What is AWS Auto Scaling?
Why Interviewers Ask This
Foundational questions like this help interviewers calibrate the rest of the interview. A confident, accurate answer signals that you have solid AWS / Cloud Computing basics — a prerequisite for any developer role.
Answer
AWS Auto Scaling automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. EC2 Auto Scaling components: (1) Auto Scaling Group (ASG): collection of EC2 instances treated as a logical unit. Define minimum, desired, and maximum capacity. Spans multiple AZs for high availability; (2) Launch Template: configuration for instances (AMI, instance type, key pair, security group, user data). Versioned — replace Launch Configurations. Supports Spot + On-Demand mix; (3) Scaling policies: Dynamic scaling — respond to CloudWatch alarms: Target Tracking: maintain a metric at a target value (e.g., keep average CPU at 70% — simplest, recommended); Step Scaling: scale by specific amounts based on alarm breach size; Simple Scaling: one adjustment per alarm. Scheduled scaling — pre-configured time-based scaling. Predictive Scaling — ML-based proactive scaling using historical data; (4) Health checks: EC2 health (instance status), ELB health (application health). Replace unhealthy instances automatically. Lifecycle hooks: pause instance launch or termination for custom actions (install software, drain connections). ASG with ELB: newly launched instances automatically register with target group. Warm pools: maintain pre-initialized stopped instances for faster scaling. Instance refresh: rolling update of all instances in ASG (useful for AMI updates). Cost optimization: Spot Instance integration with ASG — mix On-Demand (baseline) + Spot (scale) using Spot Fleet or mixed instances policy.
Pro Tip
If you're unsure about a detail, say so honestly and explain your reasoning. Interviewers respect candidates who can think through uncertainty rather than bluffing.