Module 1:​ Best Practices for Application Development

• 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

• How to set up and use Google Cloud Client Libraries, Google CloudSDK, and Google Firebase SDK
• Lab: Set up Google Client Libraries, Cloud SDK, and Firebase SDK on a Linux instance and set up application credentials

Module 3:​ Overview of Data Storage Options

• Overview of options to store application data
• Use cases for Google Cloud Storage, Cloud Firestore, Cloud Bigtable, Google Cloud SQL, and Cloud Spanner

Module 4:​ Best Practices for Using Cloud Firestore

• Best practices related to using Cloud Firestore in Datastore mode for:

○Queries

○Built-in and composite indexes

○Inserting and deleting data (batch operations)

○Transactions

○Error handling

• Bulk-loading data into Cloud Firestore by using Google Cloud Dataflow
• Lab: Store application data in Cloud Datastore

Module 5:​ Performing Operations on Cloud Storage

• Operations that can be performed on buckets and objects
• Consistency model
• Error handling Training and Certification

Module 6:​ Best Practices for Using Cloud Storage

• 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

Module 7:​ Handling Authentication and Authorization

• 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

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

• 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

Module 9:​ Adding Intelligence to Your Application

• Overview of pre-trained machine learning APIs such as Cloud VisionAPI and Cloud Natural Language Processing API.

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

• Key concepts such as triggers, background functions, HTTP functions
• Use cases
• Developing and deploying functions
• Logging, error reporting, and monitoring

Module 11:​ Managing APIs with Cloud Endpoints

• Open API deployment configuration
• Lab: Deploy an API for your application Training and Certification

Module 12:​ Deploying Applications

• 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

Module 13:​ Execution Environments for Your Application

• Considerations for choosing an execution environment for your application or service:

○Google Compute Engine (GCE)

○Google Kubernetes Engine (GKE)

○App Engine flexible environment

○Cloud Functions

○Cloud Dataflow

○Cloud Run

• Lab: Deploying your application on App Engine flexible environment

Module 14:​ Debugging, Monitoring, and Tuning Performance

• Application Performance Management Tools
• 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 are quest across services, observe, and optimize performance