[Solved] Why might Predictive Scaling forecasts sometimes be inaccurate or delayed? — Ans: Because it depends on the quality and amount of historical data available | AWS

AWS - Auto Scaling

Why might Predictive Scaling forecasts sometimes be inaccurate or delayed?

ABecause it depends on the quality and amount of historical data available

BBecause it uses random number generation for forecasts

CBecause it only updates forecasts once per month

DBecause it requires manual approval before scaling

Step-by-Step Solution

Solution:

Step 1: Understand forecast dependency
Predictive Scaling relies on historical data quality and volume for accuracy.
Step 2: Identify causes of inaccuracy or delay
Insufficient or poor data leads to less accurate or delayed forecasts.
Final Answer:
Because it depends on the quality and amount of historical data available -> Option A
Quick Check:
Data quality controls forecast accuracy and timing [OK]

Quick Trick: Good data means better forecasts; poor data causes errors [OK]

Common Mistakes:

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