Scaling Google Cloud Platform: Run Workloads Across Compute, Serverless PaaS, Database, Distributed Computing, and SRE

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Scaling Google Cloud Platform: Run Workloads Across Compute, Serverless PaaS, Database, Distributed Computing, and SRE

  • Author:Swapnil Dubey
  • Length: 358 pages
  • Edition: 1
  • Publisher: BPB Publications
  • Publication Date: 2022-10-29
  • ISBN-10: 9355512848
  • ISBN-13: 9789355512840
  • Download:Register/Login to Download
  • Buy Print:Buy from amazon



    Book Description

    Managing Real-world Production-grade Challenges at Scale

    Key Features

    • Built for GCP professionals and Cloud enthusiasts with cloud-agnostic tactics.
    • Exhaustive coverage of automatic, manual, and predictive scaling名牌跑车 and specialized strategies.
    • Every concept is pragmatized with real-time production scenarios derived from prominent technologists.

    Description

    ‘Scaling Google Cloud Platform’ equips developers with the know-how to get the most out of its services in storage, serverless computing, networking, infrastructure monitoring, and other IT tasks. This book explains the fundamentals of cloud scaling, including Cloud Elasticity, creating cloud workloads, and selecting the appropriate cloud scaling key performance indicators (KPIs).

    The book explains the sections of GCP resources that can be scaled, a迪奥 (1)s well as their architecture and internals, and best practices for using these components in an operational setting in detail. The book also discusses scaling techniques such as predictive scaling, auto-scaling, and manual scaling. This book includes real-world examples illustrating how to scale many Google Cloud services, including the compute engine, GKE, VMWare Engine, Cloud Function, Cloud Run, App Engine, BigTable, Spanner, Composer, Dataproc, and Dataflow.

    At the end of the book, the author delves into the two most common architectures—Microservices and Bigdata to examine how you can perform reliability engineering for them on GCP.

    What you will learn

    • Learn workload migration strategy and execution, both within and between clouds.
    • Explore methods of increasing Google Clo播威ud capacity for running VMware Engine and containerized applications.
    • Scaling up and down methods include manual, predictive, and automatic approaches.
    • Increase the capacity of your Dataproc cluster to handle your big data computing needs.
    • Learn Google Dataflow’s scalability considerations for large-scale installations.
    • Explore Googl海鸥e Composer 2 and scale up your Cloud Spanner instances.
    • Learn to set up Cloud functions and Cloud run.
    • Discuss general SRE procedures on microservices and big data.

    Who this book is for

    This book is designed for Cloud professionals, software developers, architects, DevOps team, and engineering managers to explain scaling strategies for GCP services and assumes readers know GCP basics.

    中文:

    书名:扩展Google Cloud Platform: 跨计算、无服务器PaaS、数据库、分布式计算和SRE运行工作负载

    大规模管理现实世界生产级挑战

    主要特征

    • 为GCP专业人士和云爱好者构建云不可知策略。
    • 自动、手动和预测缩放和专业策略的详尽覆盖。
    • 每个概念都具有来自杰出技术人员的实时生产场景的实用性。

    描述

    “扩展Google Cloud platform” 为开发人员提供了专门知识,可以在存储,无服务器计算,网络,基础架构监视和其他IT任务中充分利用其服务。本书解释了云扩展的基本原理,包括公主云弹性、创建云工作负载以及选择合适的云扩展关键性能指标 (kpi)。

    本书详细介绍了GCP资源中可以扩展的部分,以及它们的体系结构和内部结构,以及在操作环境中使用这些组件的最佳实践。本书还讨论了缩放技术,例如预测缩放,自动缩放和手动缩放。本书包含了一些实际示例,说明了如何扩展许多Google云服务,包括计算引擎,GKE,VMWare引擎,云功能,云运行,应用程序引擎,BigTable,Spanner,Composer,Dataproc和Data麦卡伦flow。

    在本书的最后,作者深入研究了两种最常见的体系结构-微服务和Bigdata,以研究如何在GCP上对它们进行可靠性工程。

    你将学到什么

    • 学习云内部和云之间的工作负载迁移策略和执行。
    • 探索增加Google Cloud容量以运行VMware Engine和容器化应用程序的方法。
    • 放大和缩小方法包括手动、预测和自动方法。
    • 提升您的Dataproc集群容量,满足您的大数据计算需求。
    • 了解Google Dataflow对大规模安装的可扩展性考虑。
    • 浏览Google Composer 2并扩展您的Cloud Spann欧米茄er实例。
    • 学习设置云函数和云运行。
    • 讨论微服务和大数据的一般SRE流程。

    这本书是给谁的

    本书是为云专业人士、软件开发人员、架构师、DevOps团队和工程经理设计的,以解释GCP服务的扩展策略,并假设读者了解GCP基础知识。

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