Docs : Add HyperJob concept documentation for multi-cluster job splitting

[codeEvolveZenith345]

Description

Introduce HyperJob documentation in both English and Chinese Concepts sections, covering multi-cluster job splitting, key features, use cases, and distinctions from standard Volcano Jobs

• Please check if the PR fulfills these requirements

• The commit message follows our guidelines

• What kind of change does this PR introduce?

/kind documentation

• What this PR does / why we need it:

This PR adds comprehensive documentation for the HyperJob concept to the Volcano website in both English and Chinese. HyperJob is a high-level multi-cluster scheduling abstraction built on top of Volcano Job that enables:

• Automatic job splitting across multiple Kubernetes clusters
• Unified status management for multi-cluster workloads
• Simplified multi-cluster AI/ML job orchestration
• Better resource utilization across heterogeneous clusters

Additionally, cross-reference links have been added to the existing Multi-Cluster Scheduling documentation to improve discoverability.

• Which issue(s) this PR fixes:

Fixes #475

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[gemini-code-assist]

Summary of Changes

Hello @codeEvolveZenith345, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request significantly enhances the Volcano project's documentation by introducing the HyperJob concept. HyperJob provides a crucial high-level abstraction for managing large-scale AI/ML workloads across multiple Kubernetes clusters, simplifying complex distributed job orchestration. It aims to improve resource utilization and provide a unified control plane for jobs that span heterogeneous and geographically dispersed environments, thereby making multi-cluster AI job scheduling more accessible and efficient.

Highlights

• New HyperJob Documentation: Introduced comprehensive documentation for the HyperJob concept in both English and Chinese, detailing its purpose, features, and usage within the Volcano ecosystem.
• Multi-Cluster AI Workload Orchestration: HyperJob is presented as a high-level abstraction for multi-cluster AI workloads, enabling automatic job splitting, unified status management, and simplified orchestration across multiple Kubernetes clusters.
• Key Features and Use Cases: The documentation outlines HyperJob's core capabilities such as automatic job splitting, unified status management, and high-level scheduling, along with typical use cases like multi-cluster LLM training and heterogeneous resource scheduling.
• Comparison with Volcano Job: A clear distinction is made between HyperJob and standard Volcano Job, highlighting when to use each based on single-cluster vs. multi-cluster requirements and job splitting needs.
• Cross-Referencing: Existing multi-cluster scheduling documentation (both English and Chinese) has been updated to include cross-reference links to the new HyperJob concept, improving discoverability.

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Changelog

• content/en/docs/hyperjob.md
  • Added new English documentation for the HyperJob concept, covering its overview, key features, comparison with Volcano Job, typical use cases, architectural overview, and a conceptual YAML example.
  • Configured the document for inclusion in the 'concepts' section of the documentation sidebar with a weight of 4.
• content/en/docs/multi_cluster_scheduling.md
  • Appended a new paragraph and link referencing the HyperJob documentation, guiding users to a high-level multi-cluster abstraction for job splitting.
• content/zh/docs/hyperjob.md
  • Added new Chinese documentation for the HyperJob concept, mirroring the English content, including its overview, core features, comparison with Volcano Job, typical use cases, architecture, and a conceptual YAML example.
  • Configured the document for inclusion in the 'concepts' section of the Chinese documentation sidebar with a weight of 4.
• content/zh/docs/multi_cluster_scheduling.md
  • Appended a new paragraph and link referencing the Chinese HyperJob documentation, providing guidance on using a high-level abstraction for multi-cluster job splitting.

Activity

• The author, codeEvolveZenith345, initiated this pull request to add new documentation for the HyperJob concept.
• The pull request is categorized as '/kind documentation'.
• This PR addresses and fixes issue Add HyperJob concept to concepts documentation (both EN and CN) #475.
• No further review comments or activity have been recorded since the initial submission.

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[codeEvolveZenith345]

/cc @JesseStutler

[gemini-code-assist]

Code Review

This pull request successfully introduces comprehensive documentation for the HyperJob concept in both English and Chinese. The new hyperjob.md files clearly explain the purpose, key features, use cases, and architecture of HyperJob, along with a helpful conceptual YAML example. Additionally, the cross-references added to the multi_cluster_scheduling.md files significantly improve the discoverability of this new concept. The documentation is well-structured and provides valuable information for users looking to understand multi-cluster job splitting with HyperJob.

[JesseStutler]

Please also solve these comments in zh docs

[codeEvolveZenith345]

Hi @JesseStutler I have refactored both the files as per your review. please review it again!