Allocated is not the same as productive.
See what your compute is actually doing, not just what the scheduler assigned.
Most GPU clusters report high allocation. The operator sees 95% on a dashboard and assumes the fleet is working. But allocation is not utilization. GPUs trapped in I/O wait states, starved for data, or blocked by dependencies are allocated but idle. Amalgamy surfaces the real yield: which accelerators are doing math, which are waiting, and why. From the facility's power feed to the workload's last gradient step, in one view.
The outcome
Prove the return, not the allocation.
The operator who just committed capital to sovereign AI infrastructure needs to prove that the investment is producing. "95% allocated" is not proof. "X computational jobs completed per kilowatt, per tenant, per period" is proof.
Amalgamy's observability layer links physical facility telemetry (power draw, cooling capacity, thermal density) directly to logical workload outcomes (jobs completed, data moved, compliance enforced). The operator sees the full stack in one view, exports it to Prometheus, and builds reporting from real data, not dashboard cosmetics.
What it delivers
From substation to training job.
Actual yield, not allocation theater.
See which GPUs are doing math and which are trapped in I/O wait states. The "utilization illusion" (95% allocated, 40% productive) is gone.
Full-stack visibility.
A single view that links physical facility metrics (power, cooling, thermal) directly to logical workload states. From the substation to the training job.
OpenTelemetry native.
Amalgamy is natively instrumented for OpenTelemetry with export to Prometheus. Vendor-neutral observability with no custom integration.
Chargeback per tenant.
Compute usage, data movement costs, and energy consumption mapped to specific tenants or departments automatically. Precise multi-tenant billing.
Executive-level reporting.
Not just engineer dashboards. Amalgamy translates deep telemetry into ROI views the operator can present to a board or an auditor.
Data gravity visibility.
See where data friction and I/O bottlenecks live across the storage fabric. Know exactly why a workload is slow before touching a config.
Stop guessing utilization, start measuring yield.
Technical docs at amalgamy.ai. Engagement and capacity planning at ThisWayGlobal.