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所在平台: Udemy |
课程主页: https://www.udemy.com/course/building-a-scalable-serverless-microservice-rest-data-api/
课程评论：没有评论
课程名称：构建可扩展的无服务器微服务REST数据API 课程概述：近年来，软件架构发生了显著变化，从传统的单体架构转向微服务架构，这种架构允许小型独立的部署，提供了更大的灵活性和敏捷交付能力。过去，虚拟机和容器是部署微服务的主要选项，但它们涉及大量的操作工作、配置和维护。最近，随着开发者生产力的提升、自动扩展能力的增强及运营成本的降低，无服务器计算已受到越来越多的关注。通过结合微服务与无服务器计算，组织可以将服务器及容量规划交由云服务提供商管理，从而更轻松地实现大规模的部署和运行。 本课程展示了如何为您的组织构建一个端到端的无服务器应用程序。我们选定了一个数据API用例，它能够降低成本，并为您及您的客户在使用或展示应用程序、指标和洞察数据方面提供更多灵活性。课程中我们将使用最新的无服务器部署和构建框架，分享我们的测试经验，并提供在生产环境中运行无服务器堆栈的最佳实践。 作者简介：理查德·T·弗里曼（Richard T. Freeman）博士目前在JustGiving工作，这是一个科技公益公司，也是全球最受信赖的在线捐赠社交平台，帮助2200万用户在164个国家筹集了45亿美元，用于27,000多个公益原因。他同时提供短期的云架构和机器学习咨询服务。理查德是一位成果导向的认证AWS解决方案架构师、数据工程师和数据科学家，在交付基于云的大数据分析、非结构化数据、高吞吐量和可扩展解决方案方面取得了显著成功。他曾在Capgemini为财富全球500强公司处理大型复杂项目，具有非常多样化、具有挑战性和多元文化的商业环境经验。理查德拥有计算机科学的坚实背景，拥有计算机系统工程硕士（MEng）和机器学习、人工智能及自然语言处理博士（Ph.D.）学位。他在慈善、保险、零售银行、招聘、金融服务、金融监管、中央政府和电子商务等多个行业工作，提供复杂事件处理、商业智能、企业内容管理和业务流程管理解决方案的设计、架构与技术咨询，开发了多个大规模图形、机器学习、自然语言处理、云数据仓库、ETL数据管道、推荐引擎和实时流分析系统的云基础设施产品，拥有超过三年的AWS无服务器计算生产经验。
In the past few years, there has been a shift away from monolithic architecture (with for example its large centralized deployments) to microservice architectures with small independent deployments, allowing much more flexibility and agile delivery. Traditionally virtual machines and containers were the main options for deploying microservices but they involve a lot of operational effort, configuration, and maintenance. More recently, there has been a growing interest in Serverless computing due to the increase in developer productivity, built in auto-scaling abilities, and reduced operational costs. In combining both microservices and serverless computing, organizations will benefit from having the servers and capacity planning managed by the cloud provider, making them much easier to deploy and run at scale.In this course we show you how to build an end-to-end serverless application for your organization. We have selected a data API use case that could reduce costs and give you more flexibility in how you and your clients consume or present your application, metrics and insight data. We make use of the latest serverless deployment and build framework, share our experience on testing, and provide best practices for running a serverless stack in a production environment. About the Author Richard T. Freeman, Ph.D. currently works for JustGiving, a tech-for-good company and the world's most trusted social platform for online giving that's helped 22 million users in 164 countries raise $4.5 billion for over 27,000 good causes. He is also offering short-term freelance cloud architecture & machine learning consultancy.He is a highly accomplished results-driven hands-on certified AWS Solutions Architect, Data Engineer and Data Scientist with proven success in delivering cloud-based big data analytics, unstructured data, high-volume, and scalable solutions. At Capgemini, he worked on large and complex projects for Fortune Global 500 companies and has experience in extremely diverse, challenging and multi-cultural business environments. Richard has a solid background in computer science and holds a Master of Engineering (MEng) in computer systems engineering and a Doctorate (Ph.D.) in machine learning, artificial intelligence and natural language processing.He has worked in charity, insurance, retail banking, recruitment, financial services, financial regulators, central government and e-commerce sectors, where he: Provided design, architecture and technical consulting on client site for complex event processing, business intelligence, enterprise content management, and business process management solutions. Delivered in-house production cloud-based big data solutions for large-scale graph, machine learning, natural language processing, cloud data warehousing, ETL data pipeline, recommendation engines, and real-time streaming analytics systems. Worked closely with IBM and AWS and presented at industry events and summits Published research articles in numerous journals, presented at conferences and acted as a peer-reviewer Has over three years of production experience with Serverless computing on AWS
