90ea18555c
Some checks failed
Security Scan / Security Analysis (push) Waiting to run
Security Scan / Native Library Security (push) Waiting to run
Verification & Maintenance / V.1 - Schema Drift Detection (push) Waiting to run
Verification & Maintenance / V.4 - Custom Go Vet Analyzers (push) Waiting to run
Verification & Maintenance / V.7 - Audit Chain Integrity (push) Waiting to run
Verification & Maintenance / V.6 - Extended Security Scanning (push) Waiting to run
Verification & Maintenance / V.10 - OpenSSF Scorecard (push) Waiting to run
Verification & Maintenance / Verification Summary (push) Blocked by required conditions
Build Pipeline / Build Binaries (push) Failing after 2m4s
Build Pipeline / Build Docker Images (push) Has been skipped
Build Pipeline / Sign HIPAA Config (push) Has been skipped
Build Pipeline / Generate SLSA Provenance (push) Has been skipped
Checkout test / test (push) Successful in 5s
CI Pipeline / Test (push) Failing after 1s
CI Pipeline / Dev Compose Smoke Test (push) Has been skipped
CI Pipeline / Security Scan (push) Has been skipped
CI Pipeline / Test Scripts (push) Has been skipped
CI Pipeline / Test Native Libraries (push) Has been skipped
CI Pipeline / Native Library Build Matrix (push) Has been skipped
Contract Tests / Spec Drift Detection (push) Failing after 16s
Contract Tests / API Contract Tests (push) Has been skipped
Deploy API Docs / Build API Documentation (push) Failing after 5s
Deploy API Docs / Deploy to GitHub Pages (push) Has been skipped
Documentation / build-and-publish (push) Failing after 44s
CI Pipeline / Trigger Build Workflow (push) Failing after 0s
- Add new vLLM workflow documentation (vllm-workflow.md) - Update scheduler-architecture.md with Plugin GPU Quota and audit logging - Add See Also sections to jupyter-workflow.md, quick-start.md, configuration-reference.md for better navigation - Update landing page and index with vLLM and scheduler links - Cross-link all documentation for improved discoverability
2.3 KiB
2.3 KiB
| title |
|---|
| Fetch ML Documentation |
Fetch ML - Secure Machine Learning Platform
A secure, containerized platform for running machine learning experiments with role-based access control and comprehensive audit trails.
Quick Start
New to the project? Start here!
# Clone the repository
git clone https://github.com/your-username/fetch_ml.git
cd fetch_ml
# Start development stack with monitoring
make dev-up
# Run basic tests
make test-unit
# Then follow the Quick Start guide
# docs/src/quick-start.md
Quick Navigation
Getting Started
- Getting Started Guide - Complete setup instructions
- Simple Install - Quick installation guide
Security & Authentication
- Security Overview - Security best practices
- API Key Process - Generate and manage API keys
- User Permissions - Role-based access control
Configuration
- Environment Variables - Configuration options
- Smart Defaults - Default configuration settings
🛠️ Development
- Architecture - System architecture and design
- Scheduler Architecture - Job scheduler and service management
- CLI Reference - Command-line interface documentation
- Testing Guide - Testing procedures and guidelines
- Jupyter Workflow - Jupyter notebook services
- vLLM Workflow - LLM inference services
- Queue System - Job queue implementation
Production Deployment
- Deployment Guide - Production deployment instructions
- Performance & Monitoring - Monitoring and observability
- Operations Guide - Production operations
Features
- Secure Authentication - RBAC with API keys, roles, and permissions
- Containerized - Podman-based secure execution environments
- Database Storage - SQLite backend for user management (optional)
- Audit Trail - Complete logging of all actions
- Production Ready - Security audits, systemd services, log rotation
Need Help?
- Documentation: Use the navigation menu on the left
- Quick help:
make help - Tests:
make test-unit
Happy ML experimenting!