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What NVIDIA’s Latest AI Platform Means for IT Operations
NVIDIA just announced the world’s first Industrial AI Cloud, in partnership with global telecoms and enterprises. Powered by up to 10,000 GPUs, this AI cloud isn’t just a compute milestone, it’s a signal to CIOs: AI infrastructure is entering the operations layer.
This shift means enterprise IT teams must rethink how they manage, automate, and secure endpoints in an AI-saturated workplace. Because while data scientists train models, IT teams are the ones who’ll run them efficiently at scale.
Why This Matters to IT Operations Leaders
- More AI apps = more endpoint complexity.
Every new model adds dependencies, memory loads, and crash risks. Traditional ITSM tools aren’t built for real-time AI service support.
- Shadow AI is coming.
Teams will start launching GenAI pilots without security oversight. Without automation, enforcing policy will become chaos.
- AI success depends on infrastructure health.
If patching lags or endpoints fail, even the smartest models won’t save the business.
How Automation Helps IT Ride the AI Cloud Wave
With Anakage’s automation-first platform, IT teams can:
- Auto-detect and pre-configure endpoints for AI workloads
- Enforce compliance on high-performance machines using real-time health telemetry
- Guide users with in-app workflows for AI app crashes or setup
- Use self-healing agents to handle spikes in memory, disk I/O, and GPU load
It’s like having a CoPilot – not just for code, but for every IT task AI might disrupt.
FAQ: What Should CIOs Be Thinking About?
Q: Do we need Anakage if we already have SCCM or Intune?
A: Those tools don’t offer proactive remediation, DEX-level visibility, or low-code workflow automation. Anakage does – all in one agent.
Q: Can we monitor high-performance endpoints used in AI labs?
A: Yes. Anakage supports GPU/memory telemetry, policy enforcement, and compliance even in air-gapped or offline environments.
Schedule a demo today to see how a global OEM used Anakage to self-resolve 70% of IT issues.
