DEA-C01 Data Ingestion and Transformation Practice Question
A data engineer is building a data ingestion pipeline that uses AWS Lambda to process records from Amazon Kinesis Data Streams. The Lambda function writes the processed data to Amazon DynamoDB. Which TWO factors affect the maximum number of concurrent Lambda executions for this stream? (Choose TWO.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Batch size configured for the Lambda event source mapping
Correct options: D and E. The maximum number of concurrent Lambda executions for processing a Kinesis stream is determined by the number of shards in the stream, because each shard can have at most one concurrent Lambda invocation processing records from that shard. The batch size configured for the Lambda event source mapping also affects concurrency: a smaller batch size can lead to more invocations per shard over time, as each shard processes batches sequentially. Options A (DynamoDB read capacity units) and B (Lambda memory allocation) do not directly limit concurrency from the stream. Option C (stream name) is just an identifier and has no effect on concurrency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
DynamoDB table's read capacity units
Why it's wrong here
Read capacity affects DynamoDB performance, not Lambda concurrency.
- ✗
Lambda function's memory allocation
Why it's wrong here
Memory affects execution time but not concurrency limits.
- ✗
Kinesis stream name
Why it's wrong here
Stream name is an identifier, does not affect concurrency.
- ✓
Batch size configured for the Lambda event source mapping
Why this is correct
Batch size determines how many records are sent per invocation, affecting concurrency.
- ✓
Number of shards in the Kinesis stream
Why this is correct
Each shard can have one concurrent Lambda invocation.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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