AUTHOR: ToaBollua | DATE: Current Log | TAGS: AWS, Azure, EdgeAI, Hardware
Attention operatives: relying on a single cloud provider is a Single Point of Failure (SPOF) risk. The natural evolution of critical systems is a Multi-Cloud Architecture coupled with Edge Computing.
1. Edge Computing in AI Cameras
It makes no sense to send terabytes of raw video to the cloud for an AI to analyze and return a response with massive latency. Processing must occur at the "edge".
- Modern cameras must possess local NPUs (Neural Processing Units).
- The device captures, executes the computer vision model locally, and only sends the processed telemetry to the central network (e.g., "Anomaly detected in the perimeter").
- This reduces bandwidth consumption by 95% and allows for tactical operations without an internet connection.
2. Disaster Recovery: AWS / Azure Synchronization
For the core infrastructure, Disaster Recovery demands cross-redundancy.
If the main cluster resides on AWS (Amazon), database backups (PostgreSQL/Vectorial) must be replicated asynchronously to a passive cluster on Microsoft Azure. If an Amazon data center collapses, DNS traffic is automatically routed to Azure, keeping the entity alive.