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所在平台: Udemy |
课程主页: https://www.udemy.com/course/aurora-postgresql/
课程评论：没有评论
课程名称：从A到Z学习Amazon Aurora PostgreSQL 课程概述： 本课程专注于设计、构建和管理Aurora PostgreSQL集群，不教授SQL或数据库设计。适合对象包括希望利用Aurora PostgreSQL的云架构师和工程师，深入了解Aurora Postgres的数据库管理员，以及希望利用Aurora Postgres构建云原生应用的开发者。此外，任何对Aurora Postgres与社区版Postgres的区别感兴趣的人士也将受益于本课程。 课程目标： 完成本课程后，学员将能够： - 设计和部署高可用、可扩展的Aurora PostgreSQL集群 - 从网络、数据、身份与访问等多方面确保数据库集群的安全 - 有效利用Aurora的功能，如全局数据库、无服务器、克隆和缓存管理等 - 使用CloudWatch指标、事件和日志进行监控 - 使用性能洞察等工具进行查询性能调优 先决条件： 本课程适合任何希望在其云应用中使用AWS Aurora PostgreSQL的人员。如果您对PostgreSQL不太熟悉，也无需担心，课程将从PostgreSQL的基础知识开始。 - 有AWS实操经验 - 熟悉任意关系数据库管理系统（RDBMS） - 有基本的Unix Shell脚本经验 - 乐于学习 课程大纲： 课程分为多个章节，每个章节开始时都有“章节目标”的课程内容。为了更好地了解课程涵盖的主题，建议查看您感兴趣章节的第一节课程（预览）。主要内容包括： - PostgreSQL基础 - Aurora架构深入解析与集群设置 - 监控特性和工具（CloudWatch、增强监控、性能洞察等） - 设计高可用且可扩展的集群 - 集群配置管理 - 查询性能调优 - Aurora Postgres安全性 - 有效使用Aurora功能，如全局数据库、无服务器、缓存管理 - Aurora灾难恢复 - 备份恢复 - 集群管理任务，如清理（vacuum）、分析（analyze）、解释（explain）等 为何开设此课程： Aurora数据库架构复杂且与市场上其他数据库大相径庭。个人学习Aurora时，最大的挑战是缺乏Aurora特定的信息资源，而Amazon Aurora文档网站并不是高效的学习方式。因此，我决定创作此课程，以便帮助他人更快地掌握Aurora知识，从而加速学习过程。 免责声明： 课程内容基于公开可用的资源，如AWS文档及博客，所表达的观点和意见仅代表我个人（Rajeev Sakhuja），并不反映雇主或Amazon/AWS的意见。
PS: Focus of this course is on Designing, Building and Managing Aurora PostgreSQL clustersThis course will NOT teach you SQL or Database designWho will benefit from this course?Cloud Architects, & Engineers looking to leverage Aurora PostgreSQLDatabase Administrators interested in diving deep into Aurora PostgresCloud Developers looking to leverage Aurora Postgres for building cloud native applicationsAnyone interested in learning how Aurora Postgres is different from community version of PostgresObjectives By the end of this course you will be able to:Design & deploy highly available, and scalable Aurora PostgreSQL clustersEnsure security of your DB cluster from all perspectives (Network, Data, A & A...)Effectively use the Aurora features such as Global Database, Serverless, Cloning, Cache management etc.Carry out monitoring using CloudWatch metrics, Events, LogsQuery performance tuning using tools such as Performance InsightsPre-RequisitesThis course is intended for anyone who is interested in using AWS Aurora PostgreSQL database for their cloud applications. If you are new to PostgreSQL then no worries as the course starts with the fundamentals of PostgreSQL.Hands on with AWSExperience with any RDBMSBasic Unix shell scriptingOpen to learnCourse outlineCourse is divided into multiple sections. Each section starts with a lesson titled "Section Objectives". To gain a better understanding of the topics covered in the course, please check out the first lesson (preview) in sections of your interest.Fundamentals of PostgreSQLAurora Architecture deep dive & cluster setupMonitoring features and tools (CloudWatch, Enhanced Monitoring, Performance Insights..)Designing highly available, and scalable clustersCluster configuration managementQuery performance tuningAurora Postgres SecurityEffectively using Aurora features such as Global Database, Serverless, Cache management Aurora Disaster RecoveryBackup RecoveryCluster management tasks such as vaccuming, analyze, explain etc.Why I built this course?Aurora is complex and architecturally very different from the databases available in the market. When I started to learn it, the biggest challenge was the non availability of Aurora specific information. The only source of information is the Amazon Aurora documentation website which in my humble opinion is not the most effective way to learn. It took me quite sometime to wrap my head around Aurora's architecture and features; the tutorials in the documentation involve manual steps, mostly on the console, as a result they are not easy to follow. Long story short, for folks new to Aurora (& Postgres) learning Aurora can be daunting. Based on my personal experience with learning Aurora Postgres, I decided to put together this course to help others get up to speed with Aurora in minimum possible time. So if I have to describe in one line, why I built this course - "It is to accelerate students learning".DisclaimerCourse content developed using publicly available sources such as AWS documentation & blogsOpinions/views expressed in the course are my (Rajeev Sakhuja) own and does not reflect opinions/views of my employer or Amazon/AWS
