SAA-C03 Design High-Performing Architectures Practice Question
A media analytics company ingests a continuous stream of JSON clickstream events, roughly 20,000 records per second, into an Amazon Kinesis Data Streams stream with 32 shards. Downstream consumers must be able to re-read the same records up to 7 days later to rebuild a reporting index. Which combination of settings should the team use to maximize the number of records each consumer can read per second while preserving this replay capability?
⚠ Common exam trap
The trap here is assuming that adding more registered consumers to a standard Kinesis Data Streams stream increases the shared 2 MiB/s per-shard read throughput limit.
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
✓
Increase the shard count to 64, set the data retention period to 168 hours, and have each consumer use enhanced fan-out with its own dedicated 2 MiB/s read throughput per shard.
The scenario needs higher aggregate read throughput plus a full week of replayable data. Enhanced fan-out is the only mechanism that gives each consumer a dedicated 2 MiB/s per-shard read pipe instead of sharing the 2 MiB/s per-shard polling budget, and the 168-hour retention setting preserves records for the required rebuild window. Adding shards raises the aggregate ceiling further.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch the stream to on-demand capacity mode, keep the retention period at 24 hours, and have consumers read with the Kinesis Client Library because it partitions reads across shards with no per-shard limit.
Why it's wrong here
On-demand mode removes shard provisioning decisions but does not provide unlimited per-shard read throughput, and the Kinesis Client Library still respects the 2 MiB/s per-shard shared limit. The 24-hour retention also fails the 7-day replay requirement, so the design misses both objectives.
- ✓
Increase the shard count to 64, set the data retention period to 168 hours, and have each consumer use enhanced fan-out with its own dedicated 2 MiB/s read throughput per shard.
Why this is correct
Adding shards raises the aggregate write and read ceiling, the 168-hour retention period keeps records replayable for a full week, and enhanced fan-out gives each registered consumer a dedicated 2 MiB/s per-shard pipe rather than sharing the 2 MiB/s per-shard limit. This directly satisfies both the throughput and the 7-day replay requirements.
- ✗
Increase the shard count to 64, set the retention period to 168 hours, and rely on the shared GetRecords polling model because it automatically scales to 10 MiB/s per shard when many consumers register.
Why it's wrong here
GetRecords consumers share a single 2 MiB/s per-shard read budget; the service does not raise that ceiling to 10 MiB/s just because more consumers register. Retention and shard count are correct, but the polling model described does not exist for Kinesis Data Streams and would throttle the consumers.
- ✗
Keep 32 shards, set the retention period to 24 hours, and have consumers poll with the GetRecords API using a single shared throughput budget of 2 MiB/s per shard.
Why it's wrong here
A 24-hour retention period cannot satisfy the 7-day rebuild requirement, and shared GetRecords polling caps all consumers together at 2 MiB/s per shard, which throttles a 20,000 records/second feed. Neither the durability of the data nor the read throughput goal is met by this configuration.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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