Developing Applications with Google Cloud Platform

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Developing Applications with Google Cloud Platform

註冊課程

Google Cloud Platform上的應用程序開發

課程代碼

GCP-DEVAPP

課程天數

3 天

課程概要

在本課程中，應用程序開發人員將學習如何設計，開發和部署應用程序，無縫接合Google Cloud生態系統的服務和功能。通過課堂解說、演示和動手實作LAB的組合，學員將學習如何使用GCP服務和預先訓練好的機器學習API來構建安全、可彈性擴展和智能的雲端原生應用程序。

學習目標和取得技能

依循最佳實踐(best practices)開發應用程序
為應用程序數據選擇適當的數據存儲方式
實施聯合身份(federated identity)管理
開發鬆散耦合(loosely coupled)的應用程序組件或微服務
整合應用程序組件和數據來源
除錯、追蹤和監視應用程序
使用容器和部署服務達成重複部署。
選擇適當的應用程序執行(runtime)環境; 使用Google Kubernetes Engine作為運行環境，然後切換至Google App Engine Flex的no-ops解決方案。

教學方式

Google認證講師課堂中文指導

教材與實驗

Google原廠教材與Qwiklabs實驗室

課程適合對象

希望構建雲端原生應用程序；或將現有應用程序重新設計在Google Cloud Platform上運行的的應用程序開發人員

前備知識

已完成Google Cloud Platform Fundamentals課程或具有同等經驗、知識
Node.js的知識
熟悉命令行工具(command-line)和Linux系統操作環境

課程大綱

課程包括課堂講解，演示和學員實作實驗

Module 1: Best Practices for Application Development

主題	實驗
Code and environment management Design and development of secure, scalable, reliable, loosely coupled application components and microservices Continuous integration and delivery Re-architecting applications for the cloud	--

Module 2: Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK

主題	實驗
How to set up and use Google Cloud Client Libraries, Google Cloud SDK, and Google Firebase SDK Lab: Set up Google Client Libraries, Google Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials	Setting up a Development Environment v1.1

Module 3: Overview of Data Storage Options

主題	實驗
Overview of options to store application data Use cases for Google Cloud Storage, Google Cloud Datastore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner	--

Module 4: Best Practices for Using Google Cloud Datastore

主題	實驗
Best practices related to the following: Queries Built-in and composite indexes Inserting and deleting data (batch operations) Transactions Error handling Bulk-loading data into Cloud Datastore by using Google Cloud Dataflow Lab: Store application data in Cloud Datastore	Storing Application Data in Cloud Datastore v1.1

Module 5: Performing Operations on Buckets and Objects

主題	實驗
Operations that can be performed on buckets and objects Consistency model Error handling	--

Module 6: Best Practices for Using Google Cloud Storage

主題	實驗
Naming buckets for static websites and other uses Naming objects (from an access distribution perspective) Performance considerations Setting up and debugging a CORS configuration on a bucket Lab: Store files in Cloud Storage	Storing Image and Video Files in Cloud Storage v1.1

Module 7: Handling Authentication and Authorization

主題	實驗
Cloud Identity and Access Management (IAM) roles and service accounts User authentication by using Firebase Authentication User authentication and authorization by using Cloud Identity-Aware Proxy Lab: Authenticate users by using Firebase Authentication	Adding User Authentication to your Application v1.1

Module 8: Using Google Cloud Pub/Sub to Integrate Components of Your Application

主題	實驗
Topics, publishers, and subscribers Pull and push subscriptions Use cases for Cloud Pub/Sub Lab: Develop a backend service to process messages in a message queue	Develop a backend service to process messages in a message queue

Module 9: Adding Intelligence to Your Application

主題	實驗
Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API	--

Module 10: Using Google Cloud Functions for Event-Driven Processing

主題	實驗
Key concepts such as triggers, background functions, HTTP functions Use cases Developing and deploying functions Logging, error reporting, and monitoring	Processing Cloud Pub/Sub Data using Cloud Functions v1.1

Module 11: Managing APIs with Google Cloud Endpoints

主題	實驗
Open API deployment configuration Lab: Deploy an API for your application	Deploying an API for the Quiz Application v1.1

Module 12: Deploying an Application by Using Google Cloud Cloud Build, Google Cloud Container Registry, and Google Cloud Deployment Manager

主題	實驗
Creating and storing container images Repeatable deployments with deployment configuration and templates Lab: Use Deployment Manager to deploy a web application into Google App Engine flexible environment test and production environments	Deploying the Application into Kubernetes Engine v1.1

Module 13: Execution Environments for Your Application

主題	實驗
Considerations for choosing an execution environment for your application or service: Google Compute Engine Kubernetes Engine App Engine flexible environment Cloud Functions Cloud Dataflow Lab: Deploying your application on App Engine flexible environment	Deploying the Application into App Engine Flexible Environment v1.1

Module 14: Debugging, Monitoring, and Tuning Performance by Using Google Stackdriver

主題	實驗
Stackdriver Debugger Stackdriver Error Reporting Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting Stackdriver Logging Key concepts related to Stackdriver Trace and Stackdriver Monitoring. Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance	Debugging Application Errors v1.1 Harnessing Stackdriver Trace and Monitoring v1.1

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