Programming Google Cloud. Building Cloud Native Applications with GCP 197675

Companies looking to move enterprise applications to the cloud are busy weighing several options, such as the use of containers, machine learning, and serverless computing. There's a better way. Instead of helping you fit your use case to individual technologies, this practical guide explains how to use these technologies to fit your use case.

Author a learning consultant with Google, demonstrates this approach by showing you how to run your application on Google Cloud. Each chapter is dedicated to an area of technology that you need to address when planning and deploying your application. This book starts by presenting a detailed fictional use case, followed by chapters that focus on the building blocks necessary to deploy a secure enterprise application successfully.

-Build serverless applications with Google Cloud Functions

-Explore use cases for deploying a real-time messaging service

-Deploy applications to Google Kubernetes Engine (GKE)

-Build multiregional GKE clusters

-Integrate continuous integration and continuous delivery with your application

-Incorporate Google Cloud APIs, including speech-to-text and data loss prevention

-Enrich data with Google Cloud Dataflow

-Secure your application with Google Cloud Identity-Aware Proxy

-Explore BigQuery and visualization with Looker and BigQuery SDKs

Rui Costa has worked at Google in various roles, most recently as a Learning Consultant working with strategic customers and partners to create and execute on their Google Cloud learning plans. He ha served as an AI Coach for the Google AI Impact Challenge and is also the founder of the Speech Analysis Framework, which has successfully graduated to become a Product within Google.

Jasen Baker has over 20+ years of IT experience starting with a job finding "commercial companies" doing business on the Internet in 1993, to founding a web hosting company in 1997. Jasen worked as a Unix engineer for 15 years working for various startups before landing technical roles at Nike, HP and eventually Google. His growing career progressed from the systems administration side, to presales, to training where Jasen enjoys an engaging career teaching the next generation of technologists about the transformation of cloud services and software development. Outside of technical training Jasen enjoys retro gaming, stock trading, and travel.

  Table of contents

 1. Our Use Case and Framework

Fictional Use Case

Business Objectives

The Framework

Storing Audio Recordings

Processing Audio Recordings

Gather Data from the Audio File

Securing the Application

Cloud Native Checkpoint

Abstracted from the Cloud Infrastructure

Continuous Integration and Continuous Delivery

Scalability

Application Reliability

Globally Accessible

Security

Summary

 2. Getting Data into Google Cloud

File Storage

Block Storage

Object-Based Storage

Options for Getting Data to Cloud Storage

Create a Bucket in the Cloud Console

Upload a File in the Cloud Console

Download the file in the Cloud Console

Using the gsutil Tool

Create a Bucket with gsutil

Upload a File with gsutil

Download the File with gsutil

Using Client Libraries

Uploading Audio Files for Our Framework

Cloud Functions

Cloud Function Libraries

GitLab CI/CD and Cloud Functions

Cloud Native Checkpoint

Closing Remarks

 3. Creating a Queue

Message Queues

Message Queuing

Google Cloud Pub/Sub

Receiving Messages with the Push Method

Receiving Messages with the Pull Method

Publishing Messages

Ordering Messages

Replaying and purging messages

Create and Seek to Snapshots

Seek to a timestamp

Monitoring

Pub/Sub or Pub/Sub Lite

Framework Deployment Part One

Configuration and Deployment

Cloud Native Checkpoint

Closing Remarks

 4. Application Data Pipeline with Cloud Dataflow

Cloud Dataflow Overview

Apache Beam Concepts

Pipelines

PCollection

Transforms

ParDo

Pipeline I/O

Aggregation

Runner

Event Time

Windowing

Watermark

Trigger

Closing Remarks

 5. Deploying the Application Data Pipeline

Deploying the Cloud Dataflow Pipeline

Cloud Dataflow Monitoring

Using Cloud Monitoring for Cloud Dataflow pipelines

Cloud Native Checkpoint

Closing Remarks

 About the Authors