joblet

Joblet: Enterprise-Grade Job Execution Platform

A Docker Alternative Built for Production Workloads

Joblet is a native Linux job execution platform that provides secure process isolation, comprehensive resource management, and enterprise-ready orchestration without the overhead of containers.

🚀 Why Joblet?

Docker Alternative for Modern Infrastructure

Unlike traditional containerization solutions, Joblet leverages Linux namespaces and cgroups directly, providing:

• 🔒 Better Security: Process-level isolation without container escape vulnerabilities
• ⚡ Superior Performance: Direct syscall execution without container runtime overhead
• 💰 Cost Efficiency: Lower resource consumption and faster startup times
• 🎯 Simpler Operations: No image management, registries, or container complexity

Enterprise Production Ready

• 🏢 mTLS Authentication: Certificate-based security with role-based access control
• 📊 Advanced Monitoring: Real-time metrics with comprehensive system observability
• 🌐 Network Isolation: Custom networks with traffic control and bandwidth limiting
• 💾 Persistent Storage: Volume management with size limits and type flexibility
• 🔄 Workflow Orchestration: YAML-based job dependencies with validation

Developer Experience First

• 🖥️ Cross-Platform CLI: Works seamlessly on Linux, macOS, and Windows
• 🎨 Modern Web UI: React-based interface for visual workflow management
• 📱 Real-Time Logs: Live log streaming with filtering and search
• 🛠️ Runtime System: Pre-built environments (Python ML, Java 17/21, Go)

🎨 Visual Interface

Comprehensive System Monitoring

Advanced Workflow Management

🎯 Industry Use Cases

CI/CD & DevOps

# Replace Docker in CI pipelines
rnx run --runtime=python:3.11-ml pytest tests/
rnx run --runtime=java:21 mvn clean install
rnx run --runtime=node:18 npm run build

Data Engineering & Analytics

# Isolated data processing with resource limits
rnx run --max-memory=8192 --max-cpu=400 \
        --volume=data-lake \
        --runtime=python:3.11-ml \
        python process_big_data.py

Microservices & Testing

# Network-isolated service testing
rnx network create test-env --cidr=10.10.0.0/24
rnx run --network=test-env --runtime=java:17 ./service-a
rnx run --network=test-env --runtime=python:3.11 ./service-b

Workflow Orchestration

# ml-pipeline.yaml
jobs:
  data-extraction:
    command: "python3"
    args: ["extract.py"]
    runtime: "python:3.11-ml"
    resources:
      max_memory: 2048
      max_cpu: 100
    
  model-training:
    command: "python3" 
    args: ["train.py"]
    runtime: "python:3.11-ml"
    requires:
      - data-extraction: "COMPLETED"
    resources:
      max_memory: 8192
      max_cpu: 400

# Execute and monitor workflow with job names
rnx run --workflow=ml-pipeline.yaml
rnx status --workflow 1

# Output shows human-readable job names and dependencies:
# JOB ID          JOB NAME             STATUS       EXIT CODE  DEPENDENCIES        
# -----------------------------------------------------------------------------------------
# 42              data-extraction      COMPLETED    0          -                   
# 43              model-training       RUNNING      -          data-extraction     

SRE & Reliability Engineering

# Resource-bounded health checks with timeout
rnx run --max-cpu=10 --max-memory=64 \
        --runtime=python:3.11 \
        python health_check.py

# Isolated incident response tooling
rnx run --network=isolated \
        --volume=incident-logs \
        ./debug-analyzer.sh

AI Agent Development

# Multi-agent system with isolation
rnx run --max-memory=4096 --runtime=python:3.11-ml \
        python agent_coordinator.py

rnx run --max-memory=2048 --runtime=python:3.11-ml \
        --network=agent-net \
        python data_processing_agent.py

rnx run --max-memory=1024 --runtime=python:3.11-ml \
        --network=agent-net \
        python monitoring_agent.py

📊 Performance Advantages

Feature	Docker	Joblet
Startup Time	2-5 seconds	50-200ms
Memory Overhead	50-100MB per container	5-10MB per job
Security	Container escape risks	Direct process isolation
Networking	Complex bridge setup	Native Linux networking
Storage	Image layers & volumes	Direct filesystem access
Monitoring	External tools required	Built-in comprehensive metrics

🏗️ Architecture Benefits

Native Linux Integration

• Cgroups v2: Advanced resource control and accounting
• Namespaces: PID, network, mount, IPC, UTS isolation
• No Virtualization: Direct hardware access for maximum performance
• System Integration: Seamless integration with existing infrastructure

Enterprise Security Model

• mTLS Everywhere: Certificate-based authentication for all communications
• Role-Based Access: Granular permissions (admin, operator, viewer)
• Process Isolation: Each job runs in isolated namespace
• Resource Boundaries: Hard limits prevent resource exhaustion

Scalable Design

• Stateless Architecture: Easy horizontal scaling
• Event-Driven: Real-time job state management
• API-First: Full gRPC API for integrations
• Web Management: Modern React UI for operations teams

📚 Complete Documentation

Getting Started

• Quick Start Guide - Get up and running in 5 minutes
• Installation Guide - Detailed installation for all platforms
• Configuration - Complete configuration reference

User Guides

• RNX CLI Reference - Complete command reference with examples
• Job Execution Guide - Running jobs with resource limits and isolation
• Workflows Guide - YAML workflows with dependencies and orchestration
• Runtime System - Pre-built environments for instant execution
• Volume Management - Persistent and temporary storage
• Network Management - Network isolation and custom networks
• Web Admin UI - React-based interface for visual management

Advanced Topics

• Security Guide - mTLS, authentication, and best practices
• Runtime Deployment - Zero-contamination runtime deployment
• Runtime Advanced Scenarios - Enterprise patterns and CI/CD
• Deployment Guide - Production deployment strategies
• Troubleshooting - Common issues and solutions

Reference

• API Reference - Complete gRPC API documentation
• Architecture - System design and architecture deep-dive
• Storage Guide - Data persistence and storage management

🚀 Quick Start Example

# Install Joblet (see Installation Guide for details)
curl -sSL https://install.joblet.org | bash

# Run your first job
rnx run echo "Hello, Joblet!"

# Create a workflow
cat > ml-pipeline.yaml << EOF
jobs:
  analyze:
    command: "python3"
    args: ["analyze.py", "--data", "/data/input.csv"]
    runtime: "python:3.11-ml"
    volumes: ["data-volume"]
EOF

# Execute the workflow
rnx run --workflow=ml-pipeline.yaml

🎯 Value Proposition

For DevOps Teams

• Simplified Infrastructure: No container registry or image management
• Better Security: Process isolation without container escape risks
• Cost Savings: Lower resource overhead and operational complexity
• Native Integration: Works with existing Linux infrastructure

For Development Teams

• Faster Iteration: Instant job startup without image builds
• Better Debugging: Direct access to processes and filesystems
• Flexible Environments: Runtime system with pre-built environments
• Modern Tooling: CLI and web UI designed for developer productivity

For Operations Teams

• Comprehensive Monitoring: Built-in metrics and real-time observability
• Enterprise Security: mTLS and role-based access control
• Workflow Management: Visual interface for complex job orchestration
• Production Ready: Designed for enterprise scale and reliability

For SRE Teams

• Reliability Engineering: Process isolation prevents cascading failures
• Resource Governance: Hard limits prevent resource exhaustion incidents
• Observability: Built-in metrics and alerting for proactive monitoring
• Incident Response: Direct process access for faster debugging and resolution

For AI Agent Developers

• Agent Isolation: Run multiple AI agents safely with process boundaries
• Resource Control: Prevent AI workloads from consuming excessive resources
• Model Execution: Pre-built ML runtimes with GPU support and package management
• Workflow Orchestration: Chain AI agents with dependencies and data flow control

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Ready to modernize your job execution infrastructure? Start with our Quick Start Guide and experience the Joblet difference.

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