A Containerized Cloud Computing Environments with Heterogeneous Task Co-Location

While microservices are able to process and communicate using lightweight techniques, finer tasks result in far more complex precedence restrictions. There is a wide range in the settings and costs of VMs (Virtual Machines) since different jobs have varying resource needs. In this study, we focus on the challenge of reducing the overall cost of renting by allocating the microservice activities of workflow tools to containers set up on demand virtual machines. Integer programming is used to create a mathematical model of the issue, and a foundation for an algorithm is presented. A task arranging heuristic is described for scheduling tasks with precedence constraints or separate assignments to available containers in response to resource needs that change over time. The Evaluation of Variance method is used to statistically calibrate all parameters and parts of the suggested algorithm framework on a large sample of random occurrences. The effectiveness of the suggested method is tested in several examples.