DEA-C01 Data Operations and Support Practice Question
A company is experiencing high costs from Amazon Redshift. The data engineer wants to optimize costs. Which THREE actions should the engineer take? (Choose THREE.)
⚠ Common exam trap
A common mix-up: candidates confuse cost optimization with performance improvement, leading them to select 'Increase the number of nodes' (Option C) thinking it will reduce costs by improving efficiency, when in fact it increases costs.
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
✓
Right-size the cluster based on workload analysis.
Right-sizing the cluster based on workload analysis ensures that the provisioned resources (number and type of nodes) match the actual compute and storage demands. Over-provisioned clusters waste money on unused capacity, while under-provisioned clusters cause performance issues. Analyzing metrics like CPU utilization, disk usage, and query queue wait times helps identify the optimal node count and instance type, directly reducing costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the frequency of automated snapshots.
Why it's wrong here
More snapshots increase S3 storage costs.
- ✓
Right-size the cluster based on workload analysis.
Why this is correct
Right-sizing ensures you only pay for needed resources.
- ✗
Increase the number of nodes to improve performance.
Why it's wrong here
More nodes increase costs; focus on right-sizing.
- ✓
Purchase Reserved Instances for steady-state workloads.
Why this is correct
Reserved instances provide significant discounts over on-demand.
- ✓
Enable Concurrency Scaling and set up a usage limit.
Why this is correct
Concurrency Scaling with pay-per-query avoids idle cluster costs.
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