Fleet operations

End-to-end fleet automation

Unify lifecycle automation, configuration control, observability, and real-time capacity APIs to reduce run-rate costs and operational risk.

Centralized control and visibility

Optimize AI fleet onboarding and lifecycle management

Control Center

Maximize GPU efficiency with unified lifecycle automation in one easy-to-use control panel.

  • Reduce operational overhead by automating routine tasks
  • Improve efficiency with node-level health tracking, reducing idle cycles
  • Operate complex multi-cluster environments with confidence

Observability

Reduce downtime, control costs, and track compliance with platform-grade telemetry.

  • Spot issues early, with telemetry across compute, storage, and networking
  • Predictable budgeting with integrated cost reporting and dashboards
  • Meet compliance and audit requirements with detailed operational metrics

Radar API

Eliminate uncertainty around GPU availability with real-time fleet signals for planning and procurement.

  • Enable effective planning with GPU availability and resolution metrics
  • Improve operational visibility with repair status and maintenance schedules
  • Support data-driven decision-making with a single API layer

Operational efficiency at fleet scale

Automated operations

Cut toil and run-rate spend by automating provisioning, scaling, patching, and retirement across fleets.

Actionable telemetry

Turn end-to-end observability into lower MTTD (mean time to detect) and higher utilisation with dashboards, alerts, and cost reporting that feed automated remediation and optimisation

Real-time capacity

Make capacity decisions with confidence by surfacing GPU availability, repair tickets, and maintenance notices via a fleet-synced API.

Power enterprise AI at scale

Telco

Scalable, AI-native infrastructure

Telcos can leverage Nscale’s GPU infrastructure to deliver AI services, optimise 5G networks, support advanced AI workflows, and drive next-generation solutions .

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Finance

Unlock AI advantage in finance

Financial service organisations that leverage GPU and Cloud technology are gaining a competitive edge through enhanced efficiency, improved decision-making, and superior customer service.

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Healthcare & Life Sciences

Enhancing efficiency in healthcare

GPU Cloud technology is revolutionising healthcare, impacting areas like bioinformatics, genomics, drug discovery, personalised medicine, and multiomic analysis.

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AI Native

Accelerated AI model deployment

AI-native companies can leverage Nscale’s scalable GPU cluster infrastructure to enhance model development, support critical operations, and drive innovation in their tech solutions.

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Introducing Nscale
Fleet Operations

Access thousands of GPUs tailored to your needs

Reserve GPUs

FAQ

Yes. Control Center exposes integration APIs for platform and SRE tooling, Observability can push telemetry to customers, and Radar is built to integrate with ticketing and back-office systems. Customers can automate ticket creation, consume repair status, and pull telemetry into their dashboards.

Yes. Fleet Operations is designed to operate across multi-cluster, multi-site fleets. The control plane provides unified inventory, policy enforcement and fleet-wide capacity signals while preserving site-level controls.


We provide customer-facing visibility into maintenance windows, repair status and incident progress through Control Center and the Radar API. This also allows customers to see the current state, expected timelines and any impact to capacity or SLAs.

Radar exposes high-level inventory, device state, capacity signals, utilization and key telemetry (device metrics, alerts and notable events). It is built to give customers the visibility they need to operate and integrate with our platform (capacity planning, automated scaling, and health checks) without exposing internal operational tooling.