{"id":38448602,"url":"https://github.com/adrien-legros/rhods-mnist","last_synced_at":"2026-01-17T04:44:00.790Z","repository":{"id":156005853,"uuid":"602923730","full_name":"adrien-legros/rhods-mnist","owner":"adrien-legros","description":"Data science pipelines and model serving using Red Hat OpenShift Data Science","archived":false,"fork":false,"pushed_at":"2025-03-27T14:57:29.000Z","size":14700,"stargazers_count":9,"open_issues_count":0,"forks_count":6,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-27T15:50:28.820Z","etag":null,"topics":["data-science","model-serving","openshift-ai","pipelines","redhat","rhoai","rhods"],"latest_commit_sha":null,"homepage":"","language":"Python","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/adrien-legros.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-02-17T08:31:49.000Z","updated_at":"2025-03-27T14:57:33.000Z","dependencies_parsed_at":null,"dependency_job_id":"2654b8b6-b2c2-486f-9b97-93fc8b4e07e6","html_url":"https://github.com/adrien-legros/rhods-mnist","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"purl":"pkg:github/adrien-legros/rhods-mnist","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-legros%2Frhods-mnist","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-legros%2Frhods-mnist/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-legros%2Frhods-mnist/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-legros%2Frhods-mnist/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/adrien-legros","download_url":"https://codeload.github.com/adrien-legros/rhods-mnist/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/adrien-legros%2Frhods-mnist/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28495969,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-17T04:31:57.058Z","status":"ssl_error","status_checked_at":"2026-01-17T04:31:45.816Z","response_time":85,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["data-science","model-serving","openshift-ai","pipelines","redhat","rhoai","rhods"],"created_at":"2026-01-17T04:44:00.695Z","updated_at":"2026-01-17T04:44:00.775Z","avatar_url":"https://github.com/adrien-legros.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MLOps with Openshift AI\n\n## About\n\nThis demo illustrates MLOps features of Openshift AI and extensions to Openshift (streaming, ELT, ...).\n\n## Content\n\n- Openshift AI MLOps features (notebooks, automated pipeline creation through git, experimentations, artifacts, model registry)\n- Streaming with kafka\n- Data transformation with camel\n- Kserve features (usage of transformer for pre/post processing)\n\n## Deployment\n\nThe following procedure will deploy all the demo components. If you want to deploy only specific components, look at [this documentation](./manifests/readme.md).\n\n### Operators \n\nInstall the operators.\n\n```shell\noc apply -k ./manifests/operators/\n```\n\nWait for the installations to complete. Confirm that all operators are ready.\n\n\n### Operator instances\n\nDeploy the data science cluster and the knative instances by runnning:\n\n```shell\noc apply -k ./manifests/operators-instances/\n```\n\n### Demo environment.\n\n\nDeploy the demo instances:\n\n```shell\nhelm template ./manifests/instances/core | oc apply -f -\noc kustomize ./manifests/instances/automated-pipelines/ --enable-helm | oc apply -f -\noc kustomize ./manifests/instances/streaming/ --enable-helm | oc apply -f -\n\n```\n\n### Required manual setup on Openshift AI\n\n1. Data science pipeline\n\nGo to the digit-recognition data science project. On the pipeline tab, create a new pipeline server using one of the data connection available. Change the bucket name to \"ml-pipelines\" for clarity. Wait for the pipeline server creation to complete.\n\n2. Notebook creation\n\nCreate a new workbench. Use the standard data science container image. Add the \"data\" data connection. Wait for the notebook creation. Open it and clone https://github.com/adrien-legros/rhods-mnist-model.\n\n3. Model registry setup\n\nOn the settings side of Openshift AI choose model registry. Create a new one with the settings:\n- Name: model-regisgtry\n- Host: mysql.mnist\n- Port: 3306\n- Database name: modelregistry\n\nWait for the model registry creation to complete.\n\n### Credentials: username / password\n\n- Openshift AI: your openshift user (needs to be a openshift ai admin)\n- Gitea: data-scientist-1 / rhods\n- Grafana: admin / admin\n\n## [UNCOMPLETE] Architecture\n\n![global-architecture](./docs/schemas/global-architecture.png)\n\nThe schema does to reflect:\n- Model registry\n- Experimentations and metric tracking\n- Kserve as a variation for the streaming workflow\n\n## [DEPRECATED] Walkthrough\n\nDeprecated but gives some steps for the demo.\nWalkthourgh and highlights can be found on [this documentation](./docs/walkthrough.md).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadrien-legros%2Frhods-mnist","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fadrien-legros%2Frhods-mnist","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fadrien-legros%2Frhods-mnist/lists"}