From my experience, the best features AWS Auto Scaling offers include target tracking scaling, which is very easy to configure. It also integrates with CloudWatch metrics, which is very important, and provides scheduled scaling, which helps some organizations. Two of my clients are using that. Predictive scaling for known traffic patterns and seamless integration with ALBs, ECS, and EC2 are also my favorite features of AWS Auto Scaling. Out of those features, target tracking scaling has saved me the most time and effort, making it my favorite feature. I find predictive scaling useful but in real-world scenarios, we rely more on dynamic scaling. AWS Auto Scaling has positively impacted my organization as it simplifies scaling decisions. I just need to define our target, such as CPU percentage, and AWS Auto Scaling handles everything. There is no need to fine-tune complex scaling rules, which has helped a lot. It has also significantly improved system reliability and reduced costs, as we no longer worry about sudden traffic spikes and we are not overpaying for idle resources. This has saved us significant costs, estimating around 25 to 30 percent after fine-tuning the scaling policy.
