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applearner

Deep learning project that aims to address the challenge of accurately estimating resource requirements for workloads running on the Red Hat OpenShift Container Platform. The objective is to dynamically adjust these estimations during the course of application execution, optimizing resource utilization and avoiding under- and overutilization

apps

Operate-first application manifests

cco_ui

Web-based UI for the CCO

ci-assitiverobot

cloud-price-analysis-public

cloudcostoptimizer

The goal of this project is to design and implement a scalable multi-cloud cost optimizer capable of calculating the best scheme for deploying a given arbitrary complex workload over a public (hybrid) cloud, thus reducing the involved monetary costs

deploy-resnet50-model-using-triton

This guide provides step-by-step instructions for establishing an inference infrastructure to deploy deep learning pipelines utilizing the Triton server. The purpose is to deploy a ResNet50 model and leverage the Triton server for efficient inference.

dynamicalgorithmsimulationenv

focus-time-app