ghost-compute 0.1.0

Intelligent serverless orchestration for data platforms - eliminate idle cluster waste and cold start latency

Ghost Compute

Intelligent Serverless Orchestration for Data Platforms

Ghost eliminates the $44.5B annual waste from idle clusters and cold start latency in enterprise data infrastructure. Drop-in optimization for Databricks, EMR, Synapse, and Spark workloads.

The Problem

Enterprises face an impossible tradeoff:

Option	Problem
Keep clusters warm	Pay for 24/7 idle compute (~30% waste)
Cold start on-demand	5-35 minute startup delays, missed SLAs
Vendor serverless	Premium pricing, vendor lock-in, limited control

Ghost solves this by providing intelligent cluster orchestration that delivers sub-second start times while eliminating idle waste.

Key Features

🔮 Ghost Predict

ML-powered predictive provisioning that pre-warms resources before you need them.

💤 Ghost Hibernate

State preservation that snapshots clusters to object storage for instant resume.

🏊 Ghost Pool

Cross-workload resource sharing that maximizes utilization across teams.

⚡ Ghost Spot

Autonomous spot/preemptible instance management with graceful failover.

📊 Ghost Insight

Real-time cost attribution and optimization recommendations.

Quick Start

Installation

One command to install Ghost Compute with all platforms:

pip install ghost-compute

This single install includes support for:

• Databricks (Azure, AWS, GCP)
• Amazon EMR
• Azure Synapse Analytics
• Google Cloud Dataproc

Install from source:

git clone https://github.com/ghost-ai-dev/ghost-compute.git
cd ghost-compute
pip install -e .

Basic Usage

from ghost import GhostClient

# Initialize Ghost
ghost = GhostClient(
    platform="databricks",
    credentials_path="~/.ghost/credentials.json"
)

# Enable intelligent orchestration
ghost.optimize(
    workspace_id="your-workspace",
    strategies=["predict", "hibernate", "spot"],
    target_savings=0.40  # 40% cost reduction target
)

# Monitor savings
stats = ghost.get_stats()
print(f"Monthly savings: ${stats.savings_usd:,.2f}")
print(f"Cold starts eliminated: {stats.cold_starts_prevented}")

CLI Usage

# View supported platforms
ghost platforms

# Connect to your platform
# Databricks
ghost connect databricks --workspace-url https://xxx.cloud.databricks.com --token YOUR_TOKEN

# AWS EMR
ghost connect emr --profile default --region us-east-1

# Azure Synapse
ghost connect synapse --subscription-id YOUR_SUB_ID --resource-group YOUR_RG

# Google Dataproc
ghost connect dataproc --project-id YOUR_PROJECT --region us-central1

# Analyze current waste
ghost analyze --output report.json

# Enable optimization
ghost optimize --strategies predict,hibernate,spot

# List clusters
ghost clusters

# View optimization insights
ghost insights

Supported Platforms

All platforms are included in the single pip install ghost-compute package.

Platform	Status	Features
Databricks	✅ GA	Predict, Hibernate, Pool, Spot, Insight
Amazon EMR	✅ GA	Predict, Hibernate*, Spot, Pool, Insight
Azure Synapse	✅ GA	Predict, Hibernate (auto-pause), Pool, Insight
Google Dataproc	✅ GA	Predict, Hibernate*, Preemptible VMs, Pool, Insight
Cloudera CDP	🚧 Alpha	Insight only (coming soon)
Self-managed Spark	🚧 Alpha	Pool, Spot (coming soon)

*EMR and Dataproc hibernation works via cluster termination with state preservation for fast recreation.

Architecture

┌─────────────────────────────────────────────────────────────┐
│                    YOUR APPLICATION                          │
│         (Databricks / EMR / Synapse / Dataproc)             │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│                      GHOST LAYER                             │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐  │
│  │   Predict   │  │  Hibernate  │  │        Spot         │  │
│  │  Scheduler  │  │   Manager   │  │    Orchestrator     │  │
│  └─────────────┘  └─────────────┘  └─────────────────────┘  │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐  │
│  │    Pool     │  │   Insight   │  │     Multi-Cloud     │  │
│  │   Manager   │  │   Engine    │  │     Abstraction     │  │
│  └─────────────┘  └─────────────┘  └─────────────────────┘  │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│                  CLOUD INFRASTRUCTURE                        │
│              (AWS / Azure / GCP / On-Prem)                  │
└─────────────────────────────────────────────────────────────┘

How It Works

1. Predictive Provisioning

Ghost analyzes your workload patterns to predict when clusters will be needed:

# Ghost learns from historical patterns
# - Scheduled jobs (cron patterns)
# - User activity (login times, query patterns)
# - Data arrival (streaming triggers)
# - Seasonal trends (end of month, quarterly)

# Pre-warms clusters 30-60 seconds before needed
# Result: Sub-second perceived start time

2. State Hibernation

Instead of terminating clusters, Ghost preserves state:

# Traditional approach:
# Terminate → Cold start (5-35 min) → Re-initialize

# Ghost approach:
# Hibernate → Snapshot to S3 → Resume in <5 sec

3. Intelligent Pooling

Share warm resources across workloads:

# Team A finishes job at 2:00 PM
# Team B starts job at 2:05 PM
# Ghost transfers warm instances → Zero cold start for Team B

4. Spot Orchestration

Maximize savings with automatic spot management:

# Ghost automatically:
# - Uses spot instances for interruptible workloads
# - Monitors interruption signals
# - Checkpoints state before termination
# - Fails over to on-demand gracefully

Configuration

Environment Variables

GHOST_API_KEY=your-api-key
GHOST_PLATFORM=databricks
GHOST_WORKSPACE_URL=https://xxx.cloud.databricks.com
GHOST_LOG_LEVEL=INFO

Configuration File

# ghost.yaml
platform: databricks
workspace_url: https://xxx.cloud.databricks.com

strategies:
  predict:
    enabled: true
    lookahead_minutes: 60
    confidence_threshold: 0.8

  hibernate:
    enabled: true
    idle_timeout_minutes: 10
    storage_backend: s3
    storage_bucket: ghost-hibernate-states

  spot:
    enabled: true
    max_spot_percentage: 80
    fallback_to_ondemand: true
    interruption_buffer_seconds: 120

  pool:
    enabled: true
    cross_team_sharing: true
    max_idle_instances: 10

  insight:
    enabled: true
    cost_alerts: true
    alert_threshold_usd: 1000

exclusions:
  - cluster_name: "production-critical-*"
  - tag: "ghost:exclude"

Pricing

Ghost operates on a savings-share model:

Tier	Monthly Compute Spend	Ghost Fee
Starter	< $50K	25% of savings
Growth	$50K - $250K	20% of savings
Enterprise	> $250K	Custom

No savings = No payment. We only charge when we deliver results.

Benchmarks

Metric	Before Ghost	After Ghost	Improvement
Average cold start	8.5 min	0.8 sec	99.8% faster
Idle compute waste	32%	4%	87% reduction
Monthly spend ($100K baseline)	$100,000	$58,000	42% savings
SLA misses (5-min threshold)	23/month	0/month	100% eliminated

Documentation

• Getting Started Guide
• Platform Integration
• API Reference
• Configuration Options
• Best Practices
• Troubleshooting

Examples

• Databricks Notebook Integration
• EMR Step Function Integration
• Airflow DAG with Ghost
• Terraform Module
• Kubernetes Operator

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

# Development setup
git clone https://github.com/ghost-ai-dev/ghost-compute.git
cd ghost-compute
python -m venv venv
source venv/bin/activate
pip install -e ".[dev]"
pytest

Security

• SOC 2 Type II certified
• No data leaves your cloud environment
• All state stored in your own S3/Blob/GCS buckets
• Role-based access control
• Audit logging

Report security issues to [e-mail]

License

Apache License 2.0 - see LICENSE

Support

• 📧 Email: [e-mail]
• 💬 Slack: ghost-compute.slack.com
• 📖 Docs: docs.ghost-compute.io
• 🐛 Issues: GitHub Issues

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Built by Ghost AI | Eliminating waste in enterprise data infrastructure