From 4b8a42df69b67d52d744c8bead95ea21c83b5526 Mon Sep 17 00:00:00 2001 From: qmhu Date: Mon, 8 May 2023 09:19:35 +0000 Subject: [PATCH] deploy: 912d800c6de07fb22804a04068921c967296f49c --- .../index.html" | 4 +- .../index.html | 4 +- .../how-kujiale-adopt-ehpa/index.html | 4 +- .../index.html | 4 +- docs/contributing/code-standards/index.html | 4 +- docs/contributing/contributing/index.html | 2 +- docs/contributing/developer-guide/index.html | 2 +- docs/core-concept/architecture/index.html | 2 +- .../resource-optimize-model/index.html | 2 +- .../timeseriees-forecasting-by-dsp/index.html | 2 +- .../installation-cli-tool/index.html | 2 +- .../installation/installation/index.html | 2 +- .../installation/quick-start/index.html | 2 +- docs/getting-started/introduction/index.html | 2 +- .../index.html | 2 +- .../index.html | 4 +- .../index.html | 2 +- .../index.html | 4 +- docs/roadmap/roadmap-2022/index.html | 2 +- docs/roadmap/roadmap-2023/index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../using-qos-ensurance/index.html | 2 +- .../dynamic-scheduler-plugin/index.html | 2 +- .../how-to-develop-recommender/index.html | 2 +- .../hpa-recommendation/index.html | 2 +- .../idlenode-recommendation/index.html | 2 +- .../recommendation-framework/index.html | 2 +- .../replicas-recommendation/index.html | 2 +- .../resource-recommendation/index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../using-time-series-prediction/index.html | 2 +- en/sitemap.xml | 2 +- search/index.html | 2 +- sitemap.xml | 2 +- .../index.html" | 4 +- .../index.html | 4 +- .../how-kujiale-adopt-ehpa/index.html | 4 +- .../index.html | 4 +- .../contributing/code-standards/index.html | 4 +- .../docs/contributing/contributing/index.html | 2 +- .../contributing/developer-guide/index.html | 2 +- .../docs/core-concept/architecture/index.html | 2 +- .../resource-optimize-model/index.html | 2 +- .../timeseriees-forecasting-by-dsp/index.html | 2 +- .../installation-cli-tool/index.html | 2 +- .../installation/installation/index.html | 2 +- .../installation/quick-start/index.html | 2 +- .../getting-started/introduction/index.html | 2 +- zh-cn/docs/index.xml | 43 +++++++++++++++++++ .../index.html | 2 +- .../index.html | 4 +- .../index.html | 2 +- .../index.html | 4 +- zh-cn/docs/roadmap/roadmap-2022/index.html | 2 +- zh-cn/docs/roadmap/roadmap-2023/index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../using-qos-ensurance.zh/index.html | 2 +- .../dynamic-scheduler-plugin/index.html | 2 +- zh-cn/docs/tutorials/index.xml | 43 +++++++++++++++++++ .../index.html | 32 +++++++++++++- .../how-to-develop-recommender/index.html | 2 +- .../hpa-recommendation/index.html | 2 +- .../idlenode-recommendation/index.html | 2 +- .../recommendation-framework/index.html | 2 +- .../replicas-recommendation/index.html | 2 +- .../resource-recommendation/index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../using-time-series-prediction/index.html | 2 +- zh-cn/search/index.html | 2 +- zh-cn/sitemap.xml | 2 +- 80 files changed, 207 insertions(+), 93 deletions(-) diff --git "a/blog/1/01/01/crane-v0.7\351\200\232\350\277\207\346\216\247\345\210\266\345\217\260\344\270\200\351\224\256\350\212\202\347\234\201\344\272\221\346\210\220\346\234\254/index.html" "b/blog/1/01/01/crane-v0.7\351\200\232\350\277\207\346\216\247\345\210\266\345\217\260\344\270\200\351\224\256\350\212\202\347\234\201\344\272\221\346\210\220\346\234\254/index.html" index 49de91cb3..14c5cc5cc 100644 --- "a/blog/1/01/01/crane-v0.7\351\200\232\350\277\207\346\216\247\345\210\266\345\217\260\344\270\200\351\224\256\350\212\202\347\234\201\344\272\221\346\210\220\346\234\254/index.html" +++ "b/blog/1/01/01/crane-v0.7\351\200\232\350\277\207\346\216\247\345\210\266\345\217\260\344\270\200\351\224\256\350\212\202\347\234\201\344\272\221\346\210\220\346\234\254/index.html" @@ -5,13 +5,13 @@ 资源推荐框架 Recommendation Framework Crane 的资源推荐,副本推荐功能在腾讯内部落地帮助自研业务每月节省了大量的成本,取得了很好的效果,详情请见:https://mp.weixin.qq.com/s/1SeMzcf_VRvRysZ9NLI-Sw 。同时,我们认为自动分析集群资源找到浪费并给出优化建议是帮助企业降本的重要方法,引入更多的分析类型至关重要。 因此在 0.7.0 版本中,Crane 设计了 Recommendation Framework,它提供了一个可扩展的推荐框架以支持多种云资源的分析,并内置了多种推荐器:资源推荐,副本推荐,闲置资源推荐。Recommendation Framework 通过 RecommendationRule 和 Recommendation CRD 描述了如何进行资源的分析推荐。 智能推荐的规则 -apiVersion: analysis.crane.io/v1alpha1 kind: RecommendationRule metadata: name: workloads-rule labels: analysis.crane.io/recommendation-rule-preinstall: "true" spec: runInterval: 24h # 每24h运行一次 resourceSelectors: # 资源的信息 - kind: Deployment apiVersion: apps/v1 - kind: StatefulSet apiVersion: apps/v1 namespaceSelector: any: true # 扫描所有namespace recommenders: # 使用 Workload 的副本和资源推荐器 - name: Replicas - name: Resource 推荐的结果">Intelligent Autoscaling Practices Based on Effective HPA for Custom Metrics | Crane