{"id":18727405,"url":"https://github.com/nasdin/example-ml-cicd-fullstack","last_synced_at":"2025-11-12T01:30:20.217Z","repository":{"id":39146647,"uuid":"252461734","full_name":"Nasdin/Example-ML-CICD-fullstack","owner":"Nasdin","description":"Example how to run ML with DevOps","archived":false,"fork":false,"pushed_at":"2023-01-04T15:10:07.000Z","size":35123,"stargazers_count":0,"open_issues_count":23,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-12-28T13:43:26.625Z","etag":null,"topics":["datascience","devops","ml","mlflow","python"],"latest_commit_sha":null,"homepage":"","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Nasdin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-04-02T13:22:01.000Z","updated_at":"2020-04-26T03:27:48.000Z","dependencies_parsed_at":"2023-02-02T17:04:01.305Z","dependency_job_id":null,"html_url":"https://github.com/Nasdin/Example-ML-CICD-fullstack","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nasdin%2FExample-ML-CICD-fullstack","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nasdin%2FExample-ML-CICD-fullstack/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nasdin%2FExample-ML-CICD-fullstack/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nasdin%2FExample-ML-CICD-fullstack/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Nasdin","download_url":"https://codeload.github.com/Nasdin/Example-ML-CICD-fullstack/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239599061,"owners_count":19665911,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["datascience","devops","ml","mlflow","python"],"created_at":"2024-11-07T14:17:39.580Z","updated_at":"2025-11-12T01:30:20.173Z","avatar_url":"https://github.com/Nasdin.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"## ML Example App\n### An Example of how to deploy ML model and scale with kubernetes\n\n## Requirements: Docker \u0026 Kubernetes\nEnsure that your kubectl is connected to a kubernetes cluster\nThis can be done by modifying your kubectl config\nwith a system path pointing to KUBECONFIG\n### Private Docker Registry\nYou must have a docker registry for the docker images to be sent to.\nindicate the host to your docker registry in the file `docker-registry-address`\n\n## Local kubernetes setup\nIf you dont have a kubernetes cluster, try microk8s\nAnd then install kubectl separately:\n#### Configure your kubectl with\n`cat microk8s.config \u003e\u003e ~/.kube/config`\nThen add `export KUBECONFIG=~/.kube/config`\ninto your bashrc\n#### Installing Docker Registry\nOn microk8s, enable docker registry with \n`microk8s.enable registry`\n\n## Allowing docker to push to private docker registry\nAdd the address of the docker private registry into your insecure-registries\nE.g http://localhost:32000\nFor Mac/Windows:\n\n```open the settings, goto the daemon tab and then pop in your registry’s URL in the “Insecure registries”``` \nRestart docker\n\n#### For Ubuntu:\n \nvim `/etc/docker/daemon.json`\n```\n{\n    \"insecure-registries\" : [\"localhost:32000\"]\n}\n```\nRestart your docker service with systemctl restart docker\n\n## Installation instructions\nJust run the included install.sh file\n\n`sh install.sh`\n\n## Removal\nJust run the included uninstall.sh file\n\n`sh uninstall.sh`\n\n# Features\n1. Frontend --\u003e UI built with ReactJS to request predictions\n2. Backend --\u003e Backend built with Python Flask for \n            \n            sanitize inputs\n            Track \u0026 record predictions\n            REST API for model serving\n            Requests Model Serving API\n            REST API for past predictions\n            \n3. Mushroom Model --\u003e ML Pipeline built with MLFlow\n \n          Website for viewing model training / track models\n          WorkFlow for Training and deploying model\n          Model trained as a container\n          Model deployed as an isolated container\n          ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnasdin%2Fexample-ml-cicd-fullstack","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnasdin%2Fexample-ml-cicd-fullstack","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnasdin%2Fexample-ml-cicd-fullstack/lists"}