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👋 Hello, I'm Alexander Kharkevich
I design and build secure, scalable, and cloud-native infrastructure for MLOps platforms and enterprise DevOps teams.
My open-source work bridges the gap between machine learning experimentation and production readiness — with security, automation, and compliance as first-class concerns.
🛠 What I Build
I maintain mlflow-oidc, a plugin that enables:
- ✅ OIDC-based authentication for MLflow
- 🔐 Role- and group-based access control (RBAC/ABAC)
- 🧩 Integration with Azure AD, Keycloak, Auth0, and more
- 🏢 Secure multi-tenant MLflow deployments with access boundaries
Other areas I contribute to:
- Kubernetes controllers for GitHub App automation
- CI/CD pipelines for ML workloads
- Practical infrastructure patterns for regulated environments
🤝 Why Sponsor?
Your sponsorship helps me:
- Extend and maintain enterprise-ready MLOps tools
- Deliver features like audit logging, tenant isolation, and flexible auth flows
- Write architecture guides, deployment examples, and documentation
- Support the MLOps and DevSecOps open-source communities
🔗 Learn More
1 sponsor has funded kharkevich’s work.
Cover expenses for infrastructure, software licenses, and subscriptions
Featured work
-
mlflow-oidc/mlflow-oidc-auth
MLflow Tracking Server OIDC Auth plugin
Python 89 -
mlflow-oidc/mlflow-tracking-server-docker
Docker image: MLFlow tracking server with OpenID Connect authentication
Dockerfile 6