resource quotas

**Resource quotas** is the **policy limits that cap how much compute, memory, or storage a user or team can consume** - quotas prevent monopolization and enforce predictable multi-tenant capacity governance. **What Is Resource quotas?** - **Definition**: Hard or soft upper bounds on allocatable resources within scheduler domains. - **Quota Types**: GPU count, CPU cores, memory, storage, job concurrency, and queue occupancy limits. - **Enforcement**: Scheduler rejects, delays, or downscales jobs exceeding defined quota policies. - **Elastic Option**: Soft quotas may allow temporary borrowing when idle capacity is available. **Why Resource quotas Matters** - **Fair Access**: Prevents one team from consuming disproportionate shared cluster capacity. - **Predictability**: Teams can plan around guaranteed baseline resource availability. - **Cost Governance**: Quota boundaries align infrastructure usage with budget ownership. - **Operational Stability**: Reduces contention spikes that can destabilize cluster performance. - **Strategic Allocation**: Supports priority distribution between production-critical and exploratory workloads. **How It Is Used in Practice** - **Policy Design**: Set quota levels from historical demand, business priority, and budget constraints. - **Borrowing Rules**: Define safe over-quota borrowing and reclaim behavior for soft quota models. - **Review Cadence**: Adjust quotas periodically based on utilization trends and roadmap changes. Resource quotas are **a core fairness and governance mechanism for shared training clusters** - clear quota policy keeps capacity distribution predictable and sustainable.