Treffer: Leveraging cloud data to evaluate performance metrics for docker containers.

This research investigates the performance characteristics of Docker containers across three deployment environments: local machines, virtual machines, and cloud platforms which are the three categories that are commonly used in today's technology environment. The study has a sound research method that utilizes cloud data and entails the use of scripts developed specifically for the study and built-in monitoring tools to evaluate key performance indicators. These metrics are the CPU usage, memory usage, disk I/O rate, and load testing; which gives a general assessment of the strengths and weaknesses of each environment. Results show that local Docker containers are significantly faster in the usage of resources and I/O operations than the remote ones, especially when the workload is high and large files are processed. This efficiency is since containers are lightweight and share the host operating system kernel, thus, they do not have much overhead and can easily access resources of the host operating system. Though cloud platforms become potential rivals when focusing on the aspects of flexibility, manageability, and having access to managed services, they tend to exhibit higher latency for I/O-bound operations. In conclusion, the choice of the proper deployment environment is defined by the peculiarities of the application, by the need to achieve the highest performance, to optimize costs and to provide the possibility of the application's further expansion. [ABSTRACT FROM AUTHOR]