具体描述
Take container cluster management to the next level; learn how to administer and configure Kubernetes on CoreOS; and apply suitable management design patterns such as Configmaps, Autoscaling, elastic resource usage, and high availability. Some of the other features discussed are logging, scheduling, rolling updates, volumes, service types, and multiple cloud provider zones.
The atomic unit of modular container service in Kubernetes is a Pod, which is a group of containers with a common filesystem and networking. The Kubernetes Pod abstraction enables design patterns for containerized applications similar to object-oriented design patterns. Containers provide some of the same benefits as software objects such as modularity or packaging, abstraction, and reuse.
CoreOS Linux is used in the majority of the chapters and other platforms discussed are CentOS with OpenShift, Debian 8 (jessie) on AWS, and Debian 7 for Google Container Engine.
CoreOS is the main focus becayse Docker is pre-installed on CoreOS out-of-the-box. CoreOS:
Supports most cloud providers (including Amazon AWS EC2 and Google Cloud Platform) and virtualization platforms (such as VMWare and VirtualBox)Provides Cloud-Config for declaratively configuring for OS items such as network configuration (flannel), storage (etcd), and user accountsProvides a production-level infrastructure for containerized applications including automation, security, and scalabilityLeads the drive for container industry standards and founded appcProvides the most advanced container registry, Quay
Docker was made available as open source in March 2013 and has become the most commonly used containerization platform. Kubernetes was open-sourced in June 2014 and has become the most widely used container cluster manager. The first stable version of CoreOS Linux was made available in July 2014 and since has become one of the most commonly used operating system for containers.
What You'll Learn
Use Kubernetes with DockerCreate a Kubernetes cluster on CoreOS on AWSApply cluster management design patternsUse multiple cloud provider zonesWork with Kubernetes and tools like AnsibleDiscover the Kubernetes-based PaaS platform OpenShiftCreate a high availability websiteBuild a high availability Kubernetes master clusterUse volumes, configmaps, services, autoscaling, and rolling updatesManage compute resourcesConfigure logging and scheduling
Who This Book Is For
Linux admins, CoreOS admins, application developers, and container as a service (CAAS) developers. Some pre-requisite knowledge of Linux and Docker is required. Introductory knowledge of Kubernetes is required such as creating a cluster, creating a Pod, creating a service, and creating and scaling a replication controller. For introductory Docker and Kubernetes information, refer to Pro Docker (Apress) and Kubernetes Microservices with Docker (Apress). Some pre-requisite knowledge about using Amazon Web Services (AWS) EC2, CloudFormation, and VPC is also required.
作者简介
From the Back Cover
Take container cluster management to the next level; learn how to administer and configure Kubernetes on CoreOS; and apply suitable management design patterns such as Configmaps, Autoscaling, elastic resource usage, and high availability. Some of the other features discussed are logging, scheduling, rolling updates, volumes, service types, and multiple cloud provider zones.The atomic unit of modular container service in Kubernetes is a Pod, which is a group of containers with a common filesystem and networking. The Kubernetes Pod abstraction enables design patterns for containerized applications similar to object-oriented design patterns. Containers provide some of the same benefits as software objects such as modularity or packaging, abstraction, and reuse.CoreOS Linux is used in the majority of the chapters and other platforms discussed are CentOS with OpenShift, Debian 8 (jessie) on AWS, and Debian 7 for Google Container Engine. You will:Use Kubernetes with DockerCreate a Kubernetes cluster on CoreOS on AWSApply cluster management design patternsUse multiple cloud provider zonesWork with Kubernetes and tools like AnsibleDiscover the Kubernetes-based PaaS platform OpenShiftCreate a high availability websiteBuild a high availability Kubernetes master clusterUse volumes, configmaps, services, autoscaling, and rolling updatesManage compute resourcesConfigure logging and scheduling
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About the Author
Deepak Vohra is an Oracle Certified Associate and a Sun Certified Java Programmer. Deepak has published in Oracle Magazine, OTN, IBM developerWorks, ONJava, DevSource, WebLogic Developer’s Journal, XML Journal, Java Developer’s Journal, FTPOnline, and devx.
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这本书的标题中提到了“设计模式”,这立刻让我联想到软件工程中的经典思想——模式是为了解决那些反复出现的问题。在Kubernetes的管理领域,这可能意味着服务网格(Service Mesh)的引入模式、日志和监控数据的聚合模式,或者更底层的持久化存储卷(PV/PVC)的动态供应模式。我非常看重的是,这些模式是否具有足够的通用性,可以脱离特定的云供应商(AWS, GCP, Azure)而独立存在,从而指导我们构建真正的混合云或多云策略。如果它能提供一套可以被不同技术栈团队共享的通用语言和思维框架,那么这本书的价值就不单单是技术手册,而更像是一份组织架构和工程文化建设的参考指南。我特别好奇它如何处理GitOps理念下的状态管理和回滚机制,毕竟,如果设计模式不能完美地融入版本控制的哲学,那一切都是空中楼阁。
这本书的名字听起来就让人精神一振,专注于Kubernetes的管理设计模式,而且还囊括了Docker、CoreOS Linux这些关键技术,这简直是为我们这些在复杂云原生环境中摸爬滚打的工程师量身定做的指南。我一直觉得,Kubernetes的强大在于其灵活性,但这种灵活性也常常带来配置和运维上的巨大挑战。真正区分优秀架构和混乱场面的,往往就在于那些“设计模式”——如何优雅地组织资源、如何处理状态迁移、如何在故障发生时快速恢复。我特别期待书中对那些常见痛点的系统性解决方案,比如如何用声明式配置实现跨集群的服务发现,或者在多租户场景下如何安全、高效地隔离工作负载。如果这本书能提供一套清晰、可复用的蓝图,让我们不再是每次都从零开始“发明轮子”,而是能够站在巨人的肩膀上,那它就绝对是物超所值。它不仅仅是教你“怎么做”,更重要的是阐述了“为什么”要这么做,以及在不同约束条件下如何权衡取舍,这才是真正有价值的管理智慧。
我一直在寻找一本能够真正帮助我从“配置Kubernetes”跨越到“设计Kubernetes生态系统”的书籍。很多资料教你如何部署一个集群,但很少有书愿意深入探讨在集群规模扩大后,管理复杂性呈指数级增长时,应该采取何种高屋建瓴的架构思路。这本书如果能提供一个清晰的层次结构,比如从集群启动和bootstrap层,到应用部署和运行时层,再到观测和治理层,并为每一层推荐一套成熟的设计范式,那它无疑将成为我书架上最常被翻阅的工具书之一。特别是关于安全和合规性的设计模式,例如如何用Admission Controllers强制执行安全基线,或者如何设计RBAC权限模型以最小权限原则运行,这些细节往往是决定一个项目能否顺利进入生产环境的关键。如果这本书能够将这些复杂的实践优雅地转化为一系列易于采纳的“模式”,那么它就完成了它作为一本优秀设计指南的使命。
我最近接手了一个遗留的Kubernetes集群维护工作,那架构简直是一团乱麻,到处都是临时的补丁和未经深思熟虑的YAML文件堆砌。说实话,当时我真希望手边能有一本这样的书,提供一个结构化的视角来看待这些问题。我猜想,这本书的核心价值一定在于它如何将那些分散在各种博客文章、GitHub Issue和社区讨论中的最佳实践,提炼并系统化成易于理解和实施的设计模式。例如,关于持续部署(CD)策略,是应该采用蓝绿部署、金丝雀发布,还是更激进的滚动更新?每种模式背后的操作复杂性和风险点是什么?如果书中能用清晰的图示和对比表格来阐述这些模式在实际生产环境中的表现,那对指导我们制定稳健的发布流程将是无可替代的。我尤其关注它如何处理配置漂移问题,毕竟,在动态的云环境中,保持基础设施代码与实际运行状态的一致性是运维的永恒难题。
对于那些刚刚开始深入Kubernetes,并且已经超越了基础Pod和Service概念的开发者和运维人员来说,这本书听起来就像是一本进阶的“武功秘籍”。我们都知道,Kubernetes的API对象非常丰富,但真正高阶的用法往往隐藏在 Operator 模式、自定义控制器或复杂的网络策略背后。如果这本书能够深入剖析如何利用这些高级特性来构建自愈合、自扩展的系统,那简直太棒了。我希望它不仅仅停留在Kubernetes本身,还能很好地结合Docker容器生命周期的管理,以及CoreOS Linux(现在或许更倾向于Flatcar或类似的不可变基础设施理念)提供的底层操作系统视角。理解了容器运行时环境和操作系统如何协同工作,才能真正构建出既安全又具备高性能的K8s工作负载。我期待看到关于资源效率优化、GPU共享调度或者StatefulSet高级用法的具体设计案例,这些都是日常工作中让人头疼的硬骨头。