In today's dynamic cloud environment, ensuring application availability and cost efficiency is crucial. AWS Auto Scaling provides a seamless way to automatically adjust resources based on demand, optimizing performance while minimizing costs.
Auto Scaling options :
- Dynamic
- Predictive
- Scheduled
Dynamic : Automatic scaling can be configured to be dynamic. For example, suppose that you have a web application that
currently runs on three instances. You do not want the CPU utilization of the auto scaling group to exceed 70
percent for more than 2 minutes. You can configure your auto scaling group to scale automatically to meet this
need. The policy type determines how the scaling action is performed.
Predictive : AWS also provides predictive scaling
Predictive scaling uses machine learning models to predict your expected traffic (and Amazon EC2 usage), including daily and weekly patterns. These predictions use data that is collected from your actual Amazon EC2 usage and data points that are drawn from your own observations. The model needs historical data from at least 1 day to start making predictions. The model is re-evaluated every 24 hours to create a forecast for the next 48 hours.
Scheduled : By scaling based on a schedule, you can scale your application in response to predictable load changes. For
example, suppose that every week, the traffic to your web application starts to increase on Wednesday, remains partially
high on Thursday, and starts to decrease by Friday. In these situations, you can plan your scaling activities based on the predictable traffic patterns of your web application.
Note : loadfile.txt (copy the file content and create .py file in EC2 and paste. Now run .py file to increase CPU utilization temporarily)
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