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7 posts tagged with "scheduling"

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Volcano v1.15 Released: Gang-Granularity Preemption, DRA Queue Quota, and More Scheduling Enhancements

· 15 min read

As batch training, inference, AI Agent, HPC, big-data and other diverse workloads are increasingly co-located in the same Kubernetes cluster, the scheduler must make higher-quality decisions under intensifying resource contention while preserving job-level semantics, queue fairness, topology affinity, and operational stability. v1.15.0 delivers enhancements across the scheduling core, heterogeneous resource management, multi-scheduler coordination, and performance observability.

The most notable new capability is Gang-Aware Preemption and Resource Reclamation: preemption decisions are evaluated at gang granularity on both the preemptor and victim sides — the preemptor is placed as a whole gang, and victim candidates are organized and evaluated at job/gang granularity, preferring surplus replicas to avoid per-Pod random eviction that disrupts multiple training jobs while the preemptor itself still cannot start. In addition, v1.15.0 introduces DRA queue quota in the capacity plugin, a pluggable multi-sharding policy framework, a Benchmark and performance observability tool, Kubernetes 1.35 support, NodeGroup preferred ordering, Agent Scheduler stability fixes, GPU/vGPU incremental enhancements, and Scheduling Gates for queue admission control.

Volcano v1.14 Released: Entering a New Era of Unified AI Scheduling

· 13 min read

Volcano community v1.14 is now officially released. As AI workloads evolve from single offline training to diverse scenarios including online inference and AI Agents, the scheduling system faces unprecedented challenges. v1.14 delivers architecture-level innovations that maintain Volcano's advantages in large-scale batch computing while closing the gap for latency-sensitive workloads, taking a solid step toward the goal of becoming a "unified scheduling platform for AI training, inference, RL, and Agent scenarios."

Volcano v1.12.0 Available Now

· 19 min read

Volcano v1.12 released: Advancing Cloud-Native AI and Batch Computing

As AI large model technology rapidly evolves, enterprises are placing higher demands on computing resource efficiency and application performance. For complex application scenarios such as AI, big data, and high-performance computing (HPC), efficiently utilizing accelerators like GPUs, ensuring high system availability, and managing resources with fine granularity are the core areas of focus for the Volcano community's continuous innovation.

Volcano v1.11.0 Available Now

· 19 min read

As the de facto standard in cloud-native batch computing, Volcano has been widely adopted across various scenarios, including AI, Big Data, and High-Performance Computing (HPC). With over 800 contributors from more than 30 countries and tens of thousands of code commits, Volcano has been deployed in production environments by over 60 enterprises worldwide. It provides the industry with excellent practical standards and solutions for cloud native batch computing.