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roadmap-2022.md 1.93 KB
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jessemeng 提交于 2022-07-27 17:40 . update 2022 roadmap

Crane Roadmap for 2022

Please refer the following sections for Crane release plan of H1 2022, new release will be cut on monthly basis.

Please let us know if you have urgent needs which are not presented in the plan.

0.1.0 [released]

  • Predictor to support Moving Windows and DSP algorithms
  • Resource Request Recommendation and Effective Horizontal Pod Autoscaler
  • Grafana Dashboard to view resource utilization and cost trends
  • fadvisor to support billing

0.2.0:[released]

  • Multiple Metric Adaptor support
  • Node QoS Ensurance for CPU
  • Operation Metrics about R3 and EPA applied ratio

0.3.0 [released]

  • UI with cost visibility and usage optimizations.
  • Request Recommendation adapts with Virtual Kubelet
  • Multiple Triggers for EPA
  • Node QoS Ensurance for Mem
  • Prediction with CPU, Memory, and Business Metrics
  • Scalability to support 1K TSP and 1K EPA

0.4.0 [released]

  • UI to support EPA.

0.5.0 [released]

  • Resource and Replicas Recommendation
  • Load-aware Scheduler

0.6.0 [released]

  • Scalability to support 3k TSP and 3k EPA
  • Algorithm and QoS Documentation
  • EHPA grafana dashboard
  • DSP Algorithm Optimization
  • Support remote adapter for external metric
  • Prediction with business metrics

0.7.0 [July]

  • Recommendation Framework
  • Crane-Descheduler based on CPU/Memory metrics
  • Offline Algorithm Evaluator

0.8.0 [August]

  • External recommendation plugins
  • Built-in CICD Pipeline integration
  • CPU topology aware scheduler
  • Enhanced Console with resource optimization

0.9.0 [September]

  • Flexible conflict prediction and detection
  • Builtin AI Prediction
  • Wastes discovery and dashboard
  • Enhanced Console with more cost visibility dashboard

0.10.0 [October]

  • Business Maturity Model Dashboard
  • In-place Update support by EVPA
  • Kubernetes and Elastic Kubernetes Service price comparison

0.11.0 [November]

  • Multi-cluster cost dashboard

0.12.0 [December]

  • Multi-cluster cost optimization
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