MLS-C01 Data Engineering Practice Question
A company is using Amazon Kinesis Data Streams with a Lambda consumer. The Lambda function writes results to an S3 bucket. The team wants to ensure that each record is processed exactly once and in order. Which TWO configurations should the team implement? (Choose 2.)
⚠ Common exam trap
It's easy for candidates to confuse batch size with concurrency control, mistakenly believing that setting batch size to 1 alone is sufficient for ordered processing, while ignoring the parallelization factor that governs how many concurrent invocations can process records from the same shard. Additionally, versioning is key for duplicate detection, not just batch size adjustments.
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
✓
Set the parallelization factor to 1
Setting the parallelization factor to 1 ensures that each shard of the Kinesis Data Stream is processed by only one Lambda instance at a time, preserving the order of records within that shard. Option E is correct because enabling S3 bucket versioning helps track duplicates: if the same record is written multiple times, S3 versioning creates multiple versions, allowing the system to detect and handle duplicates, contributing to exactly-once processing semantics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the batch size to 1
Why it's wrong here
Batch size does not affect ordering; Kinesis already provides per-shard ordering.
- ✗
Increase the Lambda function's reserved concurrency
Why it's wrong here
More concurrency can cause out-of-order processing.
- ✓
Set the parallelization factor to 1
Why this is correct
This ensures a single Lambda instance processes each shard, maintaining order.
- ✗
Configure a dead-letter queue for failed records
Why it's wrong here
DLQ handles failures but does not guarantee order.
- ✓
Enable S3 bucket versioning to track duplicates
Why this is correct
Versioning helps detect duplicates; combined with idempotent writes, ensures exactly-once.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.