terraforming-gcp：使用terraform，自己部署一个pcf

Spotty大大简化了在和上进行深度学习模型的培训： 它使在GPU实例上的训练与在本地计算机上的训练一样简单 它会自动管理所有必要的云资源，包括图像，卷，快照和SSH密钥 它使每个人都可以通过几个命令在云中训练您的模型 它使用轻松地将远程进程与其终端分离 通过使用和它可以为您节省多达70％的成本 文献资料 请参阅。 阅读文章中对于现实世界的例子。 安装 要求： Python> = 3.6 如果使用的是AWS，请参阅AWS CLI（请参阅）。 如果您使用的是GCP，请使用Google Cloud SDK（请参阅 ） 使用安装或升级Spotty： $ pip install -U spotty 开始使用 准备一个spotty.yaml文件并将其放在项目的根目录中： 请参阅的文件规范。 阅读文章为一个真实的例子。 启动实例： $ spotty start 它将运行竞价型实例，还原快照（如果有），将项目与正在运行的实例同步，然后将Docker容器与环境一起启动。 训练模型或运行笔记本。 要通过SSH连接到正在运行的容器，请使用以下命令： $ spotty sh

Google Cloud Platform Ansible系列 该集合提供了一系列用于与进行交互的Ansible模块和插件 该集合适用于Ansible 2.9+ 安装 ansible-galaxy collection install google.cloud 资源支持 App Engine防火墙规则（gcp_appengine_firewall_rule，gcp_appengine_firewall_rule_facts） BigQuery资料集（gcp_bigquery_dataset，gcp_bigquery_dataset_facts） BigQuery表（gcp_bigquery_table，gcp_bigquery_table_facts） 云Bigtable实例（gcp_bigtable_instance，gcp_bigtable_instance_facts） 云构建触发器（gcp_cloudbuild_trigger，gcp_cloudbuild_trigger_facts） 云函数CloudFunction（gcp_cloudfunctions_cloud

云服务经纪人 这是构建用于和Kubernetes的服务代理。 它遵循 。 Cloud Service Broker是的扩展，并使用公开服务。 只要您的目标公共云具有，就可以使用标准cf CLI命令通过公共接口来服务。 与传统的，由IaaS提供的服务代理相比，一些好处包括： 易于扩展和维护减少与远程团队的交流，更多地完成工作。 所有经纪服务的一名普通经纪人。 Cloud Service Broker将服务代理功能与其公开的服务目录分离。 开箱即用的Credhub集成CredHub加密和管理与您使用云服务相关的所有秘密。 社区当您通过公开服务时，可以使使用CSB的每个人都可以使用。 使用轻松迁移现有服务我们称之为“无迁移”迁移，更多内容即将推出！ 建筑 公开路线图 有关当前“核心代理”（与IaaS无关）功能的列表，请在此处查看我们在Trello上的最新路线图： : Azure路线图： : AWS路线图： : GCP路线图： ： 安装 该服务代理可以作为CF应用程序安装。 请参阅以下说明： 用法 对于操作员：有关配置服务代理的详细信息，请参阅 。 对于开

入侵云 入侵云是针对云基础架构的攻击的开源百科全书。 贡献 欢迎任何人提出您想要撰写的主题的拉取请求。 将检查内容的质量和准确性。 请保留与云相关材料（AWS，Azure，GCP，Docker，K8等）相关的主题。

Kubestack Gitops框架 基于Terraform和Kustomize的托管Kubernetes服务。 它旨在： 通过操作和应用程序集群对明确区分基础结构和应用程序环境，从而提供全面的可测试性 确保将K8的集群配置，周围的基础架构（例如DNS，IP）和集群服务（例如Ingress）一起维护 跨云提供商统一应用程序环境 实现可持续且完全自动化的Gitops工作流程 有关Kubestack的最简单方法， 。 快速入门将引导用户存储库和第一个集群对。 有关如何将其扩展到多集群和/或多云的示例，请参见tests 。 仓库布局 该存储库将Terraform模块保存在与相应提供者名称匹配的目录中，例如aws ， azurerm ， google 。 另外， common保留了所有提供程序都使用的模块。 最值得注意的是，适用于确保一致命名方案的metadata模块和将Kustomize集成到Terraform中的cluster_services模块。 每个特定于云提供商的模块目录始终具有一个cluster和一个_modules目录。 集群模块是面向用户的，一旦Kubestack退出be

实现了GIS中的影像配准，利用工具栏实现对打开影像的放大、缩小、平移、漫游和GCP输入，类别配准等初步功能。有待完善。 利用VS2010实现，需要.NetFrame 4.0环境才可以运行。

Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective Key Features Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform Make intelligent choices about which cloud technology works best for your use-case Leverage Google Cloud Platform to analyze and optimize technical and business processes Book Description Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream – the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design. What you will learn Set up GCP account and utilize GCP services using the cloud shell, web console, and client APIs Harness the power of App Engine, Compute Engine, Containers on the Kubernetes Engine, and Cloud Functions Pick the right managed service for your data needs, choosing intelligently between Datastore, BigTable, and BigQuery Migrate existing Hadoop, Spark, and Pig workloads with minimal disruption to your existing data infrastructure, by using Dataproc intelligently Derive insights about the health, performance, and availability of cloud-powered applications with the help of monitoring,

The Google Cloud Certified Professional Cloud Architect Study Guide is the essential resource for anyone preparing for this highly sought-after, professional-level certification. Clear and accurate chapters cover 100% of exam objectives―helping you gain the knowledge and confidence to succeed on exam day. A pre-book assessment quiz helps you evaluate your skills, while chapter review questions emphasize critical points of learning. Detailed explanations of crucial topics include analyzing and defining technical and business processes, migration planning, and designing storage systems, networks, and compute resources. Written by Dan Sullivan―a well-known author and software architect specializing in analytics, machine learning, and cloud computing―this invaluable study guide includes access to the Sybex interactive online learning environment, which includes complete practice tests, electronic flash cards, a searchable glossary, and more. Providing services suitable for a wide range of applications, particularly in high-growth areas of analytics and machine learning, Google Cloud is rapidly gaining market share in the cloud computing world. Organizations are seeking certified IT professionals with the ability to deploy and operate infrastructure, services, and networks in the Google Cloud. Take your career to the next level by validating your skills and earning certification. Design and plan cloud solution architecture Manage and provision cloud infrastructure Ensure legal compliance and security standards Understand options for implementing hybrid clouds Develop solutions that meet reliability, business, and technical requirements The Google Cloud Certified Professional Cloud Architect Study Guide is a must-have for IT professionals preparing for certification to deploy and manage Google cloud services.

如果影像存在rpb文件,使用此程序可以自行完成校正, 无校正文件需要改造程序构造相关输入即可, 基于GDAL开发,亦可用于 跨平台