Google Cloud Developer

Google Cloud Developer
Schedules

Objectives:

This course teaches participants the following skills:

Use best practices for application development.
Choose the appropriate data storage option for application data.
Implement federated identity management.
Develop loosely coupled application components or microservices.
Integrate application components and data sources.
Debug, trace, and monitor applications.
Perform repeatable deployments with containers and deployment services.
Choose the appropriate application runtime environment; use Google Container Engine as a runtime environment and later switch to a no-ops solution with Google App Engine Flex.

Agenda:

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 Google 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 Google 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 Google 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: Managing APIs with Google Cloud Endpoints

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.