Gunicorn Integrations

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BudgetML provides an excellent option for practitioners who wish to quickly launch their models to an endpoint without the burden of extensive time, financial investment, or effort required to navigate the intricacies of complete deployment. The inspiration behind BudgetML arose from the challenges of locating an accessible and cost-effective approach for rapidly bringing a model into production. Using cloud functions can lead to issues with memory limitations and increased expenses when scaling, and Kubernetes clusters often introduce unnecessary complexity for the deployment of a single model. Starting from ground zero necessitates a grasp of various concepts like SSL certificate generation, Docker, REST APIs, Uvicorn/Gunicorn, and backend servers, which most data scientists may not be well-versed in. By addressing these challenges, BudgetML provides a solution that emphasizes speed, simplicity, and usability for developers. Although it may not cater to extensive production environments, BudgetML proves to be a valuable resource for quickly setting up a server at minimal expenses. In this way, BudgetML not only simplifies the deployment process but also allows data scientists to concentrate on refining their models rather than getting caught up in the complexities of deployment logistics. Ultimately, this makes BudgetML a practical choice for those looking to enhance their workflow and efficiency in model deployment.