book

Google Cloud Cookbook

by Rui Santos Costa, Drew Hodun

October 2021

Beginner

282 pages

5h 38m

English

O'Reilly Media, Inc.

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Preface
Who Should Read This BookWhy I Wrote This BookNavigating This BookConventions Used in This BookUsing Code ExamplesO’Reilly Online LearningHow to Contact UsAcknowledgments
1. Introduction
2. Cloud Functions
2.1. Creating a Public HTTP Google Cloud Function2.2. Authenticating an HTTP Google Cloud Function2.3. Accessing Environment Variables at Runtime2.4. Sending Emails from Cloud Functions with SendGrid2.5. Deploying Cloud Functions with a GitLab CI/CD Pipeline2.6. Responding to SMS Messages with Twilio and Cloud Functions2.7. Unit Testing with GitLab and Cloud Functions2.8. Building an API Gateway to Gather Telemetry Data
3. Google Cloud Run
3.1. Deploying a Prebuilt Hello World Container3.2. Building Your Own Hello World Container3.3. Using Cloud Run with a Custom Domain3.4. Triggering a Cloud Run from Cloud Pub/Sub3.5. Deploying a Web Application to Cloud Run3.6. Rolling Back a Cloud Run Service Deployment3.7. Deploying Cloud Run Services in a Gradual Rollout3.8. Cloud Run Configuration Parameters
4. Google App Engine
4.1. Deploying a Hello World to App Engine (Standard)4.2. Deploying a Hello World to App Engine (Flexible)4.3. Securing Your Application with Identity-Aware Proxy4.4. Mapping Custom Domains with App Engine4.5. Using the Google Cloud Translation Machine Learning APIs with App Engine4.6. Building User Interfaces for Viewing Charts and Graphs4.7. Debugging an Instance4.8. Using CI/CD
5. Google Cloud Compute Engine
5.1. Creating a Windows Virtual Machine5.2. Creating a Linux Virtual Machine and Installing NGINX5.3. Connecting to Your Windows Virtual Machines with Identity-Aware Proxy TCP Forwarding5.4. Securing Your Virtual Machine Logins with Two-Step Verification5.5. Running Startup Scripts5.6. Creating a Group of NGINX Web Servers with a Managed Instance Group5.7. Deploying Containers to Managed Instance Groups5.8. Transferring Files to Your Virtual Machine5.9. Using VM Manager for Patch Management5.10. Backing Up Your Virtual Machine
6. Google Cloud Kubernetes Engine
6.1. Creating a Zonal Cluster6.2. Creating a Regional Cluster6.3. Resizing a Cluster6.4. Automatically Routing Traffic to the Nearest Cluster with Multi-Cluster Ingress6.5. Deploying a Spring Boot Java Application6.6. Deploying a Java Application to Kubernetes, Using Skaffold6.7. Using GKE Autopilot for Running an Application You Don’t Have to Manage
7. Working with Data
7.1. Speeding Up Cloud Storage Bulk Transfers by Multiprocessing7.2. Speeding Up GCS Transfers for Large Files with Parallel Composite Uploads7.3. Mounting GCS as a Filesystem7.4. Automatically Archiving and Deleting GCS Objects7.5. Creating and Restoring from Persistent Disk Snapshots in GCE7.6. Using Interleaved Tables in Your Cloud Spanner Database7.7. Locking Down Firestore Database So a User Can Edit Only Their Data
8. BigQuery and Data Warehousing
8.1. Using Cloud Console to Run a BigQuery Query8.2. Loading Data to BigQuery from CSV8.3. Building a Pivot Table in BigQuery8.4. Adding Partitioned and Clustered Columns to an Existing Table8.5. Adding Clustering to a Table That Can’t or Shouldn’t Be Partitioned8.6. Selecting the Top-1 Result8.7. Merging Tables in BigQuery Without Duplicates8.8. Deduplicating Rows in BigQuery with Timestamps8.9. Undeleting a Table in BigQuery8.10. Streaming JSON or Avro Data into BigQuery with a Dataflow Template
9. Data Processing Tools
9.1. Cleaning Data Using the Data Fusion GUI9.2. Running a Simple Python Dataflow Pipeline9.3. Building a Streaming Pipeline in Dataflow SQL9.4. Querying BigQuery from a Dataproc Job9.5. Adding Event Timestamps to Pub/Sub9.6. Inferring and Using Schemas in Dataflow9.7. Mini-batching and Streaming Dataflow Data to BigQuery Using Filters9.8. Triggering a Dataflow Job Automatically from a GCS Upload

10. AI/ML
10.1. Creating a Vertex AI Notebook10.2. Training a Python ML Model Serverlessly10.3. Making Serverless Predictions with a Python Model10.4. Creating a Custom Notebook Environment10.5. Extracting Data from BigQuery to Pandas for Model Training10.6. Training a Model in SQL with BQML
11. Google Cloud Security and Access
11.1. Creating a Service Account11.2. Creating Custom Roles to Access a Cloud Storage Bucket11.3. Authenticating an Application Running on Kubernetes Engine11.4. Retrieving the Authenticated User’s Identity11.5. Authenticating a Java Application Using a Service Account11.6. Building Reports Using the Cloud Asset API11.7. Allowing a List of IP Addresses to Access Your Application
12. Google Cloud Networking
12.1. Creating a Custom Mode VPC Network12.2. Creating a Static External IP Address12.3. Create a Firewall Rule12.4. Serving Content for Users in a Specific Region12.5. Configuring VPC Network Peering12.6. Creating VPN Gateways with Cloud Routers12.7. Deployments of Networks Using Terraform12.8. Limiting Access to Only Authorized Networks with VPC Service Controls
Index

Content preview from Google Cloud Cookbook

Chapter 5. Google Cloud Compute Engine

Google Cloud Compute Engine provides you the ability to run virtual machines on Google’s infrastructure. You can run Windows and Linux virtual machines. You can customize the virtual machine to meet your needs. You can change the virtual machine’s memory allocation, you can change how many virtual CPUs are assigned, and you can even automate patching of the operating system.

This chapter contains recipes for creating and managing your virtual machines. You’ll find recipes on unique methods to automate deployments, deploy containers to virtual machines, and use Identity-Aware Proxy (IAP) to tunnel Remote Desktop Protocol (RDP) traffic to connect to your Windows virtual machines securely.

You will need to make sure you have met the prerequisites before running through the recipes:

Signed up for a Google Cloud account, as described in Chapter 1.
Created a Google Cloud project, as described in Chapter 1.
Installed and configured gcloud, as described in Chapter 1.

5.1 Creating a Windows Virtual Machine

Problem

You have an application that needs to be installed on a Windows server. You also need access to the operating system to change configuration options required by the application.

Solution

Using the Google Cloud Console, create a Windows server on Google Cloud Compute Engine. This will provide you with full access to the operating system to allow you to make any configuration changes required by the application.

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