MLS-C01 Data Engineering Practice Question
A company uses Amazon Kinesis Data Streams to ingest real-time clickstream data from a website. The data is consumed by a Lambda function that writes records to an S3 bucket. Recently, the number of shards was increased from 2 to 4 to handle higher throughput. After the change, the Lambda function started processing records with increased latency and some records were being written out of order. What is the MOST likely cause?
⚠ Common exam trap
It's easy for candidates to confuse increased shard count with a need for more concurrency (Option C), but the real issue is that resharding changes the partition-to-shard mapping, which can break ordering guarantees unless the producer explicitly handles the new hash range.
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
✓
The partition key used by the producer does not ensure that related records go to the same shard after resharding.
After resharding from 2 to 4 shards, the mapping of partition keys to shards changes. If the producer does not use a partition key that ensures related records (e.g., same user session) are routed to the same shard, records that were previously ordered within a shard may now be split across multiple shards. Since the Lambda consumer processes shards independently, records from the same logical sequence can arrive out of order, and the increased shard count can also cause higher latency if the consumer is not properly parallelized.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The S3 bucket is not configured with versioning, causing overwrites.
Why it's wrong here
S3 versioning does not affect order of writes; it only keeps history.
- ✗
The Lambda function is reading from the oldest sequence number, causing high IteratorAgeSeconds.
Why it's wrong here
This would cause latency but not out-of-order writes.
- ✗
The Lambda function’s reserved concurrency is too low for the increased shard count.
Why it's wrong here
Lambda concurrency can be increased, but it does not cause out-of-order writes.
- ✓
The partition key used by the producer does not ensure that related records go to the same shard after resharding.
Why this is correct
After resharding, the mapping of partition keys to shards changes. If ordering matters, the partition key must be chosen to keep related records together.
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.