Kubernetes 中请求处理流程 什么是准入控制器 用 Python 实现准入控制器 与其他方案对比 Kubernetes 架构 kube-apiserver Kubernetes 集群的核心组件 处理集群内外的所有请求 Kubernetes 请求处理流程  API Handler 匹配处理链路（ /apis ）  认证 / 授权  Mutating Admission ：可进行变更操作

大规模生产环境下的 Faster-CPython 主讲人： 王文洋 老板思维 已知：公司有xx个计算集群 每个集群有xxxxx个core Python进程占比xx% 如果：提升 10% 那么：可以节省 xx * xxxxx * xx% * 10%个core 降本 xx * xxxxx * xx% * 10% * n >> 我的工资 结论：。。。 Why

ResearchAndMarkets.com Python赋能智慧物流 1-行业背景 · AMR调度系统 AGV/AMR两大核心技术领域 AGV/AMR本体定位/控制技 术 AGV/AMR集群调度系统 -状态机 -通讯模块 -运动控制 -任务执行 -外设 对接 -任务调度 -路径规划 -交通管制 -AMR控 制 -外设对接 Python赋能智慧物流 1-行业背景 · 传统AMR调度系统

Kapacitor • InfluxDB：⾼高性能的时序数据库。 • vs ES: 8X写⼊入，少4X磁盘占⽤用，3~7响应速度 • Telegraf：⽀支持200+数据渠道 • 开源免费版本缺少集群、安全、管理理等功能 • Chronograf：不不如Grafana强⼤大灵活 Elastic Stack (BELK) • Beats + Elasticsearch + Logstash

distribute work across threads or machines. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via No No Zookeeper Experimental No No Experimental brokers may be functional but they don’t have dedicated maintainers. Missing monitor support means that the transport doesn’t implement events, and as tutorial we keep everything contained in a single module, but for larger projects you want to create a dedicated module. Let’s create the file tasks.py: from celery import Celery app = Celery('tasks', brok

distribute work across threads or machines. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via No No Zookeeper Experimental No No Experimental brokers may be functional but they don’t have dedicated maintainers. Missing monitor support means that the transport doesn’t implement events, and as tutorial we keep everything contained in a single module, but for larger projects you want to create a dedicated module. Let’s create the file tasks.py: from celery import Celery app = Celery('tasks', brok

distribute work across threads or machines. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via No No Zookeeper Experimental No No Experimental brokers may be functional but they don’t have dedicated maintainers. Missing monitor support means that the transport doesn’t implement events, and as tutorial we keep everything contained in a single module, but for larger projects you want to create a dedicated module. Let’s create the file tasks.py: from celery import Celery app = Celery('tasks', brok

distribute work across threads or machines. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via Celery Documentation, Release 4.1.0 Experimental brokers may be functional but they don’t have dedicated maintainers. Missing monitor support means that the transport doesn’t implement events, and as tutorial we keep everything contained in a single module, but for larger projects you want to create a dedicated module. Let’s create the file tasks.py: from celery import Celery app = Celery('tasks', brok

distribute work across threads or machines. A task queue’s input is a unit of work called a task. Dedicated worker processes constantly monitor task queues for new work to perform. Celery communicates via Celery Documentation, Release 4.0.1 Experimental brokers may be functional but they don’t have dedicated maintainers. Missing monitor support means that the transport doesn’t implement events, and as tutorial we keep everything contained in a single module, but for larger projects you want to create a dedicated module. Let’s create the file tasks.py: from celery import Celery app = Celery('tasks', brok