A startup is launching a social media analytics platform that expects irregular traffic patterns, with sudden surges at times due to viral content analysis. They seek a service that can seamlessly adjust the platform's computing capacity to align with the fluctuating demand. Which feature should be utilized to maintain performance during traffic increases and decrease costs when demand is low?
Using the feature that allows automatic scaling of compute instances ensures that the platform can cope with the demand fluctuations without human intervention. This elasticity helps maintain performance during peak times and reduces costs during inactivity by modifying the number of active instances in response to traffic changes. Reserved instances would lead to underutilization during off-peak times. Load balancers distribute traffic but do not adjust computing capacity. Serverless containers streamline deployment but would not provide the on-demand scaling based on traffic volume.
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