Compute utilisation
Fleet
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Pick one or more machines from the selector above to see fleet aggregates, utilisation and cost.
Usage
Fleet avg CPU iMean CPU utilisation across the whole selected period, counting off/asleep time as 0% — the share of purchased capacity you actually use. The smaller figure is the average only while powered on.
{{ pct(core.cards.avgCpu) }}
of purchased compute, whole period incl. off/asleep
{{ pct(core.cards.avgCpuOn) }} while powered on
Fleet avg RAM iMean RAM utilisation across the whole selected period, counting off/asleep time as 0%. The smaller figure is the average only while powered on.
{{ pct(core.cards.avgRam) }}
of installed memory, whole period incl. off/asleep
{{ pct(core.cards.avgRamOn) }} while powered on
Fleet avg GPU iMean GPU utilisation across the whole period (off/asleep = 0%), computed only across machines reporting NVIDIA GPU telemetry. The smaller figure is the average only while powered on.
{{ pct(core.cards.avgGpu) }}
of GPU capacity, whole period incl. off/asleep
{{ pct(core.cards.avgGpuOn) }} while powered on
across {{ core.cards.gpuN }} machine{{ core.cards.gpuN===1?'':'s' }} with a GPU, of {{ selectedCount }} selected
Storage used iDisk capacity actually used vs purchased, across the selected machines. The gap is storage you bought but never fill.
{{ pct(core.cards.storage.pct,0) }}
{{ tb(core.cards.storage.usedBytes) }} used / {{ tb(core.cards.storage.totalBytes) }} available
Peak concurrent demand iThe single highest simultaneous moment of fleet demand, as a share of total owned compute (sum of logical cores). Even the worst moment needs only a fraction of what you own.
{{ pct(core.cards.peak.pct) }}
worst moment needed only this much of owned compute
{{ timeLabel(core.cards.peak.t) }}
On / idle / off split iShare of wall-clock time. Off = telemetry gaps (asleep / shut down). Idle = on but CPU < 10%. Active = on with CPU ≥ 10%.
{{ pct(core.cards.split.off,0) }} powered off
Active {{ pct(core.cards.split.active,0) }}
Idle {{ pct(core.cards.split.idle,0) }}
Off {{ pct(core.cards.split.off,0) }}
Saturation iShare of on-time seconds where CPU exceeds 95% (1-second granularity). High saturation means the user needed more compute than the machine could give — a throttled, degraded experience.
{{ pct(core.cards.sat.pct,2) }}
{{ secCompact(core.cards.sat.seconds) }} of on-time over 95% CPU
{{ core.cards.sat.pct<1?'under 1%':core.cards.sat.pct<=5?'1–5%':'over 5%' }}
Utilisation over time
mean line · shaded peak band · drag to zoom · scroll to pan raw resolution · drag to zoom · scroll to panCPU utilisation
fleet mean · %
{{ pct(core.cards.avgCpu) }}
avg
mean5-min peak
RAM utilisation
fleet mean · %
{{ pct(core.cards.avgRam) }}
avg
mean5-min peak
GPU utilisation
{{ core.gpuMachines }} GPU machines · %
{{ pct(core.cards.avgGpu) }}
avg
mean5-min peak
Storage used
fleet total · of {{ tb(core.fleet.totalBytes) }} bought
{{ tb(core.cards.storage.usedBytes) }}
used
Usage heatmap
hour of day × day of week · {{ tzLabel }}
Utilisation distribution
share of on-time seconds by CPU band
{{ b.label }}{{ b.band }}
Bottom-heavy by design: most seconds are spent barely using the machine.
Per-machine comparison
click a row to open its detail view| Machine {{ compSort.dir==='asc'?'▲':'▼' }} | Avg CPU {{ compSort.dir==='asc'?'▲':'▼' }} | Avg RAM {{ compSort.dir==='asc'?'▲':'▼' }} | On-hrs/day {{ compSort.dir==='asc'?'▲':'▼' }} | Saturation {{ compSort.dir==='asc'?'▲':'▼' }} |
|---|---|---|---|---|
|
{{ r.hasGpu ? 'GPU' : (r.badge==='mac'?'':'W') }}
{{ r.name }}
|
{{ pct(r.avgCpu) }} | {{ pct(r.avgRam) }} | {{ r.onHoursPerDay.toFixed(1) }} | {{ pct(r.satPct,2) }} |
Top foreground apps
by total active time across selected fleet| App | Avg active / machine | Avg CPU (fg) | Avg RAM (fg) | Machines |
|---|---|---|---|---|
{{ appInitials(a.app) }}{{ a.app }} |
{{ secCompact(a.perMachineSec) }} | {{ pct(a.avgCpu) }} | {{ pct(a.avgRam) }} | {{ a.machines }} |
Financials
Cost comparison
per {{ moneyPeriod }} · {{ costScope() }}
StorageCPURAMGPUVRAMClient
Elastic vs owning iAmortised hardware minus the elastic-cloud equivalent. Positive = cloud is cheaper; negative = cloud costs more (usually storage-driven). Toggle Monthly/Yearly and Sum / Avg-per-device above.
{{ core.totals.savingsMonthly>=0 ? '' : '+' }}{{ usdEst(Math.abs(ctv(core.totals.savingsMonthly*moneyMul))) }}/{{ moneyPeriod==='year'?'yr':'mo' }}
{{ core.totals.savingsMonthly>=0 ? 'saved vs owning the hardware · ' : 'more than owning · ' }}{{ pct(Math.abs(core.totals.savingsPct),0) }} {{ core.totals.savingsMonthly>=0 ? 'lower' : 'higher' }}
Cost per active hour
{{ usdEst(core.totals.costPerActiveHour) }}/hr
elastic spend ÷ fleet active hours
Cumulative spend over the period
cloud accrues only while machines are active (flat overnight) · owned is the upfront purchase · click legend to toggle
Owned
Static
Elastic
Per-machine cost
per {{ moneyPeriod }} · % columns relative to owned hardware| Machine | Owned | Static cloud | Elastic cloud | Static % | Elastic % |
|---|---|---|---|---|---|
{{ r.hasGpu ? 'GPU' : (r.badge==='mac'?'':'W') }}{{ r.name }} |
{{ usdEst(r.ownedMonthly*moneyMul) }} | {{ usdEst(r.staticMonthly*moneyMul) }} | {{ usdEst(r.elasticMonthly*moneyMul) }} | {{ pct(r.staticPct,0) }} | {{ pct(r.elasticPct,0) }} |
{{ costMode==='avg' ? 'Per-device average' : 'Fleet total' }} |
{{ usdEst(ctv(core.totals.ownedMonthly*moneyMul)) }} | {{ usdEst(ctv(core.totals.staticMonthly*moneyMul)) }} | {{ usdEst(ctv(core.totals.elasticMonthly*moneyMul)) }} | {{ pct(core.totals.staticMonthly/core.totals.ownedMonthly*100,0) }} | {{ pct(core.totals.elasticMonthly/core.totals.ownedMonthly*100,0) }} |