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quest

GCP Essentials

In this Quest, the most popular Quest of all time, get your first hands-on experience with Google Cloud. Get comfortable with the basics, like spinning up a VM and configuring key infrastructure tools, then challenge yourself to the next level.

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quest

Baseline: Infrastructure

This Quest of all-Introductory-level Self-Paced Labs is intended for the complete beginner in Google Cloud. In this eleven-lab sequence, you will get your first-touch experiences with the Google Cloud services that provide basic infrastructure building blocks that make up core components of any production cloud environments.

quest

Baseline: Data, ML, AI

This Quest of all-Introductory-level Self-Paced Labs is intended for the complete beginner in Google Cloud. In these short hands-on labs, you will get your first-touch experiences with a subset of the Google Cloud services that provide tools for working with big (and small!) data and machine learning / artificial intelligence services in Google Cloud.

quest

Baseline: Deploy & Develop

This Quest of all-Introductory-level Self-Paced Labs is intended for the complete beginner in Google Cloud. In these short hands-on labs, you will get your first-touch experiences with a subset of the Google Cloud services that provide tools for creating and deploying applications: App Engine, the SDK, Source Tools, data stores for your application data, and useful tools for security and privacy, all provided by Google Cloud.

quest

Cloud Architecture

This Quest is intended to provide hands-on practice for those preparing for the <A HREF="https://cloud.google.com/certification/cloud-architect">Google Cloud Certified Professional Cloud Architect Certification</A>. Students will get hands-on exposure to a wide range of Google Cloud Services and techniques which are closely mapped to the topic areas in the certification test. Be aware that while practice with these labs will increase your knowledge and abilities in these topic areas, you will need other preparation to succeed in the question and answer test itself (such as work experience).

quest

Data Engineering

This Quest is intended to provide hands-on practice for those preparing for the <A HREF="https://cloud.google.com/certification/data-engineer">Google Cloud Certified Professional Data Engineer Certification</A>. Students will get hands-on exposure to a wide range of Google Cloud Services and techniques which are closely mapped to the topic areas in the certification test. Be aware that while practice with these labs will increase your knowledge and abilities in these topic areas, you will need other preparation to succeed in the question and answer test itself (such as work experience).

hands-on lab

Advanced Design Patterns using Amazon DynamoDB

DynamoDB Workshop CloudFormation Template: Create an Amazon EC2 instance running the Amazon Linux with the applications required for running the DynamoDB workshop.

hands-on lab

VPC Network Peering

Google Cloud Platform (GCP) Virtual Private Cloud (VPC) Network Peering allows private connectivity across two VPC networks regardless of whether or not they belong to the same project or the same organization.

hands-on lab

Build a Serverless Text-to-Speech Application with Amazon Polly

This lab builds a complete serverless application that demonstrates how to convert text-to-speech using Amazon Polly.

hands-on lab

Improving Network Performance I

In this lab, you'll work on practical elements of performance testing, with an eye to improving network bandwidth in your environment by using different core sizes and internal vs. external networks.

hands-on lab

Network Performance Testing

In this lab, you'll learn important connectivity, performance, testing, and troubleshooting techniques in the Google Cloud Networking insfrastructure environment.

hands-on lab

Improving Network Performance II

In this lab, you'll work on further practical elements of performance testing, toward improving network server performance by using load balancing and content caching.

hands-on lab

Scanning User-generated Content Using the Cloud Video Intelligence and Cloud Vision APIs

This lab will show you how to deploy a set of Cloud Functions in order to process images and videos with the Cloud Vision API and Cloud Video Intelligence API.

hands-on lab

Building High Availability and High Bandwidth NAT Gateways

This lab shows you how to set up multiple NAT gateways with Equal Cost Multi-Path (ECMP) routing and autohealing enabled for a resilient and high-bandwidth deployment.

hands-on lab

Create a Custom Network Using Deployment Manager

This lab creates a complex Deployment Manager (DM) configuration for deploying a custom network resource in Google Cloud Platform. It also explains the basic fundamental block of developing a Deployment Manager.

hands-on lab

使用 Amazon Redshift

本实验演示了如何使用 Amazon RedShift 来创建集群、加载数据、运行查询以及监控性能。注意:在本实验中,学员需要下载免费的 SQL 客户端。

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hands-on lab

Setting up Jenkins on Kubernetes Engine

This hands-on lab will show you how to set up Jenkins on Google Kubernetes Engine to help orchestrate your software delivery pipeline.

hands-on lab

Rent-a-VM to Process Earthquake Data

In this lab you spin up a virtual machine, configure its security, access it remotely, and then carry out the steps of an ingest-transform-and-publish data pipeline manually. This lab is part of a series of labs on processing scientific data.

hands-on lab

Using Ruby on Rails with Cloud SQL for PostgreSQL

In this lab, you'll learn how to deploy a new Ruby on Rails application using Google Cloud SQL for PostgreSQL to Google App Engine Flexible environment.

hands-on lab

Cloud Source Repositories: Qwik Start

In this lab you will create a local Git repository that contains files for a sample App Engine application, add a GCP repository as a remote, and push the contents of the local repository.

hands-on lab

Detect Labels, Faces, and Landmarks in Images with the Cloud Vision API

The Cloud Vision API lets you understand the content of an image by encapsulating powerful machine learning models in a simple REST API. In this lab you’ll send an image to the Cloud Vision API and have it identify objects, faces, and landmarks.

hands-on lab

Creating a Persistent Disk

In this hands-on lab, you’ll learn how to create a persistent disk and use it on a Google Compute Engine virtual machine. You’ll also learn about zones, regions, and different disk types.

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hands-on lab

Cloud Security Scanner: Qwik Start

The Cloud Security Scanner identifies security vulnerabilities in your Google App Engine web applications.

hands-on lab

Internal Load Balancer

Internal Load Balancer offers you the possibility to load balance TCP/UDP traffic without exposing your VMs via a public IP to the Internet. In this lab we will create a public facing web server to serve the result of a simple web application.

hands-on lab

Amazon Elastic Block Store (Amazon EBS) 的简介

本指南介绍了如何使用 AWS 管理控制台操作 Amazon Elastic Block Store (EBS)。

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hands-on lab

使用脚本和 AWS CLI 自动化 AWS 服务

此实验室展示了访问和管理 AWS 服务的三种方法:通过 AWS 管理控制台、AWS 命令行接口 (CLI) 和 AWS 软件开发工具包 (SDK)。您将使用这三种方法中的一种或多种来访问 Amazon S3、Amazon EBS、Amazon EC2 和 Amazon CloudWatch。

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hands-on lab

BigQuery: Qwik Start - Command Line

This hands-on lab shows you how to query public tables and load sample data into BigQuery using the Command Line Interface. Watch the short video <A HREF="https://youtu.be/m0rqccviLNM">Get Meaningful Insights with Google BigQuery</A>.

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hands-on lab

Blue/Green Deployment Pattern with AWS Elastic Beanstalk

AWS Elastic Beanstalk provides a quick and easy way to deploy your web applications to the AWS cloud without requiring knowledge of the individual pieces that make up the infrastructure. This lab demonstrates the common steps of developing a web application and deploying it to production on AWS, using the EB command line interface. In this lab you will learn how to deploy a simple web application continuously using the Elastic Beanstalk Command Line Interface (EB CLI) in two ways, Rolling Deployment and Blue/Green Deployment. The lab also demonstrates many interesting command line tools to interact with, monitor, scale, and ssh into your running Elastic Beanstalk deployment completely from the command line. Prerequisites: for success with this lab, you should be familiar with systems administration of Linux servers, have comfort with Unix/Linux text editors, and should have at least taken the lab "Introduction to AWS Elastic Beanstalk".

hands-on lab

使用 Elastic Load Balancing

本实验室课程介绍了 Elastic Load Balancing (ELB) 的概念。在此实验室课程中,您将使用 ELB 负载均衡一个可用区中的一组 Web 服务器。您将启动一对 Amazon EC2 实例,引导它们安装 Web 服务器和内容,然后使用 Amazon EC2 DNS 记录独立访问实例。接下来,您将设置 ELB、将您的实例添加到 ELB 中,然后访问 ELB DNS 记录以观察您的请求在服务器之间的负载均衡情况。最后,您将在 CloudWatch 中看到 ELB 指标。

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hands-on lab

Introduction to Amazon EC2 Auto Scaling

This lab provides the basic hands-on experience of Amazon EC2 Auto Scaling -- setting up Auto Scaling to automatically launch compute instances in response to conditions that you specify. You will use Auto Scaling via the AWS console to create the basic infrastructure of a Launch Configuration and an Auto Scaling group. You will test the configuration by terminating a running instance and viewing the results as Auto Scaling responds by scaling up and starting another instance. <br><br> For the lab to function as written, please DO NOT change the auto assigned region.

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hands-on lab

Entity and Sentiment Analysis with the Natural Language API

The Cloud Natural Language API lets you extract entities, and perform sentiment and syntactic analysis on a block of text. In this hands-on lab you’ll learn how to extract entities and sentiment from text using the Cloud Natural Language API.

hands-on lab

Working with Alexa: Build a Fact Skill

In this lab, you will build a Fact Skill in the Amazon Developer Portal, then build a Lambda function to handle notifications from Alexa. You will use a sample Fact skill for this lab, which you can use as a template for your own Skill after completing the lab. You will use both the AWS Console and the Amazon Developer Portal in this lab. You do not need an Alexa device. Prerequisites: To successfully complete this lab, you should be familiar with AWS Lambda through taking the introductory lab. Familiarity with Node.js programming will be helpful, although full solution code is provided. You will need to have/create a no-cost, no-credit-card-required account in the Amazon Developer Portal. Familiarity with the Amazon Developer Portal and the Alexa Skills Kit is helpful, though not required. You do not need an Alexa device for this lab.

hands-on lab

Deploy a Ruby on Rails App to App Engine Flexible Environment

In this lab, you will learn how to deploy a new Ruby on Rails application or Rails app for short to Google App Engine Flexible environment. You will learn Cloud Shell and the Cloud SDK to get started without needing any downloads or installs.

hands-on lab

Networking 101

In this lab you will learn how to perform basic networking tasks on Google Cloud Platform by setting up a network and 3 subnetworks; and how GCP might differ from an on-premises setup.

hands-on lab

Container-Optimized OS: Qwik Start

This hands-on lab shows you how to create Compute Engine instances running Container-Optimized OS.

hands-on lab

Managing Deployments Using Kubernetes Engine

Dev Ops best practices make use of multiple deployments to manage application deployment scenarios. This lab provides practice in scaling and managing containers to accomplish common scenarios where multiple heterogeneous deployments are used.

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hands-on lab

Getting Started with Cloud KMS

In this lab you'll work with advanced features of Google Cloud Security and Privacy APIs, including setting up a secure Cloud Storage bucket, managing keys and encrypted data using Key Management Storage, and viewing Cloud Storage audit logs.

hands-on lab

Introduction to Amazon Route 53

The lab provides a basic understanding of Amazon Route 53. It will demonstrate the basic steps required to get started with Route 53, including creating, editing, and deleting simple DNS records within a Hosted Zone (HZ), and creating and testing simple health check and associated failover records. Prerequisites for this lab: basic understanding of IP networking, DNS addressing and host name resolution. Students should also have taken the following three labs at a minimum prior to taking this lab: 1) Introduction to Amazon Elastic Compute Cloud (EC2), 2) Introduction to Simple Storage Service (s3), and 3) Introduction to Amazon Virtual Private Cloud (VPC).For the lab to function as written, please DO NOT change the auto assigned region.

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hands-on lab

结合使用 Windows Server Storage Spaces 和 Amazon EBS

本实验室将逐步指导您如何使用 Amazon 系统映像 (AMI) 启动 Amazon Elastic Compute Cloud (EC2) 实例、向该实例添加多个磁盘以及构建具有 SSD 和磁性介质卷的分层存储池。您还将使用该存储池创建虚拟磁盘,并在已挂载的卷上执行基本的 IOPS 测试操作。在本实验室结束时,您将了解如何结合使用 Amazon EBS 和 Windows Storage Spaces 构建具有多个存储层的虚拟磁盘池,以及如何通过 iSCSI 从其他机器连接至 Storage Spaces。

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hands-on lab

使用S3服务于开放数据

本实验展示如何上传文件到S3,并让文件跨越通过web浏览器来访问。你将学到如何创建亚马逊S3存储桶,配置它来提供web站点服务,使用JavaScript代码来展示这些对象。同时,你将了解到创建开放数据的最佳实践。在实验的最后,你将部署一个简单的web 站点,让数据跨越被访问,和提供数据的基本文档。

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hands-on lab

Building Search into your Applications with Amazon CloudSearch

This lab will demonstrate the basics of search engines and Amazon CloudSerach. It will cover how to create a search domain, how to configure it, how to upload data, how to build queries, and how to tune your ranking. You will explore the features of the AWS Management Console and learn how easy it is to get started with Amazon CloudSearch.

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hands-on lab

Running Distributed TensorFlow on Compute Engine

This lab shows you how to use a distributed configuration of TensorFlow on multiple Compute Engine instances to train a convolutional neural network model using the MNIST dataset.

hands-on lab

Deploy a Java EE Application on AWS Elastic Beanstalk Using Docker Containers

This lab demonstrates how to install a Java EE application into JBoss Wildfly, running in a custom Docker Container and then deploy your container to AWS Elastic Beanstalk.

hands-on lab

Provision Services with Cloud Launcher

In this hands-on lab you'll learn how to use Cloud Launcher to quickly get started with common operating systems, web frameworks, and databases.

hands-on lab

Automated Video Editing with YOU as the Star!

Learn how to auto-detect faces with Amazon Rekognition and automatically create a new video with Amazon Elastic Transcoder.

hands-on lab

Running a Node.js Container in Kubernetes with Container Engine

Containers are becoming a popular way to run and scale applications across multiple cloud providers or on both cloud and on premise hardware. This lab provides a quick introduction to running a website on Google Container Engine using Docker.

hands-on lab

Introduction to Amazon DynamoDB

This lab teaches you about Amazon DynamoDB and walks you through how to create, query, view and delete a table in the AWS Management Console. For a demonstration, go to: https://www.youtube.com/watch?v=ujWV3-m1pLo For the lab to function as written, please DO NOT change the auto assigned region.

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hands-on lab

Using OpenTSDB to Monitor Time-Series Data on Cloud Platform

In this lab you will learn how to collect, record, and monitor time-series data on Google Cloud Platform (GCP) using OpenTSDB running on Google Kubernetes Engine and Google Cloud Bigtable.

hands-on lab

Deployment Manager - Package and Deploy

In this lab you will develop an advanced Deployment Manager template using JINJA and YAML. You will learn how to install and run a Python application on an instance through Deployment Manager.

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hands-on lab

Amazon Elastic Load Balancer (Amazon ELB) 简介

本指南旨在向您介绍如何使用 AWS 管理控制台操作 Amazon Elastic Load Balancer。

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