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Cut training costs by 70% — without cutting corners.

Compute Orchestrator

Dynamically provisions and scales GPU and CPU compute resources for training workloads, leveraging spot/preemptible instances to reduce training infrastructure costs by up to 70%. Removes the operational burden of managing heterogeneous compute fleets that overwhelms in-house teams at traditional enterprises.

Why It Matters

ComputeOrchestrator attacks the biggest line item in enterprise ML — compute cost — with intelligence rather than compromise.
Dynamic provisioning and spot instance orchestration cut training infrastructure costs by up to 70%, while automatic interruption handling ensures cheap compute never means lost work.
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70% cost reduction with safety nets

Spot and preemptible instances are dramatically cheaper but risky by default — automatic interruption handling and checkpoint recovery capture the savings without the failures that plague basic AWS Batch.

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Removes fleet management burden

Heterogeneous GPU/CPU fleets overwhelm in-house teams at traditional enterprises — orchestration automates provisioning, scaling, and scheduling so teams train models instead of babysitting infrastructure.

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Elastic by design

KEDA-driven autoscaling on Kubernetes means clusters grow for training bursts and shrink to zero after — clients pay for what they use, not what they provisioned.

The Cloudly Advantage

ComputeOrchestrator is Cloudly’s CFO conversation — a product whose pitch is a number (“cut training costs 70%”) rather than a capability.
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Hard-number sales pitch

Cost reduction claims can be validated against the client's own cloud bill in a discovery session — the most credible ROI story in our portfolio.

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Core Cluster Services alignment

Kubernetes, Slurm, and Volcano cluster design and operations are our home turf — every deployment is a substantial consultancy plus managed-service engagement.

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Completes the TrainForge stack

TrainForge schedules the jobs, ComputeOrchestrator provisions the iron — bundled, they're a full training platform with a built-in cost-savings story.

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EKS opens AWS Migration deals

Kubernetes-based orchestration on EKS creates natural entry points for AWS Migration and Monitoring services in every engagement.

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Self-funding platform adoption

Compute savings can literally pay for the broader Cloudly platform — "fund your MLOps transformation from your GPU bill" is a compelling expansion narrative.

The Final Takeaway

AIOps showcase — Intelligent autoscaling and interruption handling demonstrate our AIOps capability in production — a live reference for selling AIOps services across the account.

Powered By

Kubernetes (EKS/GKE)

Core to the ComputeOrchestrator technology stack.

KEDA autoscaler

Core to the ComputeOrchestrator technology stack.

AWS Spot/GCP Preemptible

Core to the ComputeOrchestrator technology stack.

Slurm

Core to the ComputeOrchestrator technology stack.

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