Developing Applications with Google Cloud Platform
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
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
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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
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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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