SAP-C02 Per-shard ordering Practice Question
A company is designing a new serverless data processing pipeline that uses Amazon Kinesis Data Streams to ingest real-time clickstream data. The data must be processed using AWS Lambda and then stored in Amazon S3. The company needs to ensure that records are processed in order within each shard and that each record is processed exactly once. Which configuration should they use? (Choose TWO.)
⚠ Common exam trap
The trap here is that candidates might think setting reserved concurrency to 1 per shard would maintain ordering, but reserved concurrency is a function-level limit and cannot be set per shard. The correct approach is to keep the default parallelization factor of 1 for each shard.
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
✓
Use the Kinesis Client Library (KCL) and implement deduplication logic in the Lambda function.
The correct options are D and E. Using the Kinesis Client Library (KCL) with deduplication logic ensures exactly-once processing and maintains per-shard ordering. Configuring the Lambda function with a reserved concurrency of 1 limits the function to a single concurrent execution, which can enforce sequential processing across shards and help preserve order, though it is not a scalable per-shard solution. Option A is incorrect because SQS FIFO adds unnecessary complexity and does not preserve Kinesis shard ordering natively. Option B is incorrect because the batch window only affects invocation latency, not ordering or exactly-once semantics. Option C is incorrect because enabling parallelization factor allows concurrent batches per shard, breaking strict ordering.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use an Amazon SQS FIFO queue between Kinesis and Lambda to ensure ordering.
Why it's wrong here
SQS FIFO adds complexity and latency; ordering is already maintained per shard.
- ✗
Increase the batch window to reduce the number of Lambda invocations.
Why it's wrong here
Batch window does not affect ordering; it may cause delays.
- ✗
Enable parallelization factor on the Lambda event source mapping.
Why it's wrong here
Parallelization factor allows multiple concurrent invocations per shard, breaking ordering.
- ✓
Use the Kinesis Client Library (KCL) and implement deduplication logic in the Lambda function.
Why this is correct
KCL with deduplication leverages sequence numbers and checkpointing to achieve exactly-once processing within a shard.
- ✓
Configure the Lambda function with a reserved concurrency of 1 per shard.
Why this is correct
Setting reserved concurrency to 1 ensures only one Lambda instance runs at a time, which can help maintain ordering for low-throughput streams, though it is not a per-shard setting.
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 |
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