Quotas in Ori AI Fabric: Predictable Scaling for a Reliable AI Cloud
In the fast-moving world of AI infrastructure, predictability is power. AI builders deploying workloads across distributed AI infrastructure need to know that their resources will scale smoothly, workloads will run reliably, and performance will remain consistent, even as demand surges.
To make that possible, Ori AI Fabric provides a system of quotas, a foundational mechanism for maintaining fairness, predictability, and operational balance across the platform.
Quotas ensure that every user, team, and organization has access to the capacity they need, while protecting shared infrastructure from overconsumption. It’s a design choice that enables both governance and growth, letting customers scale with confidence.
Quotas prevent chaos in your AI cloud operations
In traditional cloud environments, quotas often serve as administrative boundaries. But in AI clouds, they also play a strategic role. AI workloads aren’t static, they expand and contract dynamically based on training schedules, inference load, or the lifecycle of deployed models. Without a quota framework, unmanaged resource usage can jeopardize financial and operational stability, particularly in enterprise environments where predictable usage, budgeting, and uptime are paramount.
Ori’s Quota system provides the balance:
- Fairness — ensuring equitable resource access for all tenants
- Predictability — preserving performance consistency during demand spikes
- Control — enabling administrators and teams to plan and allocate resources efficiently
By introducing structure into an inherently elastic environment, quotas allow your cloud operations team to remain responsive and sustainable, even under extreme load.
How Quotas Work in Ori AI Fabric
Every user and organization starts with a baseline quota, a predefined allocation of GPU, compute, and networking resources.
When a new resource is provisioned, say a GPU Instance, Kubernetes cluster, or inference endpoint, Ori performs an automated quota check to ensure that the request falls within assigned limits.
If the quota threshold has been reached, the provisioning process is paused and the user is notified directly through the Ori Console. From there, the user can request a quota increase with a single action.
This real-time enforcement ensures that usage always aligns with capacity planning, preventing accidental over-provisioning while maintaining a seamless user experience.
Quota Allocation Across Services
Each organization on Ori receives an initial set of quotas tailored to their needs and platform usage. These quotas cover multiple infrastructure layers within the AI Fabric, including:
- Supercomputers: Specifies reserved nodes and GPU configurations for dedicated, high-performance jobs.
- GPU Instances: Defines the maximum number of active GPU Instances across locations.
- Serverless Kubernetes: Sets GPU limits per cluster and controls load balancer-level scaling for workloads.
- Inference Endpoints: Determines how many active GPUs can run per GPU type (e.g., H100, L40S, A100).
This granular allocation approach ensures that organizations can scale independently across different workload types, without affecting others sharing the platform.
Requesting a Quota Increase
As AI initiatives evolve, so do resource requirements. Whether it’s scaling inference endpoints for production traffic or provisioning more GPUs for fine-tuning, Ori allows users to request additional quota directly through the Console.
Each request is automatically routed to the Admin Platform, where administrators review the submission based on clear, objective criteria:
- Customer status: Active subscription and payment record.
- Payment verification: Valid billing method on file.
- Usage history: Previous utilization patterns and efficiency.
- Organization profile: Use case type, region, and projected workload.
Once approved, quota increases are applied instantly, unlocking new capacity without disruption to running workloads.
This responsive process ensures that customers can scale when they need to, while Ori maintains the operational integrity that keeps the cloud infrastructure balanced.
Deploy a reliable AI cloud with Ori AI Fabric
In the landscape of large-scale AI infrastructure, growth without governance quickly turns to chaos. Ori’s Quota system turns that challenge into an advantage, providing the clarity, control, and structure required to scale responsibly.
Ori AI Fabric’s quota management ensures that elasticity never comes at the expense of stability. Every GPU, every cluster, and every workload operates within a transparent framework that protects performance and stability. In doing so, Ori makes predictable scale not just a possibility, but a built-in feature of the modern AI cloud. Speak with our team to see how you can build a powerful and reliable AI cloud with Ori AI Fabric.
