Developing Solutions for Google Cloud Platform

Each participant will leave with a recognised certificate

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 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

Module 3: Overview of Data Storage Options

• 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 Cloud Datastore

• 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

Module 5: Performing Operations on Buckets and Objects

• Operations that can be performed on buckets and objects

• Consistency model

• Error handling

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: Securing Your Application

• 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 Google Cloud 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 Vision API 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: Using Cloud Endpoint to Deploy APIs

• Open API deployment configuration

• Lab: Deploy an API for your application

Module 12: Debugging Your Application by Using Google Stackdriver

• Stackdriver Debugger

• Stackdriver Error Reporting

• Lab: Debugging an application error by using Stackdriver Debugger and Error Reporting

Module 13: Deploying an Application by Using Google Cloud Container Builder, Google Cloud Container Registry, and Google Cloud Deployment Manager

• 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 Flex test and production environments

Module 14: Execution Environments for Your Application

• Considerations for choosing an execution environment for your application or service: Google Compute Engine, Container Engine, App Engine Flex, Cloud Functions, Cloud Dataflow

• Lab: Deploying your application on App Engine Flex

Module 15: Monitoring and Tuning Performance

• Best practices and watchpoints for performance

• Key concepts related to Stackdriver Trace and Stackdriver Monitoring

• Detecting and resolving performance issues

• Lab: Use Stackdriver Monitoring and Stackdriver Trace to trace a request across services, observe, and optimize performance