DBS-C01 Management and Operations Practice Question
A company is running a production Amazon DynamoDB table with on-demand capacity. The table experiences occasional throttling during traffic spikes. The table's partition key is a timestamp, and the workload is write-heavy. The operations team needs to reduce throttling. Which THREE actions should the team take? (Choose three.)
⚠ Common exam trap
It's easy for candidates to assume on-demand capacity eliminates all throttling, but they overlook that throttling can still occur at the partition level due to uneven access patterns, which requires application-level key design changes to resolve.
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
✓
Add a random suffix to the partition key to distribute writes evenly.
Adding a random suffix to the timestamp partition key breaks the sequential write pattern, distributing writes evenly across all partitions. This prevents hot partitions, which are the root cause of throttling in a write-heavy workload with a monotonically increasing partition key.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add a random suffix to the partition key to distribute writes evenly.
Why this is correct
This prevents hot partitions.
- ✗
Increase the read capacity units for the table.
Why it's wrong here
The issue is write throttling, not read.
- ✓
Use DynamoDB Accelerator (DAX) to cache read-heavy queries.
Why this is correct
Reducing read load frees capacity for writes.
- ✓
Switch to provisioned capacity mode with auto scaling.
Why this is correct
Provisioned capacity with auto scaling can handle spikes better than on-demand.
- ✗
Enable DynamoDB global tables to distribute write traffic.
Why it's wrong here
Global tables do not solve local partition hot spots.
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