Effective management of this collection of systems and services involves skillful instrumentation and lightning-fast root cause analysis when things go awry. Rule4 has the unique combination of experience and skills to span the breadth of this complex landscape.
Machine Learning (ML/AI) Ecosystem Security
Ensure your AI/ML implementations start off on the right foot — and stay that way.
AIOps is the buzzword — AI for IT operations. But what about its cousin, IT operations for AI?
A production-grade, fully functional ecosystem to support the use of AI/ML in your enterprise environment requires, among other things, a number of supporting subsystems:
Data collection and ingestion
Orchestration engine
Auto scale-up/scale-down
ETL
API gateway(s)
Configuration management
Cybersecurity protection (IDS, IPS, IAM, event logging, certificate management, authentication, etc.)
Server infrastructure (cloud, on-premise, or both)
Application platform scaffolding
Network/SDN management (VPN tunnels, routing, bandwidth management, etc.)
Monitoring
Data validation and verification
Without these subsystems, the core AI/ML engine (even in an IaaS/PaaS/SaaS) environment cannot exist — not to mention thrive — in a production environment.
Build your ML/AI house on a solid foundation!
Let's discuss your organization’s ML/AI ecosystem security challenges and opportunities.
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