Google Cloud Certified: Professional Cloud Developer認證考試原廠學習課程
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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