In a scenario involving seasonal spikes in data processing demand, how should a Hadoop cluster's capacity be planned to maintain performance?
- Auto-Scaling
- Over-Provisioning
- Static Scaling
- Under-Provisioning
In a scenario with seasonal spikes, auto-scaling is crucial in capacity planning. Auto-scaling allows the cluster to dynamically adjust resources based on demand, ensuring optimal performance during peak periods without unnecessary over-provisioning during off-peak times.
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