Developing Applications with Google Cloud
Description
Learn how to design, develop, and deploy applications that seamlessly integrate components from the Google Cloud ecosystem. This course uses lectures, demos, and hands-on labs to show you how to use Google Cloud services and pre-trained machine learning APIs to build secure, scalable, and intelligent cloud-native applications.
Intended audience
Application developers who want to build cloud-native applications or redesign existing applications that will run on Google Cloud Platform
Topics
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
Objectives
Activities
Overview of Data Storage Options
• Overview of options to store application data
• Use cases for Cloud Storage, Firestore, Cloud Bigtable, Cloud SQL,
and Cloud Spanner
• Demo: Connecting Securely to a Cloud SQL Database
Objectives
Activities
Best Practices for Using Datastore
• Best practices related to using Firestore in Datastore mode for:
• Queries
• Built-in and composite indexes
• Inserting and deleting data (batch operations)
• Transactions
• Error handling
• Demo: Explore Datastore
• Demo: Use Dataflow to Bulk-load Data into Datastore
• Lab: Storing Application Data in Datastore
Objectives
Activities.
Performing Operations on Buckets and Objects
• Cloud Storage concepts
• Consistency model
• Demo: Explore Cloud Storage
• Request endpoints
• Composite objects and parallel uploads
• Truncated exponential backoff
• Demo: Enable CORS Configuration in Cloud Storage
• Understand Cloud Storage concepts.
• Differentiate between strongly consistent and eventually consistent operations.
• Access Cloud Storage through request endpoints.
• Use object composition to upload an object in parallel.
• Use truncated exponential backoff to deal with network failures.
Objectives
Activities
Best Practices for Using Cloud Storage
• Naming buckets for static websites and other uses
• Naming objects (from an access distribution perspective)
• Performance considerations
• Lab: Storing Image and Video Files in Cloud Storage
Objectives
Activities
Handling Authentication and Authorization
• Identity and Access Management (IAM) roles and service accounts
• User authentication by using Firebase Authentication
• User authentication and authorization by using Identity-Aware Proxy
• Lab: Adding User Authentication to your Application
Objectives
Activities
Using Pub/Sub to Integrate Components of Your Application
• Topics, publishers, and subscribers
• Pull and push subscriptions
• Use cases for Pub/Sub
• Lab: Developing a Backend Service
Objectives
Activities
Adding Intelligence to Your Application
Overview of pre-trained machine learning APIs such as the Vision API and the Cloud
Natural Language Processing API
Objectives
Activities
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
• Demo: Invoke Cloud Functions Through Direct Request-response
• Lab: Processing Pub/Sub Data using Cloud Functions
Objectives
Activities
Managing APIs with Cloud Endpoints
• Open API deployment configuration
• Lab: Deploying an API for the Quiz Application
Objectives
Activities
Deploying Applications
• Creating and storing container images
• Repeatable deployments with deployment configuration and templates
• Demo: Exploring Cloud Build and Cloud Container Registry
• Lab: Deploying the Application into Kubernetes Engine
Objectives
Activities
Compute Options for Your Application
Considerations for choosing a compute option for your application or service:
• Compute Engine
• Google Kubernetes Engine (GKE)
• Cloud Run
• Cloud Functions
• Platform comparisons.
• Comparing App Engine and Cloud Run
Objectives
Activities
Debugging, Monitoring, and Tuning Performance
• Google Cloud’s operations suite
• Managing performance
• Lab: Debugging Application Errors
• Logging
• Monitoring and tuning performance
• Identifying and troubleshooting performance issues
• Lab: Harnessing Cloud Trace and Cloud Monitoring
Objectives
Activities
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