Author: Alasdair Gilchrist
Publisher: BPB Publications
ISBN: 935551123X
Category : Computers
Languages : en
Pages : 431
Get Book Here
Book Description
Step-by-step guide for developing cloud native apps on GCP powered by hands-on interactive learning KEY FEATURES ● Cutting-edge coverage on Google Cloud Build, Cloud Run, GKE, Kubectl and Anthos. ● Includes tutorials and exercises to learn designing, deploying and running cloud native apps. ● Covers Service Mesh, Apps Optimization, logs monitoring and cloud IAM access. DESCRIPTION The book “Cloud Native Apps on Google Cloud Platform” teaches the readers how to design, construct, and maintain successful cloud-native apps using the Google Cloud Platform. With interactive tutorials, the book reinforces learning and helps to develop practical skills for working in an Agile and DevOps context. The book provides a step-by-step approach to building and managing cloud-native applications on Google Cloud Platform for Google Cloud Users, DevOps teams, and Cloud-Native Developers. First, you will investigate the advantages and applicability of each Google Serverless Computing option. You'll learn about Cloud Build and how to use it to prepare code files, create microservices, and build container images. The book walks readers through creating and running Docker image containers on Cloud Run and App Engine. You'll learn how to use kubectl to create and manage Kubernetes clusters, as well as how to configure the autoscaler for increased resilience and availability. You'll build a pipeline that uses Cloud Build to automate CI/CD and Pub/Sub to ingest streaming data. Finally, you'll have the opportunity to learn about Anthos, which enables you to manage massive GKE clusters in both Cloud and on-premises environments. WHAT YOU WILL LEARN ● Distinguish between using containers or microservices for cloud native apps. ● Build a streaming data pipeline using BigQuery and Dataflow using Pub/Sub. ● Practice to deploy and optimize cloud native applications on Kubernetes Engine. ● Build continuous integration/continuous delivery pipelines and improve Kubernetes apps. ● Learn to protect apps running on GCP from cyberattacks. WHO THIS BOOK IS FOR This book is meant for the Cloud and DevOps professionals and for those who wish to learn about Google Cloud services and incorporate them into end-to-end cloud applications. TABLE OF CONTENTS 1. Introducing Cloud Native Apps 2. Developing Cloud Native Apps with Cloud Shell 3. Preparing Source-Code with Cloud Build 4. Create and Deploy Microservices 5. Building and Deploying Containers in Cloud Build 6. Create a Serverless Pipeline with Pub/Sub, Dataflow and BigQuery 7. Container Orchestration with Google Kubernetes Engine 8. Deploying and Managing Kubernetes Applications 9. Optimizing Kubernetes Cluster and Apps in GKE 10. Deploying a CI/CD Pipeline with Kubernetes and Cloud Build 11. Build a Software Delivery Platform with Anthos 12. Application Management with Anthos 13. Securing Cloud Native Apps in Anthos
Author: Alasdair Gilchrist
Publisher: BPB Publications
ISBN: 935551123X
Category : Computers
Languages : en
Pages : 431
Get Book Here
Book Description
Step-by-step guide for developing cloud native apps on GCP powered by hands-on interactive learning KEY FEATURES ● Cutting-edge coverage on Google Cloud Build, Cloud Run, GKE, Kubectl and Anthos. ● Includes tutorials and exercises to learn designing, deploying and running cloud native apps. ● Covers Service Mesh, Apps Optimization, logs monitoring and cloud IAM access. DESCRIPTION The book “Cloud Native Apps on Google Cloud Platform” teaches the readers how to design, construct, and maintain successful cloud-native apps using the Google Cloud Platform. With interactive tutorials, the book reinforces learning and helps to develop practical skills for working in an Agile and DevOps context. The book provides a step-by-step approach to building and managing cloud-native applications on Google Cloud Platform for Google Cloud Users, DevOps teams, and Cloud-Native Developers. First, you will investigate the advantages and applicability of each Google Serverless Computing option. You'll learn about Cloud Build and how to use it to prepare code files, create microservices, and build container images. The book walks readers through creating and running Docker image containers on Cloud Run and App Engine. You'll learn how to use kubectl to create and manage Kubernetes clusters, as well as how to configure the autoscaler for increased resilience and availability. You'll build a pipeline that uses Cloud Build to automate CI/CD and Pub/Sub to ingest streaming data. Finally, you'll have the opportunity to learn about Anthos, which enables you to manage massive GKE clusters in both Cloud and on-premises environments. WHAT YOU WILL LEARN ● Distinguish between using containers or microservices for cloud native apps. ● Build a streaming data pipeline using BigQuery and Dataflow using Pub/Sub. ● Practice to deploy and optimize cloud native applications on Kubernetes Engine. ● Build continuous integration/continuous delivery pipelines and improve Kubernetes apps. ● Learn to protect apps running on GCP from cyberattacks. WHO THIS BOOK IS FOR This book is meant for the Cloud and DevOps professionals and for those who wish to learn about Google Cloud services and incorporate them into end-to-end cloud applications. TABLE OF CONTENTS 1. Introducing Cloud Native Apps 2. Developing Cloud Native Apps with Cloud Shell 3. Preparing Source-Code with Cloud Build 4. Create and Deploy Microservices 5. Building and Deploying Containers in Cloud Build 6. Create a Serverless Pipeline with Pub/Sub, Dataflow and BigQuery 7. Container Orchestration with Google Kubernetes Engine 8. Deploying and Managing Kubernetes Applications 9. Optimizing Kubernetes Cluster and Apps in GKE 10. Deploying a CI/CD Pipeline with Kubernetes and Cloud Build 11. Build a Software Delivery Platform with Anthos 12. Application Management with Anthos 13. Securing Cloud Native Apps in Anthos
Author: Eyal Estrin
Publisher: BPB Publications
ISBN: 9355518900
Category : Computers
Languages : en
Pages : 288
Get Book Here
Book Description
Your practical handbook for securing cloud-native applications KEY FEATURES ● An overview of security in cloud-native applications, such as modern architectures, containers, CI/CD pipeline, and so on. ● Using automation, such as infrastructure as code and policy as code, to achieve security at scale. ● Implementing security, from encryption and secrets management to threat management. DESCRIPTION Security for cloud-native applications is an overview of cloud-native application’s characteristics from a security point of view, filled with best practices for securing services based on AWS, Azure, and GCP infrastructure. This book is a practical guide for securing cloud-native applications throughout their lifecycle. It establishes foundational knowledge of cloud services and cloud-native characteristics. It focuses on securing design approaches like APIs, microservices, and event-driven architectures. Specific technologies like containers, Kubernetes, and serverless functions are covered with security best practices. The book emphasizes integrating security throughout development using CI/CD pipelines and IaC tools. It explores policy as code for enforcing security policies and immutable infrastructure for enhanced security posture. Key management and threat detection strategies are also covered. Finally, the book offers a practical example and resources for further learning. By the end of the book, the reader will be able to design and secure modern applications using the public cloud scale, managed services, automation, and built-in security controls. WHAT YOU WILL LEARN ● How to secure modern design architectures from APIs, event-driven architectures, and microservices. ● How to secure applications using containers and the Kubernetes platform. ● How to secure applications using serverless/function-as-a-service. ● How to implement key and secrets management as part of cloud-native applications. ● How to implement the 12-factor application methodology and immutable infrastructure in cloud-native applications. WHO THIS BOOK IS FOR This book is for security professionals, software development teams, DevOps and cloud architects, and all those who are designing, maintaining, and securing cloud-native applications. TABLE OF CONTENTS 1. Introduction to Cloud Native Applications 2. Securing Modern Design Architectures 3. Containers and Kubernetes for Cloud Native Applications 4. Serverless for Cloud Native Applications 5. Building Secure CI/CD Pipelines 6. The 12-Factor Application Methodology 7. Using Infrastructure as Code 8. Authorization and Policy as Code 9. Implementing Immutable Infrastructure 10. Encryption and Secrets Management 11. Threat Management in Cloud Native Applications 12. Summary and Key Takeaways
Author: Steve (Satish) Sangapu
Publisher: Packt Publishing Ltd
ISBN: 1800209029
Category : Computers
Languages : en
Pages : 488
Get Book Here
Book Description
Get to grips with the tools, services, and functions needed for application migration to help you move from legacy applications to cloud-native on Google Cloud Key FeaturesDiscover how a sample legacy application can be transformed into a cloud-native application on Google CloudLearn where to start and how to apply application modernization techniques and toolingWork with real-world use cases and instructions to modernize an application on Google CloudBook Description Legacy applications, which comprise 75–80% of all enterprise applications, often end up being stuck in data centers. Modernizing these applications to make them cloud-native enables them to scale in a cloud environment without taking months or years to start seeing the benefits. This book will help software developers and solutions architects to modernize their applications on Google Cloud and transform them into cloud-native applications. This book helps you to build on your existing knowledge of enterprise application development and takes you on a journey through the six Rs: rehosting, replatforming, rearchitecting, repurchasing, retiring, and retaining. You'll learn how to modernize a legacy enterprise application on Google Cloud and build on existing assets and skills effectively. Taking an iterative and incremental approach to modernization, the book introduces the main services in Google Cloud in an easy-to-understand way that can be applied immediately to an application. By the end of this Google Cloud book, you'll have learned how to modernize a legacy enterprise application by exploring various interim architectures and tooling to develop a cloud-native microservices-based application. What you will learnDiscover the principles and best practices for building cloud-native applicationsStudy the six Rs of migration strategy and learn when to choose which strategyRehost a legacy enterprise application on Google Compute EngineReplatform an application to use Google Load Balancer and Google Cloud SQLRefactor into a single-page application (SPA) supported by REST servicesReplatform an application to use Google Identity Platform and Firebase AuthenticationRefactor to microservices using the strangler patternAutomate the deployment process using a CI/CD pipeline with Google Cloud BuildWho this book is for This book is for software developers and solutions architects looking to gain experience in modernizing their enterprise applications to run on Google Cloud and transform them into cloud-native applications. Basic knowledge of Java and Spring Boot is necessary. Prior knowledge of Google Cloud is useful but not mandatory.
Author: Adrián González Sánchez
Publisher: "O'Reilly Media, Inc."
ISBN: 1098154959
Category : Computers
Languages : en
Pages : 275
Get Book Here
Book Description
Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies
Author: Shiju Varghese
Publisher: Apress
ISBN: 1484210522
Category : Computers
Languages : en
Pages : 300
Get Book Here
Book Description
Take a deep dive into web development using the Go programming language to build web apps and RESTful services to create reliable and efficient software. Web Development with Go provides Go language fundamentals and then moves on to advanced web development concepts and successful deployment of Go web apps to the cloud. Web Development with Go will teach you how to develop scalable real-world web apps, RESTful services, and backend systems with Go. The book starts off by covering Go programming language fundamentals as a prerequisite for web development. After a thorough understanding of the basics, the book delves into web development using the built-in package, net/http. With each chapter you’ll be introduced to new concepts for gradually building a real-world web system. The book further shows you how to integrate Go with other technologies. For example, it provides an overview of using MongoDB as a means of persistent storage, and provides an end-to-end REST API sample as well. The book then moves on to demonstrate how to deploy web apps to the cloud using the Google Cloud platform. Web Development with Go provides: Fundamentals for building real-world web apps in Go Thorough coverage of prerequisites and practical code examples Demo web apps for attaining a deeper understanding of web development A reference REST API app which can be used to build scalable real-world backend services in Go A thorough demonstration of deploying web apps to the Cloud using the Google Cloud platform Go is a high-performance language while providing greater level of developer productivity, therefore Web Development with Go equips you with the necessary skills and knowledge required for effectively building robust and efficient web apps by leveraging the features of Go.
Author: Murari Ramuka
Publisher: BPB Publications
ISBN: 9389423635
Category : Computers
Languages : en
Pages : 287
Get Book Here
Book Description
Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services DESCRIPTION Modern businesses are awash with data, making data-driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with enough knowledge of Cloud Computing in conjunction with Google Cloud Data platform to succeed in the role of a Cloud data expert. The current market is trending towards the latest cloud technologies, which is the need of the hour. Google being the pioneer, is dominating this space with the right set of cloud services being offered as part of GCP (Google Cloud Platform). At this juncture, this book will be very vital and will cover all the services that are being offered by GCP, putting emphasis on Data services. This book starts with sophisticated knowledge on Cloud Computing. It also explains different types of data services/technology and machine learning algorithm/Pre-Trained API through real-business problems, which are built on the Google Cloud Platform (GCP). With some of the latest business examples and hands-on guide, this book will enable the developers entering the data analytics fields to implement an end-to-end data pipeline, using GCP Data services. Through the course of the book, you will come across multiple industry-wise use cases, like Building Datawarehouse using Big Query, a sample real-time data analytics solution on machine learning and Artificial Intelligence that helped with the business decision, by employing a variety of data science approaches on Google Cloud environment. Whether yourÊbusinessÊis at the early stage of cloud implementation in its journey or well on its way to digital transformation,ÊGoogle Cloud'sÊsolutions and technologies will always help chart a path to success. This book can be used to develop the GCP concepts in an easy way. It contains many examples showcasing the implementation of a GCP service. It enables the learning of the basic and advance concepts of Google Cloud Data Platform. This book is divided into 7 chapters and provides a detailed description of the core concepts of each of the Data services offered by Google Cloud. KEY FEATURES Learn the basic concept of Cloud Computing along with different Cloud service provides with their supported Models (IaaS/PaaS/SaaS) Learn the basics of Compute Engine, App Engine, Container Engine, Project and Billing setup in the Google Cloud Platform Learn how and when to use Cloud DataFlow, Cloud DataProc and Cloud DataPrepÊ Build real-time data pipeline to support real-time analytics using Pub/Sub messaging service Setting up a fully managed GCP Big Data Cluster using Cloud DataProc for runningÊApache SparkÊandÊApache HadoopÊclusters in a simpler, more cost-efficient manner Learn how to use Cloud Data Studio for visualizing the data on top of Big Query Implement and understand real-world business scenarios for Machine Learning, Data Pipeline Engineering WHAT WILL YOU LEARN By the end of the book, you will have come across different data services and platforms offered by Google Cloud, and how those services/features can be enabled to serve business needs. You will also see a few case studies to put your knowledge to practice and solve business problems such as building a real-time streaming pipeline engine, Scalable Data Warehouse on Cloud, fully managed Hadoop cluster on Cloud and enabling TensorFlow/Machine Learning APIÕs to support real-life business problems. Remember to practice additional examples to master these techniques. WHO IS THIS BOOK FOR This book is for professionals as well as graduates who want to build a career in Google Cloud data analytics technologies. While no prior knowledge of Cloud Computing or related technologies is assumed, it will be helpful to have some data background and experience. One stop shop for those who wish to get an initial to advance understanding of the GCP data platform. The target audience will be data engineers/professionals who are new, as well as those who are acquainted with the tools and techniques related to cloud and data space.ÊÊ _Ê Ê Ê Individuals who have basic data understanding (i.e. Data and cloud) and have done some work in the field ofÊ data analytics, can refer/use this book to master their knowledge/understanding. _Ê Ê Ê The highlight of this book is that it will start with theÊ basic cloud computing fundamentals and will move on to cover the advance concepts on GCP cloud data analytics and hence can be referred across multiple different levels of audiences.Ê Table of Contents 1. GCP Overview and Architecture 2. Data Storage in GCPÊ 3. Data Processing in GCP with Pub/Sub and DataflowÊ 4. Data Processing in GCP with DataPrep and Dataflow 5. Big Query and Data Studio 6. Machine Learning with GCP 7. Sample Use cases and Examples
Author: Kasun Indrasiri
Publisher: "O'Reilly Media, Inc."
ISBN: 1492090662
Category : Computers
Languages : en
Pages : 314
Get Book Here
Book Description
With the immense cost savings and scalability the cloud provides, the rationale for building cloud native applications is no longer in question. The real issue is how. With this practical guide, developers will learn about the most commonly used design patterns for building cloud native applications using APIs, data, events, and streams in both greenfield and brownfield development. You'll learn how to incrementally design, develop, and deploy large and effective cloud native applications that you can manage and maintain at scale with minimal cost, time, and effort. Authors Kasun Indrasiri and Sriskandarajah Suhothayan highlight use cases that effectively demonstrate the challenges you might encounter at each step. Learn the fundamentals of cloud native applications Explore key cloud native communication, connectivity, and composition patterns Learn decentralized data management techniques Use event-driven architecture to build distributed and scalable cloud native applications Explore the most commonly used patterns for API management and consumption Examine some of the tools and technologies you'll need for building cloud native systems
Author: Alasdair Gilchrist
Publisher: Alasdair Gilchrist
ISBN:
Category : Computers
Languages : en
Pages : 372
Get Book Here
Book Description
Google Cloud Platform for Data Engineering is designed to take the beginner through a journey to become a competent and certified GCP data engineer. The book, therefore, is split into three parts; the first part covers fundamental concepts of data engineering and data analysis from a platform and technology-neutral perspective. Reading part 1 will bring a beginner up to speed with the generic concepts, terms and technologies we use in data engineering. The second part, which is a high-level but comprehensive introduction to all the concepts, components, tools and services available to us within the Google Cloud Platform. Completing this section will provide the beginner to GCP and data engineering with a solid foundation on the architecture and capabilities of the GCP. Part 3, however, is where we delve into the moderate to advanced techniques that data engineers need to know and be able to carry out. By this time the raw beginner you started the journey at the beginning of part 1 will be a knowledgable albeit inexperienced data engineer. However, by the conclusion of part 3, they will have gained the advanced knowledge of data engineering techniques and practices on the GCP to pass not only the certification exam but also most interviews and practical tests with confidence. In short part 3, will provide the prospective data engineer with detailed knowledge on setting up and configuring DataProc - GCPs version of the Spark/Hadoop ecosystem for big data. They will also learn how to build and test streaming and batch data pipelines using pub/sub/ dataFlow and BigQuery. Furthermore, they will learn how to integrate all the ML and AI Platform components and APIs. They will be accomplished in connecting data analysis and visualisation tools such as Datalab, DataStudio and AI notebooks amongst others. They will also by now know how to build and train a TensorFlow DNN using APIs and Keras and optimise it to run large public data sets. Also, they will know how to provision and use Kubeflow and Kube Pipelines within Google Kubernetes engines to run container workloads as well as how to take advantage of serverless technologies such as Cloud Run and Cloud Functions to build transparent and seamless data processing platforms. The best part of the book though is its compartmental design which means that anyone from a beginner to an intermediate can join the book at whatever point they feel comfortable.
Author: Richard Rose
Publisher: Packt Publishing Ltd
ISBN: 183882684X
Category : Computers
Languages : en
Pages : 308
Get Book Here
Book Description
Effectively deploy fully managed workloads using Google Cloud's serverless services Key FeaturesUse real-world use cases to understand the core functionalities of Functions as a ServiceExplore the potential of Cloud Run, Knative, Cloud Build, Google Kubernetes Engine, and Cloud StorageGet to grips with architectural decisions, seamless deployments, containerization, and serverless solutionsBook Description Google Cloud's serverless platform allows organizations to scale fully managed solutions without worrying about the underlying infrastructure. With this book, you will learn how to design, develop, and deploy full stack serverless apps on Google Cloud. The book starts with a quick overview of the Google Cloud console, its features, user interface (UI), and capabilities. After getting to grips with the Google Cloud interface and its features, you will explore the core aspects of serverless products such as Cloud Run, Cloud Functions and App Engine. You will also learn essential features such as version control, containerization, and identity and access management with the help of real-world use cases. Later, you will understand how to incorporate continuous integration and continuous deployment (CI/CD) techniques for serverless applications. Toward the concluding chapters, you will get to grips with how key technologies such as Knative enable Cloud Run to be hosted on multiple platforms including Kubernetes and VMware. By the end of this book, you will have become proficient in confidently developing, managing, and deploying containerized applications on Google Cloud. What you will learnExplore the various options for deploying serverless workloads on Google CloudDetermine the appropriate serverless product for your application use caseIntegrate multiple lightweight functions to build scalable and resilient servicesIncrease productivity through build process automationUnderstand how to secure serverless workloads using service accountsBuild a scalable architecture with Google Cloud Functions and Cloud RunWho this book is for If you are a cloud administrator, architect, or developer who wants to build scalable systems and deploy serverless workloads on Google Cloud, then this book is for you. To get the most out of this book, a basic understanding of the serverless ecosystem and cloud computing will be beneficial.
