Production-Grade Container Scheduling and Management
Easy and fluent Go cron scheduling. This is a fork from https://github.com/jasonlvhit/gocron
Self-hosted AI gateway for multi-channel, multi-credential setups — API keys and subscription accounts, scheduling, failover, request logs and usage. 自托管 AI 网关:多渠道多凭据统一接入,含密钥与订阅账号、调度容错、日志与用量。
Descheduler for Kubernetes
Dkron - Distributed, fault tolerant job scheduling system https://dkron.io
A toolkit for orchestrating distributed systems at any scale. It includes primitives for node discovery, raft-based consensus, task scheduling and more.
Kubernetes WithOut Kubelet - Simulates thousands of Nodes and Clusters.
:vertical_traffic_light: Kubernetes-native Job Queueing and Scheduling
Open source on-call scheduling, automated escalations, and notifications so you never miss a critical alert
A QoS-based scheduling system brings optimal layout and status to workloads such as microservices, web services, big data jobs, AI jobs, etc.
pg_timetable: Advanced scheduling for PostgreSQL
Repository for out-of-tree scheduler plugins based on scheduler framework.
Cleaner is a Kubernetes controller that identifies unused or unhealthy resources, helping you maintain a streamlined and efficient Kubernetes cluster. It provides flexible scheduling, label filtering, Lua-based selection criteria, resource removal or update and notifications via Slack, Webex and Discord. it can also automate clusters operations.
KubeStellar - a flexible solution for multi-cluster configuration management for edge, multi-cloud, and hybrid cloud
Open Model Engine (OME) — Kubernetes operator for LLM serving, GPU scheduling, and model lifecycle management. Works with SGLang, vLLM, TensorRT-LLM, and Triton
Cross-Cluster Embodied Intelligence Cloud-Native Platform. Manage cross-cluster embodied AI workloads with Kubernetes-native CRDs, unified job scheduling, cross-cluster Pod networking, and multi-runtime support.
A model-agnostic, stateless Go agent runtime featuring dual-IR planning, dependency-aware batch scheduling, capability-driven MCP/tool orchestration, policy-based failure recovery, conditional replanning, side-effect control, and end-to-end execution observability.