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所在平台: Udemy |
课程主页: https://www.udemy.com/course/build-and-deploy-lambda-functions-aws-with-python-and-boto3/
课程评论：没有评论
课程名称：构建和部署 Lambda 函数：AWS 与 Python 和 Boto3 课程概述： AWS Lambda 是 AWS 最快速增长的服务之一！在本课程中，您将学习如何使用 Python 和 Boto3 开发和部署 Python、Node.js 或 Java 的 Lambda 函数，轻松管理无服务器函数！本课程是关于 AWS 解决方案的一系列课程的一部分，现在是实现无服务器函数的时候了！AWS Lambda 是 AWS 无服务器架构的基石服务，您无需管理 CPU、内存、操作系统或补丁等基础设施。您只需关注实现和代码即可！ 在本课程中，我们将一步一步详细介绍将要构建的内容和您需要在计算机上准备的环境。课程将包含 Windows 和 MacOS 用户的两个部分，展示如何准备计算机环境以便使用 AWS Lambda。我们将演示如何安装 Python、Boto3，并配置这些工具的工作环境。此外，我还会一步一步指导您如何创建 AWS 账户，并确保您能迅速开始使用 AWS！ 准备好工作环境后，我们将开始实施 AWS 的解决方案。首先，我们将为 Lambda 函数创建 IAM 访问策略，以便其能够访问和与其他 AWS 资源（如 S3、CloudWatch 等）进行通信。我们将创建一个 IAM 角色，使我们的 Lambda 函数能够代表我们在 AWS 上执行，并将 IAM 策略附加到 IAM 角色，以完成运行 Lambda 函数所需的权限设置。 接下来，我们将从头开始开发 Python Lambda 函数，编写适当的处理程序，并学习如何将其打包为 zip 文件，与 AWS 进行交互。在成功部署 Python Lambda 函数后，我们将检查 AWS 控制台，以确保其配置符合预期。 随后的步骤是实施和部署 Node.js Lambda 函数，我们将重复相同的步骤为其创建并部署函数。之后，我们将启动 Eclipse IDE，创建我们的第一个 Java Lambda 函数，并使用 Maven 将其打包为可执行的 JAR 文件，随后再次进行部署并验证。 接下来，我们将学习如何轻松调用和管理 Lambda 函数，包括别名、版本控制、使用环境变量、更新源代码等。我们还将掌握对 Lambda 函数进行基本 CRUD 操作的所有方法并演示其简易性。 让我们赶紧开始开发和部署 Lambda 函数到 AWS Lambda 吧！
AWS Lambda is one of the fastest growing services of AWS! Join me in this course to learn how you can develop and deploy Python, Node.js or Java Lambda functions using Python and Boto3; manage your serverless functions easily! This course is part of a series of courses on AWS solutions with Python and Boto3 and now it's time to implement serverless functions! AWS Lambda is a cornerstone service for serverless architectures on AWS. You do not manage infrastructure like CPU, memory, OS or patches you name it! All you have to do and worry about is your implementation and code! Let's take a closer look at what we're going to cover in this course step-by-step. In this course, we will start off with what we'll build throughout the course and what you need to have on your computer to follow along with me. Don't worry; I'll explain everything you need very clearly and I'll show you what you need to install and setup on your computer to work with AWS Lambda. There will be two different sections for Windows and MacOS users. These sections are basically identical and show how you can prepare your computer environment to be ready to work with AWS Lambda! I'll show you how to install Python, Boto3 and configure your environments for these tools. I'll also show you how you can create your own AWS account step-by-step and you'll be ready to work AWS in no time! When we're done with preparing our environment to work AWS with Python and Boto3, we'll start implementing our solutions for AWS. First thing we'll do is to create an IAM Access Policy for our Lambda Functions to access and communicate with other AWS resources like S3, CloudWatch and so on. Once we have it created, we'll also create an IAM Role for our Lambda Function to execute and run on AWS on our behalf. And as for the most crucial part of this process, we'll attach the IAM Policy to IAM Role so we will be complete on permissions and roles to run our Lambda Functions! Next step is to develop a Python Lambda function from scratch! We'll develop a Python function with a proper handler and start implementing the way to develop it to AWS. For that purpose - since AWS is looking for bytes of the source code for Lambda functions - we'll develop a Utility class where we'll implement the way to package our Lambda Function first as zip file. Once we do that, we'll then read the bytes of the file and pass that information to our deployer method. Apart from source code, we will also provide our Lambda function a runtime, name and so on. Once we successfully deploy our Python Lambda function, we'll check it out on AWS console and verify that its configured as we expect it to be. Next up is the implementation and deployment of a Node.js Lambda function! We'll follow the same steps again to implement and create our own Node.js Lambda function and deploy it using our genericly-implemented solution for deployment. Once we've done that, we'll again go to AWS console and verify our Lambda function. Java Lambda functions are up next! We'll launch Eclipse IDE - which is basically the easiest way to create and work with Java Lambda functions - and install AWS Toolkit first. Once we have it, we will create our very first Java Lambda function and then we'll package it as an executable JAR file using Maven. Next thing to do is to deploy our Java Lambda function and once we do that, we'll go to AWS console and verify it. Now is time to invoke our Lambda functions and you will see how easy it is to do so! We'll call our function and parse the response from AWS! Next up is to manage our Lambda function in various ways and that includes Aliasing, Versioning, using Environment Variables, Updating the Source Code and much more! We'll also learn all the basic CRUD operations we can do against Lambda functions and you'll again see how easy those are too! Let's not lose any more time and jump right into developing and deploying Lambda functions to AWS Lambda!
