publish quickly creates a new published version in a single command. This method sidesteps UI upload constraints and is favored in automated pipelines.

The Trap (Distractor Analysis):
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  • Why not B? AWS does not increase the maximum deployment package size via Support tickets. The limits are enforced system-wide by the Lambda service.
  • Why not D? While container images are a valid Lambda deployment method, this requires repackaging your code as a container image and using ECR. The question’s developer is compiling a .zip file, so this represents a different packaging paradigm, not a direct fix.
  • Why not E? Code signing is for verifying package integrity and authenticity but does not affect upload mechanisms or package size limits directly.

The Technical Blueprint
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# Upload lambda package via CLI with --publish
aws lambda update-function-code \
    --function-name my-function \
    --zip-file fileb://my-function.zip \
    --publish

# Upload large package to S3
aws s3 cp my-large-function.zip s3://my-bucket/my-large-function.zip

# Update Lambda to use the S3 object
aws lambda update-function-code \
    --function-name my-function \
    --s3-bucket my-bucket \
    --s3-key my-large-function.zip \
    --publish

The Comparative Analysis
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Option API Complexity Performance Use Case
A Medium (S3 + Lambda) Good For larger .zip packages beyond console upload limits
B None (unsupported) N/A No practical effect—package size limits not increased
C Low (simple CLI) Fast Direct uploads suitable for smaller to medium .zip sizes
D High (container prep) Varies (cold start) When moving to container-based Lambda functions
E Medium (signing setup) No upload impact For security; does not solve upload errors

Real-World Application (Practitioner Insight)
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Exam Rule
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For the exam, always pick S3 upload or CLI methods when faced with Lambda package upload errors due to size or console limits.

Real World
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In production, many teams rely on CI/CD pipelines using the AWS CLI or SDK to automate publishing new Lambda versions, avoiding browser upload limits altogether. Container images are great for complex dependencies but come with different operational trade-offs.


(CTA) Stop Guessing, Start Mastering
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Disclaimer

This is a study note based on simulated scenarios for the 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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