Developing Applications With Google Cloud Platform

Best Practices for Application DevelopmentCode 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

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

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

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

Performing Operations on Buckets and Objects: Operations that can be performed on buckets and objects - Consistency model - Error handlingLesson 7Best 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

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

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

Adding Intelligence to Your Application: Overview of pre-trained machine learning APIs such as Cloud Vision API and Cloud Natural Language Processing API.

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

Using Cloud Endpoint to Deploy APIs: Open API deployment configuration - Lab Deploy an API for your application

Debugging Your Application by Using Google Stackdriver: Stackdriver Debugger - Stackdriver Error Reporting - Lab Debugging an application error by using Stackdriver Debugger and Error Reporting

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

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 - Deploying your application on App Engine Flex

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