AWS DVA-C02 Drill: Lambda Deployment Limits - Handling Large Function Packages

Jeff’s Note

#

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 understanding how to deploy Lambda functions that exceed console upload size limits. In production, this knowledge is critical because the Lambda Console has strict size caps on direct uploads, and knowing alternative deployment mechanisms can save hours of troubleshooting. Let’s drill down.

The Certification Drill (Simulated Question)

#

Scenario

#

Phoenix Dynamics, a SaaS startup developing an AI-powered analytics platform, has a new Lambda function with heavy dependencies resulting in a deployment package exceeding the size allowed by the AWS Lambda Console’s direct upload limit. The lead developer tries uploading the .zip package via the Lambda Console but encounters the error: RequestEntityTooLargeException. The team needs to find valid methods to successfully publish and deploy the Lambda function code.

The Requirement:

#

Identify two viable solutions that enable Phoenix Dynamics to publish the large Lambda deployment package without hitting size-related errors.

The Options

#

• A) Upload the deployment package to an Amazon S3 bucket. Then use the Lambda Console’s function configuration to specify the S3 object location and deploy the function code from there.
• B) Open a support ticket with AWS to request an increase in the maximum allowed Lambda package size for the account.
• C) Use the AWS CLI command update-function-code with the --publish flag to deploy the zipped function package.
• D) Repackage the Lambda function as a Docker container image, upload the image to Amazon Elastic Container Registry (ECR), and configure the Lambda function to use the container image.
• E) Digitally sign the zipped package and create a new Lambda function referencing the code signing configuration Amazon Resource Name (ARN).

Google adsense

#

leave a comment:

Correct Answer

#

A) Upload the package to Amazon S3. Use the Functions page on the Lambda console to upload the package from the S3 location.
D) Repackage the Lambda function as a Docker container image. Upload the image to Amazon Elastic Container Registry (Amazon ECR). Create a new Lambda function by using the Lambda console. Reference the image that is deployed to Amazon ECR.

Quick Insight: The Developer Imperative

#

The Lambda Console has a strict direct upload size limit (50 MB zipped for console upload). To work around this, developers either use S3 as an intermediate storage or switch to container image deployment, which supports larger packages up to 10 GB. These are practical and native ways to handle large Lambda artifacts. CLI commands themselves don’t lift the upload size limit if the code is passed directly.

Content Locked: The Expert Analysis

#

You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?

The Expert’s Analysis

#

Correct Answer

#

Options A and D

The Winning Logic

#

• Option A: Uploading the zip package to an S3 bucket bypasses the console upload size limit because Lambda supports specifying S3 object locations for deployment packages. This approach is commonly used when packages exceed the 50 MB zipped size limit for direct console uploads. The Lambda console or CLI then fetches the code from S3 internally.

• Option D: Packaging the function as a Docker container image and pushing it to Amazon ECR is the modern alternative for large Lambda deployments. Container images can be up to 10 GB in size, supporting complex dependencies and binaries beyond zip-package constraints. Lambda can then be configured to use that image as the function runtime.

The Trap (Distractor Analysis):

#

• Option B: AWS Support cannot increase the 50 MB zipped console upload limit; this is a hard service limit.

• Option C: The CLI update-function-code command does not bypass upload size limits if you try to push a zipped package larger than allowed. The --publish flag only publishes a new version; it doesn’t affect size limits.

• Option E: Code signing enhances security but does not affect upload size limits and won’t resolve the RequestEntityTooLargeException.

The Technical Blueprint

#

B) For Developer / SysOps (Code/CLI Snippet):

#

Uploading a large package to S3 and deploying via CLI:

aws s3 cp my-function.zip s3://my-lambda-code-bucket/my-function.zip

aws lambda update-function-code \
    --function-name MyFunction \
    --s3-bucket my-lambda-code-bucket \
    --s3-key my-function.zip

Deploying a Lambda container image from Amazon ECR via AWS CLI:

# Assume the container has been built and tagged locally:
docker build -t my-lambda-function .

# Authenticate Docker to ECR:
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin <ACCOUNT_ID>.dkr.ecr.us-east-1.amazonaws.com

# Tag and push:
docker tag my-lambda-function:latest <ACCOUNT_ID>.dkr.ecr.us-east-1.amazonaws.com/my-lambda-function:latest
docker push <ACCOUNT_ID>.dkr.ecr.us-east-1.amazonaws.com/my-lambda-function:latest

# Update the Lambda function to use the image:
aws lambda update-function-code \
    --function-name MyFunction \
    --image-uri <ACCOUNT_ID>.dkr.ecr.us-east-1.amazonaws.com/my-lambda-function:latest

The Comparative Analysis (Developer)

#

Real-World Application (Practitioner Insight)

#

Exam Rule

#

“For the exam, always remember: If a Lambda zip package is too large for console upload, use S3 deployment or container images.”

Real World

#

“In production, container images for Lambda open the door to adopting existing container workflows and simplifying dependency management — a big win for complex workloads.”

(CTA) Stop Guessing, Start Mastering

#

Disclaimer

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