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Scale before you need to — 72 hours ahead of demand.

Infra Predict

Uses ML models trained on historical CloudWatch, GCP Monitoring, and application metrics to predict infrastructure capacity needs 72 hours ahead, enabling proactive scaling before performance degradation occurs. Eliminates the reactive firefighting that defines capacity management in traditional enterprises running legacy banking and telecom workloads.

Why It Matters

InfraPredict replaces capacity management’s two failure modes — firefighting when demand spikes and paying for idle headroom the rest of the time — with foresight.
ML forecasting on historical infrastructure metrics predicts capacity needs 72 hours ahead, so scaling happens before users feel degradation and provisioning matches demand instead of fear.
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72 hours of warning changes everything

Reactive scaling starts after performance already degraded — predictive scaling means banking end-of-month peaks and telecom event surges are provisioned for before they arrive.

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35% less overprovisioning waste

Static capacity planning buys peak capacity year-round — demand forecasting rightsizes infrastructure continuously, cutting the idle-resource spend CFOs never see itemized.

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Ends the firefighting culture

Capacity incidents at 2 AM become scheduled scaling events reviewed in daily standups — operations teams shift from reactive heroics to proactive management.

The Cloudly Advantage

InfraPredict is AIOps in its most literal form — ML applied to operations itself — making it the purest product expression of Cloudly’s core identity yet.
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Broadest market in the portfolio

Every enterprise with cloud infrastructure has capacity pain — no ML maturity required, opening accounts the MLOps products can't yet reach.

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AIOps identity, product form

ML-driven prediction on Prometheus and CloudWatch data is exactly what "AIOps services" means — the flagship demo of what Cloudly does.

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Monitoring services pull-through

Prophet forecasting over Prometheus TSDB and Grafana requires the observability foundation our AWS Monitoring services build — every deployment starts with a monitoring engagement.

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Legacy workload wedge

Traditional banking and telecom workloads — our home-turf accounts — suffer worst from static capacity planning, making current clients the first pipeline.

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Hard savings plus reliability pitch

35% waste reduction and prevented outages give BD both a CFO number and a CTO story in one product.

The Final Takeaway

Gateway to the platform — Infrastructure prediction builds trust in Cloudly's ML capability using the client's own ops data — the proof point that opens the full MLOps platform conversation later.

Powered By

Prophet

Core to the InfraPredict technology stack.

AWS Forecast

Core to the InfraPredict technology stack.

Prometheus TSDB

Core to the InfraPredict technology stack.

Grafana ML annotations

Core to the InfraPredict technology stack.

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