On January 9, 2024, UTC+8, Volcano version v1.8.2 was officially released. This version added the following new features:

As artificial intelligence (AI) technologies advance and large language models (LLMs) grow more popular, the demand for AI compute has been booming. This has generated huge demand for high-performance scheduling for the AI and for hardware like AI chips.

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 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.

On October 26, 2022, Krzysztof Adamski and Tinco Boekestijn from ING Group delivered a keynote speech "Efficient Scheduling Of High Performance Batch Computing For Analytics Workloads With Volcano" at KubeCon North America. The speech focused on how Volcano, a cloud native batch computing project, supports high-performance scheduling for big data analytics jobs on ING's data management platform. More details: KubeCon + CloudNativeCon North America

This article was firstly released at Container Cube on September 6th, 2021, refer to Volcano v1.4.0-Beta发布，支持NUMA-Aware等多个重要特性

Volcano, CNCF's first batch computing project, is now available with a new version, v1.4 (Beta). This version includes multiple important features, such as resource ratio-based partitions on GPU nodes, NUMA-aware, mixed deployment of multiple schedulers, and greatly improved stability.

This article was firstly released at Container Cube on September 30th, 2020, refer to鹏城实验室启智章鱼教你彻底摆脱Kubernetes集群资源抢占难题

This article was firstly released at Container Cube on September 30th, 2020, refer to揭秘爱奇艺深度学习平台云原生迁移实践

This article was firstly released at Container Cube on December 24th, 2020, refer to锐天投资基于Volcano的大规模分布式离线计算平台的应用实践

This article was firstly released at Container Cube on October 27th, 2020, refer to HPC on Volcano：容器在气象行业HPC高性能计算场景的应用

Kubernetes has become the de facto standard for cloud native application orchestration and management. An increasing number of applications are being reconstructed or built to employ Kubernetes. High performance computing (HPC) is a popular distributed computing mode and is widely used in many fields. For users who have deployed HPC applications and are eager to containerize and manage their applications using Kubernetes, Volcano, CNCF's first distributed scheduling system for batch computing, is a good choice. Volcano supports multiple types of computing frameworks, such as Spark, TensorFlow, and Message Passing Interface (MPI). This article uses a traditional HPC application, the Weather Research and Forecasting (WRF) model, as an example to describe how Volcano works for HPC applications.

This article was firstly released at Container Cube on May 27th, 2021, refer to 小红书基于Volcano的大规模离线与在线推荐模型训练实践