Google cloud platform for architects : design and manage powerful cloud solutions / Vitthal Srinivasan, Janani Ravi, Judy Raj.

Format:

Book

Author/Creator:

Srinivasan, Vitthal, author.

Ravi, Janani, author.

Raj, Judy, author.

Language:

English

Subjects (All):

Google (Firm).

Architecture--Data processing.

Architecture.

Cloud computing.

Computing platforms.

Physical Description:

1 online resource (355 pages)

Edition:

1st edition

Place of Publication:

Birmingham ; Mumbai : Packt, 2018.

System Details:

text file

Summary:

Get acquainted with GCP and manage robust, highly available, and dynamic solutions to drive business objective About This Book Identify the strengths, weaknesses and ideal use-cases for individual services offered on the Google Cloud Platform Make intelligent choices about which cloud technology works best for your use-case Leverage Google Cloud Platform to analyze and optimize technical and business processes Who This Book Is For If you are a Cloud architect who is responsible to design and manage robust cloud solutions with Google Cloud Platform, then this book is for you. System engineers and Enterprise architects will also find this book useful. A basic understanding of distributed applications would be helpful, although not strictly necessary. Some working experience on other public cloud platforms would help too. What You Will Learn Set up GCP account and utilize GCP services using the cloud shell, web console, and client APIs Harness the power of App Engine, Compute Engine, Containers on the Kubernetes Engine, and Cloud Functions Pick the right managed service for your data needs, choosing intelligently between Datastore, BigTable, and BigQuery Migrate existing Hadoop, Spark, and Pig workloads with minimal disruption to your existing data infrastructure, by using Dataproc intelligently Derive insights about the health, performance, and availability of cloud-powered applications with the help of monitoring, logging, and diagnostic tools in Stackdriver In Detail Using a public cloud platform was considered risky a decade ago, and unconventional even just a few years ago. Today, however, use of the public cloud is completely mainstream - the norm, rather than the exception. Several leading technology firms, including Google, have built sophisticated cloud platforms, and are locked in a fierce competition for market share. The main goal of this book is to enable you to get the best out of the GCP, and to use it with confidence and competence. You will learn why cloud architectures take the forms that they do, and this will help you become a skilled high-level cloud architect. You will also learn how individual cloud services are configured and used, so that you are never intimidated at having to build it yourself. You will also learn the right way and the right situation in which to use the important GCP services. By the end of this book, you will be able to make the most out of Google Cloud Platform design. Style and approach A clear, conc...

Contents:

Cover

Title Page

Copyright and Credits

Packt Upsell

Contributors

Table of Contents

Preface

Chapter 1: The Case for Cloud Computing

Genesis

Why Google Cloud Platform (GCP)?

Autoscaling and autohealing

Capital expenditure (CAPEX) versus operating expenses (OPEX)

Career implications

Summary

Chapter 2: Introduction to Google Cloud Platform

Global, regional, and zonal resources

Accessing the Google Cloud Platform

Projects and billing

Setting up a GCP account

Using the Cloud Shell

Chapter 3: Compute Choices - VMs and the Google Compute Engine

Google Compute Engine - GCE

Creating VMs

Creating a VM instance using the web console

Creating a VM instance using the command line

VM customization options

Operating system

Compute zone

Machine type

Networks - aka VPCs

Storage options

Persistent disks and local SSDs - block storage for GCE

Understanding persistent disks and local SSDs

Creating and attaching a persistent disk

Linux procedure for formatting and mounting a persistent disk

Sharing a persistent disk between multiple instances

Resizing a persistent disk

More on working with GCE VMs

Rightsizing recommendations

Availability policies

Auto-restart

Preemptibillity

Load balancing

Autoscaling and managed instance groups

Billing

Labels and tags

Startup scripts

Snapshots and images

How to snapshot a disk

How to create an image of a disk

Cloud launcher

Deploying LAMP stack using GCE

Modifying GCE VMs

Chapter 4: GKE, App Engine, and Cloud Functions

GKE

Contrasting containers and VMs

What is a container?

Docker containers and Kubernetes - complements, not substitutes

Creating a Kubernetes cluster and deploying a WordPress container

Using the features of GKE.

Storage and persistent disks

Auto scaling

Scaling nodes with the cluster autoscaler

Scaling pods with the horizontal pod autoscaler

Multi-zone clusters

Cloud VPN integration

Rolling updates

The container registry

Federated clusters

Google App Engine - flexible

Hosted Docker containers with App Engine Flex

Running a simple Python application with App Engine Flex

Cron Jobs with App Engine Flex

Advantages of GKE over Docker on VMs or App Engine Flex

Google App Engine - standard

Hosted web apps with App Engine Standard

Typical App Engine architecture

Deploying and running on App Engine Standard

Traffic splitting

Serverless compute with cloud functions

Cloud Functions triggered by HTTP

Cloud Functions triggered by Pub/Sub

Cloud functions triggered by GCS object notifications

Chapter 5: Google Cloud Storage - Fishing in a Bucket

Knowing when (and when not) to use GCS

Serving Static Content with GCS Buckets

Storage classes-Regional, multi-regional, nearline, and coldline

Working with GCS buckets

Creating buckets

Creating buckets using the web console

Creating buckets using gsutil

Changing the storage class of bucket and objects

Transferring data in and out of buckets

Uploading data to buckets using the web console

Uploading data to buckets using gsutil

Copying data between buckets using the web console

Copying data between buckets using the gsutil command line

Using the Transfer Service (instead of gsutil or the web console)

Transfer Service or gsutil?

Use case - Object Versioning

Object versioning in the Cloud Storage bucket

Use case - object life cycle policies

Managing bucket life cycle using the web console

Manipulating object life-cycle via JSON file.

Deleting objects permanently using the web console

Deleting objects permanently using gsutil

Use case - restricting access with both ACLs and IAM

Managing permissions in bucket using the GCP console

Use case - signed and timed URLs

Setting up signed URLs for cloud storage

Use case - reacting to object changes

Setting up object change notifications with the gsutil notification watchbucket

Use case - using customer supplied encryption keys

Use case - auto-syncing folders

Use case - mounting GCS using gcsfuse

Mounting GCS buckets

Use case - offline ingestion options

Chapter 6: Relational Databases

Relational databases, SQL, and schemas

OLTP and the ACID properties

Scaling up versus scaling out

GCP Cloud SQL

Creating a Cloud SQL instance

Creating a database in a Cloud SQL instance

Importing a database

Testing Cloud SQL instances

Use case - managing replicas

Use case - managing certificates

Use case - operating Cloud SQL through VM instances

Automatic backup and restore

Cloud Spanner

Creating a Cloud Spanner instance

Creating a database in Cloud Spanner instances

Querying a database in a Cloud Spanner instance

Interleaving tables in Cloud Spanner

Chapter 7: NoSQL Databases

NoSQL databases

Cloud Bigtable

Fundamental properties of Bigtable

Columnar datastore

Denormalization

Support for ACID properties

Working with Bigtable

When to use Bigtable

Solving hot-spotting

Choosing storage for Bigtable

Solving performance issues

Ideal row key choices

Performing operations on Bigtable

Creating and operating an HBase table using Cloud Bigtable

Exporting/Importing a table from Cloud Bigtable

Scaling GCP Cloud BigTable

The Google Cloud Datastore

Comparison with traditional databases.

Working with Datastore

When to use Datastore

Full indexing and perfect index

Using Datastore

Chapter 8: BigQuery

Underlying data representation of BigQuery

BigQuery public datasets

Legacy versus standard SQL

Working with the BigQuery console

Loading data into a table using BigQuery

Deleting datasets

Working with BigQuery using CLI

BigQuery pricing

Analyzing financial time series with BigQuery

Chapter 9: Identity and Access Management

Resource hierarchy of GCP

Permissions and roles

Units of identity in GCP

Creating a Service Account

Working with cloud IAM - grant a role

Working with IAM - creating a custom role

Chapter 10: Managing Hadoop with Dataproc

Hadoop and Spark

Hadoop on the cloud

Google Cloud Dataproc

Compute options for Dataproc

Working with Dataproc

Chapter 11: Load Balancing

Why load balancers matter now

Taxonomy of GCP load balancers

HTTP(S) load balancing

Configuring HTTP(S) load balancing

Configuring Internal Load Balancing

Other load balancing

Chapter 12: Networking in GCP

Why GCP's networking model is unique

VPC networks and subnets

The default VPC

Internal and external IP addresses

VPN and cloud router

Working with VPCs

Working with custom subnets

Working with firewall rules

Chapter 13: Logging and Monitoring

Logging

Working with logs

More Stackdriver - creating log-based metrics

Monitoring

Chapter 14: Infrastructure Automation

Managed Instance Groups

Cloud deployment manager

Chapter 15: Security on the GCP

Security features at Google and on the GCP

Google-provided tools and options for security

Some security best practices

BeyondCorp - Identity-Aware Proxy

Summary.

Chapter 16: Pricing Considerations

Compute Engine

BigTable

BigQuery

Datastore

Cloud SQL

Google Kubernetes Engine

Pub/Sub

Cloud ML Engine

Stackdriver

Video Intelligence API

Key Management Service - KMS

Vision API

Chapter 17: Effective Use of the GCP

Eat the Kubernetes frog

Careful that you don't get nickel-and-dimed

Pay for what you allocate not what you use

Make friends with the gsuite admins

Try to find reasons to use network peering

Understand how sustained use discounts work

Read the fine print on GCS pricing

Use BigQuery unless you have a specific reason not to

Use pre-emptible instances in your Dataproc clusters

Keep your Dataproc clusters stateless

Understand the unified architecture for batch and stream

Understand the main choices for ML applications

Understand the differences between snapshots and images

Don't be Milton!

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Index.

Notes:

Description based on print version record.

ISBN:

9781788833073

1788833074

OCLC:

1043654239