This document defines a high level roadmap for Karmada development and upcoming releases. Community and contributor involvement is vital for successfully implementing all desired items for each release. We hope that the items listed below will inspire further engagement from the community to keep Karmada progressing and shipping exciting and valuable features.
- Lazy mode of PropagationPolicy
- Cluster Problem Detector(CPD) - Part one: Cluster condition-based remedy system
- Scheduler Enhancement - enable scheduler estimator supports resource quota
- Scheduler Enhancement - Provide a mechanism of re-balance workloads
- AI training and batch job support (Including PyTorch, Spark, Flink and so on)
- Karmada Dashboard - alpha release
- Multi-cluster workflow
- Scheduler Enhancement - Optimize scheduling with GPU resources
- Cluster addon management
- Multi-cluster Application
- Multi-cluster monitoring
- Multi-cluster logging
- Multi-cluster storage
- Multi-cluster RBAC
- Multi-cluster networking
- Data migration across clusters
- Image registry across clouds
- Multi-cluster Service Mesh solutions