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Predictive hardware failure detection across 4,200 physical servers, catching 89% of failures before they happened.
Measured outcomes
4,200
Servers monitored
−71%
Unplanned outages
9 days
Median warning lead time
$620k
Avoided emergency spend
Hardware failures were discovered when a service went down. Vendor tooling reported per-server, in three different formats, with no aggregation.
The dashboard ingests IPMI, iDRAC, iLO and SMART telemetry, learns per-component failure signatures, and raises a maintenance request before the component dies.
Headline result
0%
failures predicted
Tags
Five capabilities that define the system. Each one exists because something specific was broken.
Dell iDRAC, HPE iLO, Lenovo XCC and generic IPMI normalised into one schema.
Per-component models on SMART attributes, thermal trends, PSU ripple and memory correctable-error rates.
A prediction opens a vendor case with the diagnostic bundle attached.
Predicted failures trigger VM migration off the affected host before maintenance.
Rack-level heat mapping identifies airflow problems before they cause throttling.
Out-of-band polling into a time-series store, with per-component models scoring hardware health continuously.
3 components
Out-of-band only — collection survives an OS hang.
3 components
Models are calibrated so a 90% prediction is right 90% of the time.
3 components
Evacuation runs before the maintenance window opens, not during it.
No mystery components. Everything below is either open source or a platform you already own.
Interactive mock-ups of the shipped interface. The live environment is available during a demo session.
Predicted failures ranked by confidence and impact
The running environment is available during a booked session — including a sandbox tenant you can drive yourself.
The real sequence, in order. Steps with a command are copy-pasteable.
DaemonSet or standalone pollers with out-of-band network access.
$helm install server-health aiinfraengine/server-healthStore BMC credentials in Vault with per-datacentre scoping.
Collect 60 days of telemetry before enabling predictions.
$aiinfraengine health baseline --days 60Configure vendor API credentials and the maintenance approval chain.
Published rather than hidden behind a call. Volume and multi-year terms move these numbers.
Platform
$1.40per server / month
Implementation
from $42kone-time
Need this scoped against your estate? We will size it properly, in writing, within a week.
Request a quoteWe will walk you through the architecture, the trade-offs we made, and what would change for your environment.