Scaling Google Cloud Platform

Managing Real-world Production-grade Challenges at Scale KEY FEATURES ● Built for GCP professionals and Cloud enthusiasts with cloud-agnostic tactics. ● Exhaustive coverage of automatic, manual, and predictive scaling and specialized strategies. ● Every concept is pragmatized with real-time production scenarios derived from prominent technologists. DESCRIPTION ‘Scaling Google Cloud Platform’ equips developers with the know-how to get the most out of its services in storage, serverless computing, networking, infrastructure monitoring, and other IT tasks. This book explains the fundamentals of cloud scaling, including Cloud Elasticity, creating cloud workloads, and selecting the appropriate cloud scaling key performance indicators (KPIs). The book explains the sections of GCP resources that can be scaled, as well as their architecture and internals, and best practices for using these components in an operational setting in detail. The book also discusses scaling techniques such as predictive scaling, auto-scaling, and manual scaling. This book includes real-world examples illustrating how to scale many Google Cloud services, including the compute engine, GKE, VMWare Engine, Cloud Function, Cloud Run, App Engine, BigTable, Spanner, Composer, Dataproc, and Dataflow. At the end of the book, the author delves into the two most common architectures—Microservices and Bigdata to examine how you can perform reliability engineering for them on GCP. WHAT YOU WILL LEARN ● Learn workload migration strategy and execution, both within and between clouds. ● Explore methods of increasing Google Cloud capacity for running VMware Engine and containerized applications. ● Scaling up and down methods include manual, predictive, and automatic approaches. ● Increase the capacity of your Dataproc cluster to handle your big data computing needs. ● Learn Google Dataflow's scalability considerations for large-scale installations. ● Explore Google Composer 2 and scale up your Cloud Spanner instances. ● Learn to set up Cloud functions and Cloud run. ● Discuss general SRE procedures on microservices and big data. WHO THIS BOOK IS FOR This book is designed for Cloud professionals, software developers, architects, DevOps team, and engineering managers to explain scaling strategies for GCP services and assumes readers know GCP basics. TABLE OF CONTENTS 1. Basics of Scaling Cloud Resources 2. KPI for Cloud Scalability 3. Cloud Elasticity 4. Challenges of Infrastructure Complexity and the Way Forward 5. Scaling Compute Engine 6. Scaling Kubernetes Engine 7. Scaling VMware Engine 8. Scaling App Engine 9. Scaling Google Cloud Function and Cloud Run 10. Configuring Bigtable for Scale 11. Configuring Cloud Spanner for Scale 12. Scaling Google Composer 2 13. Scaling Google Dataproc 14. Scaling Google Dataflow 15. Site Reliability Engineering 16. SRE Use Cases

Summary Google Cloud Platform in Action teaches you to build and launch applications that scale, leveraging the many services on GCP to move faster than ever. You'll learn how to choose exactly the services that best suit your needs, and you'll be able to build applications that run on Google Cloud Platform and start more quickly, suffer fewer disasters, and require less maintenance. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Thousands of developers worldwide trust Google Cloud Platform, and for good reason. With GCP, you can host your applications on the same infrastructure that powers Search, Maps, and the other Google tools you use daily. You get rock-solid reliability, an incredible array of prebuilt services, and a cost-effective, pay-only-for-what-you-use model. This book gets you started. About the Book Google Cloud Platform in Action teaches you how to deploy scalable cloud applications on GCP. Author and Google software engineer JJ Geewax is your guide as you try everything from hosting a simple WordPress web app to commanding cloud-based AI services for computer vision and natural language processing. Along the way, you'll discover how to maximize cloud-based data storage, roll out serverless applications with Cloud Functions, and manage containers with Kubernetes. Broad, deep, and complete, this authoritative book has everything you need. What's inside The many varieties of cloud storage and computing How to make cost-effective choices Hands-on code examples Cloud-based machine learning About the Reader Written for intermediate developers. No prior cloud or GCP experience required. About the Author JJ Geewax is a software engineer at Google, focusing on Google Cloud Platform and API design. Table of Contents PART 1 - GETTING STARTED What is "cloud"? Trying it out: deploying WordPress on Google Cloud The cloud data center PART 2 - STORAGE Cloud SQL: managed relational storage Cloud Datastore: document storage Cloud Spanner: large-scale SQL Cloud Bigtable: large-scale structured data Cloud Storage: object storage PART 3 - COMPUTING Compute Engine: virtual machines Kubernetes Engine: managed Kubernetes clusters App Engine: fully managed applications Cloud Functions: serverless applications Cloud DNS: managed DNS hosting PART 4 - MACHINE LEARNING Cloud Vision: image recognition Cloud Natural Language: text analysis Cloud Speech: audio-to-text conversion Cloud Translation: multilanguage machine translation Cloud Machine Learning Engine: managed machine learning PART 5 - DATA PROCESSING AND ANALYTICS BigQuery: highly scalable data warehouse Cloud Dataflow: large-scale data processing Cloud Pub/Sub: managed event publishing

Learn fundamental to advanced GCP architectural techniques using 30 + real-world use cases. The 'Google Cloud Platform an Architect's Guide' is a comprehensive handbook that covers everything that you need to know from GCP fundamentals to advanced cloud architecture topics. The book covers what you need to understand to pass the Google certification exams but goes far further and deeper as it explores real-world use cases and business scenarios. But you don't need to be an IT expert as the book is designed to cater for both beginners and those experienced in other cloud or on other on-premises networks. To that end, the book is split into distinct parts that caters for all levels of expertise. Part -1 is aimed at the novice someone new to a cloud architecture environment that needs to become familiar with the fundamentals of cloud architecture and industry best practices so the more experienced reader may wish to skip this section. Part-2 takes a far deeper dive into GCP theory and practice as well as providing real-world use cases and practical tips that are beneficial for architects at all levels. Part-3 delves much deeper into GCP practical theory on elasticity, scalability and resilience. It also covers Kubernetes in greater detail and touches on High-Performance Computing and IoT designs. The book closes with a final part dealing with cloud-native design practices and as such it covers design, monitoring, notification and remediation techniques to ensure best practice in cloud-native application design, deployment, stabilisation and commissioning.

Develop, deploy, and scale your applications with Google Cloud Platform Key Features Create and deploy your applications on Google Cloud Platform Store and manage source code and debug Cloud-hosted apps with plugins and IDEs Streamline developer workflows with tools for alerting and managing deployments Book Description Google Cloud Platform (GCP) provides autoscaling compute power and distributed in-memory cache, task queues, and datastores to write, build, and deploy Cloud-hosted applications. With Google Cloud Platform for Developers, you will be able to develop and deploy scalable applications from scratch and make them globally available in almost any language. This book will guide you in designing, deploying, and managing applications running on Google Cloud. You’ll start with App Engine and move on to work with Container Engine, compute engine, and cloud functions. You’ll learn how to integrate your new applications with the various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. This book will teach you how to streamline your workflow with tools such as Source Repositories, Container Builder, and StackDriver. Along the way, you’ll see how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerting for your production systems. By the end of this book, you’ll be well-versed with all the development tools of Google Cloud Platform, and you’ll develop, deploy, and manage highly scalable and reliable applications. What you will learn Understand the various service offerings on GCP Deploy and run services on managed platforms such as App Engine and Container Engine Securely maintain application states with Cloud Storage, Datastore, and Bigtable Leverage StackDriver monitoring and debugging to minimize downtime and mitigate issues without impacting users Design and implement complex software solutions utilizing Google Cloud Integrate with best-in-class big data solutions such as Bigquery, Dataflow, and Pub/Sub Who this book is for Google Cloud Platform for Developers is for application developers. This book will enable you to fully leverage the power of Google Cloud Platform to build resilient and intelligent software solutions.

Develop, deploy, and scale your applications with Google Cloud Platform Key Features Create and deploy your applications on Google Cloud Platform Store and manage source code and debug Cloud-hosted apps with plugins and IDEs Streamline developer workflows with tools for alerting and managing deployments Book Description Google Cloud Platform (GCP) provides autoscaling compute power and distributed in-memory cache, task queues, and datastores to write, build, and deploy Cloud-hosted applications. With Google Cloud Platform for Developers, you will be able to develop and deploy scalable applications from scratch and make them globally available in almost any language. This book will guide you in designing, deploying, and managing applications running on Google Cloud. You’ll start with App Engine and move on to work with Container Engine, compute engine, and cloud functions. You’ll learn how to integrate your new applications with the various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. This book will teach you how to streamline your workflow with tools such as Source Repositories, Container Builder, and StackDriver. Along the way, you’ll see how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerting for your production systems. By the end of this book, you’ll be well-versed with all the development tools of Google Cloud Platform, and you’ll develop, deploy, and manage highly scalable and reliable applications. What you will learn Understand the various service offerings on GCP Deploy and run services on managed platforms such as App Engine and Container Engine Securely maintain application states with Cloud Storage, Datastore, and Bigtable Leverage StackDriver monitoring and debugging to minimize downtime and mitigate issues without impacting users Design and implement complex software solutions utilizing Google Cloud Integrate with best-in-class big data solutions such as Bigquery, Dataflow, and Pub/Sub Who this book is for Google Cloud Platform for Developers is for application developers. This book will enable you to fully leverage the power of Google Cloud Platform to build resilient and intelligent software solutions.

Managing Real-world Production-grade Challenges at Scale KEY FEATURES ● Built for GCP professionals and Cloud enthusiasts with cloud-agnostic tactics. ● Exhaustive coverage of automatic, manual, and predictive scaling and specialized strategies. ● Every concept is pragmatized with real-time production scenarios derived from prominent technologists. DESCRIPTION ‘Scaling Google Cloud Platform’ equips developers with the know-how to get the most out of its services in storage, serverless computing, networking, infrastructure monitoring, and other IT tasks. This book explains the fundamentals of cloud scaling, including Cloud Elasticity, creating cloud workloads, and selecting the appropriate cloud scaling key performance indicators (KPIs). The book explains the sections of GCP resources that can be scaled, as well as their architecture and internals, and best practices for using these components in an operational setting in detail. The book also discusses scaling techniques such as predictive scaling, auto-scaling, and manual scaling. This book includes real-world examples illustrating how to scale many Google Cloud services, including the compute engine, GKE, VMWare Engine, Cloud Function, Cloud Run, App Engine, BigTable, Spanner, Composer, Dataproc, and Dataflow. At the end of the book, the author delves into the two most common architectures—Microservices and Bigdata to examine how you can perform reliability engineering for them on GCP. WHAT YOU WILL LEARN ● Learn workload migration strategy and execution, both within and between clouds. ● Explore methods of increasing Google Cloud capacity for running VMware Engine and containerized applications. ● Scaling up and down methods include manual, predictive, and automatic approaches. ● Increase the capacity of your Dataproc cluster to handle your big data computing needs. ● Learn Google Dataflow's scalability considerations for large-scale installations. ● Explore Google Composer 2 and scale up your Cloud Spanner instances. ● Learn to set up Cloud functions and Cloud run. ● Discuss general SRE procedures on microservices and big data. WHO THIS BOOK IS FOR This book is designed for Cloud professionals, software developers, architects, DevOps team, and engineering managers to explain scaling strategies for GCP services and assumes readers know GCP basics. TABLE OF CONTENTS 1. Basics of Scaling Cloud Resources 2. KPI for Cloud Scalability 3. Cloud Elasticity 4. Challenges of Infrastructure Complexity and the Way Forward 5. Scaling Compute Engine 6. Scaling Kubernetes Engine 7. Scaling VMware Engine 8. Scaling App Engine 9. Scaling Google Cloud Function and Cloud Run 10. Configuring Bigtable for Scale 11. Configuring Cloud Spanner for Scale 12. Scaling Google Composer 2 13. Scaling Google Dataproc 14. Scaling Google Dataflow 15. Site Reliability Engineering 16. SRE Use Cases

Explore the Essential Concepts, Tools, and Services in GCP KEY FEATURES ● Build a solid foundation of the Google Cloud Platform. ● Work with different AI and Machine Learning services offered by Google Cloud. ● Learn how to use Google cloud services to build scalable apps. DESCRIPTION Google Cloud platform has a suite of cloud computing services for developing and maintaining software. It includes products like Google Compute Engine, Google App Engine, Google Cloud Storage, and Google Container Engine. With so much to offer, we will learn how to manage services running on Google Cloud. ‘Google Cloud Platform All-In-One Guide’ is primarily for everyone who wants to get familiar with the comprehensive list of services in GCP. You will work with various cloud-based services in computing, storage, database, and networking domains. You will understand how Big Data services can be used for developing end-to-end ETL/ELT pipelines. Lastly, you will explore various APIs available in Google cloud. The book ends with a chapter on best practices that will help you maximize resource utilization and cost optimization. By the end of the book, you will be able to design, develop, and deploy apps in GCP. WHAT YOU WILL LEARN ● Explore and work with security and monitoring services in Google Cloud. ● Learn how to build an ETL Pipeline in the Google Cloud Platform. ● Build and deploy code-based custom models using Vertex AI and Jupyter notebook. ● Learn how to create workflows using GCP services. ● Get an overview of best practices for securely deploying your workloads on Google Cloud. WHO THIS BOOK IS FOR This book is for everyone new to cloud computing or Google cloud. Cloud professionals who are looking to migrate their services to the Google cloud platform will find this book helpful. TABLE OF CONTENTS 1. Cloud Computing Fundamentals 2. Compute in Google Cloud 3. Storage in Google Cloud 4. Database Services in Google Cloud 5. Networking in Google Cloud 6. Security and Monitoring Services in Google Cloud 7. Big Data in Google Cloud 8. AI/ML in Google Cloud 9. Orchestration Services in GCP 10. Migration Services in GCP 11. Best Practices 12. Bonus Chapter 13. Use Cases

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines