Developing Applications with Google Cloud Platform, 3 days

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

Each participant will leave with a recognised certificate

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Great course, practical skills, which is what I needed. The trainer knew their subject inside out. K Morris

Professional and competitively priced. D Harries