
Monitored, managed, and optimized. From the physical layer up through orchestration, run by the team that deploys GPU clusters for a living.
AI workloads don't pause for broken GPUs. Training jobs don't tolerate unplanned downtime. And your engineers shouldn't be firefighting at 3 AM because one degraded NVLink connection cascaded into a cluster-wide failure.
Total annual impact in lost compute and recovery overhead for a 512-node cluster (H100/B200 class) at $3-6 per GPU-hour.
Telemetry across GPU, CPU, memory, NVLink, thermal, power, and fabric, with escalation paths agreed before anything fails.
Updates tested against your workloads, scheduled into planned maintenance windows, and applied on a managed cadence, not when something breaks.
Tickets, RMAs, and parts logistics opened and chased by Arc through our OEM relationships, so your engineers never sit in a support queue.
Critical spares stocked onsite and inventoried against your bill of materials, so repairs happen in hours instead of shipping cycles.
InfiniBand, RoCE, and RDMA monitored and tuned as first-class infrastructure, with link health tracked down to individual ports.
Utilization trends, growth forecasting, and executive-ready reporting that ties capacity and spend to what your workloads actually need.
Telemetry from every GPU, CPU, memory bank, NVLink lane, and power rail rolls up to a single health state per node, across the whole cluster.
Spine and leaf topology is mapped, not inferred. Link health is tracked down to individual ports across InfiniBand and RoCE fabrics.
Degradation surfaces as a trend before it becomes an incident. ECC drift, thermal creep, and link flap caught below standard alerting thresholds.
Every alert carries a severity, a response time, and an escalation path agreed before anything fails, so nothing lands as a surprise.
Planned windows, RMAs in flight, and open tickets sit in the same view, so you always know what's in motion and when.
Failures get caught on the trend line and fixed in a planned window, not during a training run.
Your team spends its time on models and workloads instead of OEM tickets and firmware.
Continuous tuning and scheduling keep the GPUs you already own doing useful work.
A fixed managed service instead of internal overhead, with a longer hardware lifecycle.
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Arc designs, deploys, and scopes management before the first rack ships. The team that built your cluster is the team that runs it.

Self-managed or switching from another provider, Arc takes over in three weeks with zero disruption to running workloads.
Whether you're deploying a new cluster, running one yourself, or ready to leave your current provider, this is the starting point. Share the basics and Arc takes it from there.
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