DEA-C01 Data Store Management Practice Question
A data engineer is troubleshooting an Amazon DynamoDB table that has frequent throttling exceptions for write requests. The table has auto scaling enabled. What is the most likely cause?
⚠ Common exam trap
Many candidates assume auto scaling automatically prevents all throttling, but it only adjusts table-level capacity and cannot fix uneven data access patterns like a hot partition.
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 is causing a hot partition
Auto scaling adjusts capacity based on utilization, but it cannot prevent throttling caused by a hot partition. If a single partition key value receives a disproportionate share of write traffic, that partition's throughput limit (3,000 WCU or 10 MB per partition) is exceeded, triggering ProvisionedThroughputExceededException. Auto scaling operates at the table level, not per partition, so it cannot resolve this imbalance.
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 partition key is causing a hot partition
Why this is correct
Auto scaling adjusts capacity for uniform load, but a hot partition concentrates writes on one partition key value, exceeding that partition's throughput ceiling regardless of table-level capacity. This is the most likely cause of persistent write throttling.
- ✗
The table's read capacity is set too low
Why it's wrong here
Write throttling is governed by write capacity units, so lowering read capacity would not cause it; reads and writes consume separate capacity pools. Read capacity is the tempting answer because under-provisioned RCU causes throttling on read-heavy tables, and that would be the correct diagnosis if the errors were on GetItem or Query calls.
- ✗
The table's auto scaling is disabled
Why it's wrong here
The stem states auto scaling is already enabled, so this contradicts the given scenario rather than explaining the throttling. Auto scaling is the tempting answer because disabled scaling genuinely causes capacity to stay fixed during traffic spikes, which would be the correct diagnosis if the question had not confirmed it was active.
- ✗
The table is using global tables without conflict resolution
Why it's wrong here
Global tables replicate writes across regions but do not throttle local write requests; conflict resolution affects data consistency, not capacity. It is tempting because multi-region replication does consume write capacity units, so a global table with heavy replication traffic would be the correct diagnosis if the stem mentioned cross-region replication load.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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