Container × GPU × AI Pod Platform
AI Compute Platform - VIDAware Containerization
An Elastic Runtime and Real-Time Scheduling Hub Built Around AI Service Units (Pods)
Built around an AI containerized compute platform, each AI model, video analytics task, and event inference service is packaged as an independent AI service unit (Pod). According to real-time requirements across city sites, workloads can be automatically assigned to different GPU compute nodes, enabling real-time scaling, uninterrupted operation, and cross-node fault tolerance for city-scale AI computing.
Distributed Compute
Idle resources / Unmanaged
VIDAware Compute Containerization System Architecture
Elastic Container × GPU × AI Pod Architecture
VIDAWARE × AI Pod Orchestration
Multi-Source Streams → AI Pod → Dynamic GPU Resource Scheduling
Management & Operations Layer: Commercialization and Security
Ensures data security between tenants and supports compute-token-based business models.
Multi-Tenant Compute Token Billing
Measures resource usage across projects and converts it into token deductions. The chart shows token consumption by major tenants across different services.
Identity Authentication & Security
SSO / OIDC, API key management, and end-to-end TLS encryption.
Multi-Tenant Isolation
Namespace + RBAC ensures complete resource isolation between tenants.
Real-Time Alert System
Automatic alerts via Email / LINE / SMS.