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OOSP:用于Pod部署的机会主义优化方案,增强了多层传感.
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概括
对于微服务,Kubernetes的调度可能是低效的. 一种新的自适应置技术通过考虑服务依赖性来优化性能,减少了11.5%的响应时间,并提高了10.04%的吞吐量.
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科学领域:
- 云计算 云计算 云计算 云计算
- 分布式系统 分布式系统
- 集装箱管弦乐的使用方法
背景情况:
- 库贝内茨是容器编排的标准,但其默认调度器有局限性.
- 默认调度器对CPU/内存的关注导致了复杂的微服务架构中的低于最佳性能和资源浪费.
- 服务间通信延迟的增加会对系统的整体性能产生负面影响.
研究的目的:
- 为Kubernetes提出一个自适应的Pod放置优化技术.
- 为了解决默认Kubernetes调度器的性能和资源效率限制.
- 在云原生环境中改进应用程序性能和资源利用.
主要方法:
- 开发了一种使用多层检查的自适应式布放置优化技术.
- 收集和分析多层数据,重点关注合和依赖关系.
- 在虚拟化环境中配置一个Kubernetes集群,用于实验验证.
主要成果:
- 拟议的方法显著优于默认的Kubernetes调度器.
- 实现了高达11.5%的平均响应时间缩短.
- 每秒处理的请求增加了高达10.04%.
结论:
- 适应式置技术有效地最大限度地减少了间通信延迟,并提高了全系统的资源利用率.
- 与传统方法相比,该方法提供了更复杂和更适应的调度方法.
- 这项研究有助于优化云原生环境,并有可能在各种工作负载和云平台上得到更广泛的应用.
