The course in detail

Module 1: Good practice in application development

• Manage code and development environments.
• Develop and design secure, scalable and reliable microservices and applications,
• Integrate and deploy continuously.
• Rethink application architecture for the cloud.

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

• Install and use Google Cloud client libraries, Google Cloud SDK and Google Firebase SDK.
• Lab: Install Google Cloud, Google Cloud SDK, and Firebase SDK client libraries on a Linux installation and set up application credentials.

Module 3: Overview of data storage options

• Gain an overview of application data storage options.
• Discover 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

• Establish best practices for: queries, integrated or composite indexes, batch data insertion or deletion, error handling, transactions, and loading raw data into Cloud Datastore using Google Cloud Dataflow.
• Lab: Store application data in Cloud Datastore.

Module 5: Performing operations on objects or buckets

• Learn about operations that can be performed on objects and buckets.
• Discover the coherence model.
  Manage error.

Module 6: Best practices for using Google Cloud Storage

• Name buckets for static websites in particular.
• Name objects (from an access and distribution perspective).
• Explore performance considerations.
• Install and debug a CORS configuration on a bucket.
• Lab: Storing files on Cloud Storage.

Module 7: Authorisation and authentication management

• Learn more about roles on Cloud Identity and Access Management (IAM), and service accounts.
• Explore user authentication using Firebase authentication.
• Explore user authentication using Cloud Identity-Aware proxies.
• Workshop user authentication using Firebase authentication.

Module 8: Using Google Cloud Pub/Sub to integrate application components

• Explore topics, publications and subscriptions.
• Learn about pull and push subscriptions.
• Explore use cases for Cloud Pub/Sub.
• Lab: Develop a backend service for processing messages in a queue.

Module 9: Add intelligence to an application

• Gain an overview of pre-trained machine learning APIs such as Cloud Vision and the Cloud Natural Language API.

Module 10: Use Cloud Functions for event-driven processing

• Explore key concepts such as triggers, background functions and HTTP functions.
• Examine use cases.
• Explore development and deployment of functions.
  Manage errors and follow up.

Module 11: API management with Google Cloud Endpoints

• Learn more about OpenAPI deployment configuration.
• Lab: Deploy an API for your application.

Module 12: Deploy an application with Google Cloud Build, Google Cloud Container Registry and Google Cloud Deployment Manager

• Create and store container images.
• Consider repeated deployments with configuration and deployment templates.
• Lab: Use Cloud Deployment Manager to deploy a web application to flexible test and production environments on the App Engine.

Module 13: Runtime environments for your application

• Choose the runtime environments for your application or service: Google Compute Engine, Kubernetes Engine, App Engine (flexible environment), Cloud Functions or Cloud Dataflow.
• Lab: Deploy an application on the flexible App Engine environment.

Module 14: Debug, manage and improve performance with Google

• Stackdriver.
• Learn about Stackdriver (Debugger/Logging) and Stackdriver error reports.
  Lab: Debug an application with Stackdriver and error reports.
• Explore key concepts related to Stackdriver Trace and Stackdriver Monitoring.
• Lab: Use Stackdriver Trace and Stackdriver Monitoring to trace a query through different services and optimise performance.