Abstract
Horizontal scalability is very crucial in cloud applications. For microservices applications that are installed in AWS cloud environment, auto-scaling feature will automatically scale applications based on the configurations. Amazon ECS can calculate service performance as per CPU and memory resources consumed at a point in time and it provides data to CloudWatch metrics, such as ECSServiceAverageCPUUtilization and ECSServiceAverageMemoryUtilization. This paper discusses how auto-scaling can be achieved using the metrics and applying the scaling policies proportionally. Details of how the metrics collection strategies can be used for Application Auto-Scaling to scale services installed in the AWS cloud environment are discussed. It is observed that auto-scaling not only supports scaling up the instances in peak hours but also scales down the instances when there is minimal or no load on the application. Auto-scaling keeps monitoring the instance metadata. It helps in identifying the health status of the instances. It is observed that in peak load situations, if there is a demand for instant user requests or there is a surprise increase in user transactions increase in user requests, auto-scaling automatically adds more resources to handle the situation, which makes the system fault tolerant.
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Singh, A., Singh, V., Aggarwal, A. (2024). Improving the Application Performance by Auto-Scaling of Microservices in a Containerized Environment in High Volumed Real-Time Transaction System. In: Bhardwaj, A., Pandey, P.M., Misra, A. (eds) Optimization of Production and Industrial Systems. CPIE 2023. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-99-8343-8_27
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