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11 posts tagged with "release"

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Volcano v1.16 Released: NamespaceQueue, fairshare, and a Broader HyperNode Ecosystem

· 19 min read

Volcano v1.16.0 introduces NamespaceQueue and the fairshare plugin. Tenants can use hierarchical queues within their own namespaces to organize quotas and queue hierarchies within administrator-authorized resource pools. Fairshare brings historical resource consumption into scheduling decisions among namespaces sharing a queue, improving fairness across teams.

This release also expands the HyperNode ecosystem. Platforms using other schedulers can deploy the HyperNode controller on its own to discover topology and manage supernodes and their hierarchy, then integrate that information through the HyperNode API. For inference services using Volcano, new PodGroup topology anti-affinity rules can spread instances across supernodes to reduce exposure to a shared failure domain.

Scheduler performance improvements include an Unschedulable Job Cache that records why Jobs could not be scheduled and skips repeated checks until blocking conditions change. Node scoring, cache updates, and queue lookups also become more efficient. The release additionally brings Kubernetes 1.36 support, load estimation for bulk Pod dispatch, DRA scoring, and accelerator and stability improvements.

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.

Volcano 1.7.0 Available Now

· 6 min read

Volcano 1.7.0 is now available with the following new features:

  • enhanced plugin for PyTorch Jobs
  • Ray on Volcano
  • enhanced scheduling for general Kubernetes services
  • multi-architecture images of Volcano
  • optimized queue status info

volcano_logo.png

Volcano is the industry-first cloud native batch computing project. Open-sourced at KubeCon Shanghai in June 2019, it became an official CNCF project in April 2020. In April 2022, Volcano was promoted to a CNCF incubating project. By now, more than 490 global developers have committed code to the project. The community is seeing growing popularity among developers, partners, and users.