AeroWeight
An Intelligent Data Gravity Engine for Multi-Cloud Compute Routing
Cloud Computing / Data Gravity Optimization
Overview
AeroWeight is an intelligent orchestration engine that routes computational workloads across multiple cloud providers by modeling data gravity-the tendency of data to attract processing. The system analyzes data location, volume, movement costs, network latency, and compute pricing to make optimal placement decisions using reinforcement learning.
Key Features
Data Gravity Modeling
Quantifies the 'pull' of each dataset based on size, access frequency, and inter-dataset dependencies.
Multi-Cloud Cost-Aware Routing
Evaluates compute, storage, and egress costs across AWS, Azure, GCP in real time.
Predictive Workload Characterization
Forecasts resource requirements and data movement needs before jobs start.
Adaptive RL Controller
Dynamically refines routing policies based on observed cost and performance.
Policy Compliance Engine
Enforces geo-fencing, data residency, and regulatory constraints.
Simulation Sandbox
What-if experiments with historical workload traces.
Technology Stack
Algorithms & Methods
Data Gravity Model
Quantitative model for dataset attraction based on size and access patterns.
Reinforcement Learning
Policy gradient methods for adaptive routing optimization.
Cost Optimization
Multi-cloud cost function evaluation with egress and compute pricing.