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Manages co-scheduling of latency-sensitive and batch workloads on shared resources with QoS guarantees.
Distinct from Resource Colocation Strategies: No candidate matches this concept; closest Resource Colocation Strategies is limited to model component colocation, not general online/offline workload colocation.
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Volcano is a Kubernetes-native batch scheduler specialized for AI, machine learning, and high-performance computing workloads. It provides gang scheduling to atomically allocate resources for all tasks of a distributed job, preventing deadlocks from partial allocation, and supports hierarchical queue management for multi-tenant resource isolation with configurable quotas, borrowing, and preemption. Topology-aware placement optimizes communication-intensive workloads by modeling network hierarchy to minimize cross-switch latency. Volcano differentiates itself with automated orchestration of di
Volcano runs latency-sensitive services alongside batch jobs while preserving service quality through resource overcommitment, QoS classification, and CPU burst.