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raids-lab

crater

Crater is a cloud-native AI training & inference platform.

InfrastructureDeploy & ServeOrchestrationGo
Open on GitHub
Momentum
+0stars in 24 hours0.0%
568
Stars
76
Forks
+-4
This week
28
Contributors
Created 2025-06-08 · Updated 2026-10-15 · #16874 today
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raids-lab/crater is ranked 16,874 with 568 stars.

Same-category comparison

raids-lab/crater is ranked 16,874 among these 8 peers; LeoYeAI/openclaw-guardian is ranked 16,860.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguageGo
CategoryInfrastructure
SubcategoryDeploy & Serve, Orchestration
KeywordsContainers, DevOps, Distributed training, Inference optimization
Stars568
Forks76
Contributors28
Created date2025-06-08
Updated date2026-10-15
Stars in 1 day0
Stars in 7 days-4
Rank16,874
Previous rank19,062
Rank change2,188
7-day stars rank18,775
Previous 7-day stars rank18,426
7-day stars rank change-349
Total stars rank17,544
Previous total stars rank17,518
Total stars rank change-26
README summary

Crater A Kubernetes-native control plane for shared AI computing clusters Operate shared **GPU clusters**, **LLM training and serving workloads**, **developer environments**, and **data/model assets** across research, education, and enterprise teams. It helps organizations manage heterogeneous compute resources, submit and govern AI workloads, quickly deploy large-model training and inference environments, and observe cluster health from a unified web console, CLI, and AI-assisted operations interface. Crater is designed for environments where different teams and workloads share the same

GPU cluster: long-running training jobs, bursty lab workloads, interactive notebooks, online AI services, LLM inference services, and offline data processing pipelines. It builds an operational control plane on top of Kubernetes and Volcano, connecting users, accounts, queues, quotas, images, datasets, models, jobs, services, and observability into one workflow. Crater is organized around four layers: **User interfaces**: web console, CLI, HTTP APIs, and agent-friendly command skills. **Control plane**: authentication, accounts, quotas, scheduling policies, jobs, services, templates, images, datasets, models

, approvals, and operations. **Execution layer**: Kubernetes workloads, Volcano scheduling, accelerator resources, Pods, Services, PVCs, and external access rules for training, serving, and interactive environments. **Observability and AI operations layer**: metrics, logs, Grafana dashboards, operation records, runtime diagnostics, AI assistant workflows, and admin-side intelligent operations. Prerequisites A running Kubernetes cluster Helm v3 2. io | | 🧱 **Minikube** | Single-node local dev & testing | minikube. io | | ☁️ **Production K8s** | Production or large-scale deployments | kubernetes. Install via Helm (OCI) 💡 The chart version is in (field

) or in the GitHub releases. 🤝 Contributing We welcome community contributions! The complete development and contribution specification lives in CONTRIBUTING. md: global rules, environment setup (fork, hooks, unified config), workflow, commit convention, PR description template, and per-module entry points. md 📝 License Crater is licensed under the **Apache License 2. Copyright 2023-2026 The Crater Project Team, RAIDS-Lab.

Frequently asked questions

How many stars and forks are recorded?

raids-lab/crater has 568 stars and 76 forks.

What is the repository rank?

raids-lab/crater is ranked 16,874.

What language and category are recorded?

raids-lab/crater has 568 stars, uses Go and belongs to Infrastructure.

Which repository is closest in rank?

raids-lab/crater is compared with LeoYeAI/openclaw-guardian, ranked 16,860 with 568 stars.

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