Cloud computing Books

Book SynopsisPrinciples of Soft Computing Using Python Programming An accessible guide to the revolutionary techniques of soft computing Soft computing is a computing approach designed to replicate the human mind's unique capacity to integrate uncertainty and imprecision into its reasoning. It is uniquely suited to computing operations where rigid analytical models will fail to account for the variety and ambiguity of possible solutions. As machine learning and artificial intelligence become more and more prominent in the computing landscape, the potential for soft computing techniques to revolutionize computing has never been greater. Principles of Soft Computing Using Python Programming provides readers with the knowledge required to apply soft computing models and techniques to real computational problems. Beginning with a foundational discussion of soft or fuzzy computing and its differences from hard computing, it describes different models for soft computing and

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Book SynopsisAdora Nwodo is a software engineer who develops mixed-reality products at Microsoft. She frequently shares her insights on cloud technology and careers on her blog and popular YouTube channel. She is the founder of NexaScale, a social enterprise aimed at offering and sharing new opportunities for projects and work experiences within the tech sector. She is a sought-after public speaker, thought leader and author. She is based in Cambridge, UK.

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Book SynopsisAdora Nwodo is a software engineer who develops mixed-reality products at Microsoft. She frequently shares her insights on cloud technology and careers on her blog and popular YouTube channel. She is the founder of NexaScale, a social enterprise aimed at offering and sharing new opportunities for projects and work experiences within the tech sector. She is a sought-after public speaker, thought leader and author. She is based in Cambridge, UK.

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Book SynopsisDo you need to learn about cloud computing architecture with Microsoft's Azure quickly? Read this book! It gives you just enough info on the big picture and is filled with key terminology so that you can join the discussion on cloud architecture.

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Book SynopsisLearn how to run large-scale, data-intensive workloads with Compute Engine, Google's cloud platform. Written by Google engineers, this tutorial walks you through the details of this Infrastructure as a Service by showing you how to develop a project with it from beginning to end.

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Book SynopsisExamine the building blocks that make any good MVC framework using PHP 8. This book exposes all the considerations that many developers take for granted when using a popular framework, and teaches you how to make this MVC framework your own.You'll quickly get started writing your first bit of framework code,then, you build a variety of examples using aspects of an MVC framework, including a router, a template engine, a database library, a persistence engine (ORM), and a testing framework.In the next section, you'll implement sessions, caches, file systems, queues, logging, and mail. You'll wrap up by building a larger scale sample web application: a sales website for a company that sells rockets. Along the way, this book lays bare all the secret parts of MVC to take with you to apply to your own PHP-based MVC projects.What You Will LearnBuild PHP-based web applications using the model view controller (MVC) architecture Write your first bit of framework codeCompare the code Table of Contents1: Ways to Use PHP2: Writing Our First Bit of Code3: Building a Router4: Building a Template Engine5: Building a Validator6: Building a Database Library7: Building an Object-Relational Mapper Library8: Building a Dependency Injection Container9: Testing Our Framework10: Config, Cache, Sessions, Filesystems11: Queues, Logging, Emails12: Publishing Your CodeAfterword: Wrapping Up

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Book SynopsisGet started with Azure Cognitive Services and its APIs that expose machine learning as a service. This book introduces the suite of Azure Cognitive Services and helps you take advantage of the proven machine learning algorithms that have been developed by experts and made available through Cognitive Services, easily integrating those algorithms into your own applications without having to develop the algorithms from scratch. The book also shows you how to use the algorithms provided by Cognitive Services to accelerate data analysis and development within your organization.   The authors begin by introducing the tools and describing the steps needed to invoke libraries to analyze structured and unstructured text, speech, and pictures, and you will learn to create interactive chatbots using the Cognitive Services libraries. Each chapter contains the information you need to implement artificial intelligence (AI) via Azure Cognitive Services in your peTable of Contents1. Introducing Cognitive Services2. Prerequisites and Tools3. Vision4. Language in Cognitive Services5. Speech Services6. Power Platform & Cognitive Services7. Chatbots8. Ethics in AI

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Book SynopsisWelcome to this introductory guide to using Microsoft''s Azure Arc service, a new multi-cloud management platform that belongs in every cloud or DevOps estate. As many IT pros know, servers and Azure Kubernetes Service drive a huge amount of consumption in Azure-so why not extend familiar management tools proven in Azure to on-premises and other cloud networks? This practical guide will get you up to speed quickly, with instruction that treads light on the theory and heavy on the hands-on experience to make setting up Azure Arc servers and Kubernetes across multiple clouds a lot less complex. Azure experts and MVPs Buchanan and Joyner provide just the right amount of context so you can grasp important concepts, and get right to the business of using and gaining value from Azure Arc. If your organization has resources across hybrid cloud, multi-cloud, and edge environments, then this book is for you. You will learn how to configure and use Azure Arc to uniformly manage workloads across all of these environments.What You Will Learn  Introduces the basics of hybrid, multi-cloud, and edge computing and how Azure Arc fits into that IT strategy Teaches the fundamentals of Azure Resource Manager, setting the reader up with the knowledge needed on the technology that underpins Azure Arc Offers insights into Azure native management tooling for managing on-premises servers and extending to other clouds Details an end-to-end hybrid server monitoring scenario leveraging Azure Monitor and/or Azure Sentinel that is seamlessly delivered by Azure Arc Defines a blueprint to achieve regulatory compliance with industry standards using Azure Arc, delivering Azure Policy from Azure Defender for Servers Explores how Git and GitHub integrate with Azure Arc; delves into how GitOps is used with Azure Arc Empowers your DevOps teams to perform tasks that typically fall under IT operations Dives into how to best use Azure CLI with Azure Arc Who This Book Is ForDevOps, system administrators, security professionals, and IT workers responsible for servers both on-premises and in the cloud. Some experience in system administration, DevOps, containers, and use of Git/GitHub is helpful.Table of Contents1. Azure Arc as Extension of the Azure Control Plane 2. Azure Resource Manager Insights 3. Azure Management Insights 4. Azure Arc Servers: Getting Started 5. Azure Arc Servers: Using at Scale 6. Hybrid Server Monitoring Solution 7. Regulatory and Security Compliance for Azure Arc Servers 8. GitOps Insights9. Azure Arc Enabled Kubernetes: Getting Started

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Book SynopsisApply different enterprise integration and processing strategies available with Pulsar, Apache''s multi-tenant, high-performance, cloud-native messaging and streaming platform. This book is a comprehensive guide that examines using Pulsar Java libraries to build distributed applications with message-driven architecture.You''ll begin with an introduction to Apache Pulsar architecture. The first few chapters build a foundation of message-driven architecture. Next, you''ll perform a setup of all the required Pulsar components. The book also covers work with Apache Pulsar client library to build producers and consumers for the discussed patterns. You''ll then explore the transformation, filter, resiliency, and tracing capabilities available with Pulsar. Moving forward, the book will discuss best practices when building message schemas and demonstrate integration patterns using microservices. Security is an important aspect of any applicatiTable of ContentsData Processing with Apache PulsarChapter 1: Introduction to Apache Pulsar Chapter 2: Working with MessagesChapter 3: Working with Pulsar Functions Chapter 4: Schema RegistryChapter 5: Build Microservices using PulsarChapter 6: Pulsar ConnectersChapter 7: Pulsar SecurityChapter 8: Deploy Pulsar on Kubernetes

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Book SynopsisWrite efficient, smart, and optimized code for containerized applications on public and private clouds at a generic level. This book shows you how to set up microservices that are robust, scalable, and capable of running on GKE (Google Kubernetes Service), AKS (Azure Kubernetes Service), ECS (Elastic Container Service), or even on a vanilla K8S cluster.The book covers the nuts and bolts of container orchestration engines (COEs) and explains how to install and configure them. It also covers creation and deployment of a sample application on COEs. You will learn how to integrate different applications such as OAuth and how to test them and secure them using Istio Citadel. You also will be taught how to create HPA rules for microservices and scale only those microservices that require it, making your stack intelligent. In the concluding chapter, the book explains how to build a SaaS solution from scratch, running on the cloud with automated deployments accessed publicly via a secured ingrTable of Contents•Chapter 1, Cloud Computing and KubernetesChapter Goal:o What is cloud computingo What is Kuberneteso Different distributions of Kuberneteso Setting up a K8S cluster- for workshop purposeso Common commands of K8So Place of Kubernetes from an architecture point of view.•Chapter 2, Creating Applications on KubernetesChapter Goal:o Create an Apache http servero Create a Java Tomcat war-based servero Create a gRPC API server o Create a Rest API servero Differences when creating applications on Kubernetes.o How will the application be actually called in a production based cluster.•Chapter 3, Testing of Applications on KubernetesChapter Goal:o Creating a CI system for testing.o Using of Pytest, go test, behave and other best testing tools based on programming language.o Adding a simple CD system stage.o Coverage of code and mock of applications to replicate real time scenarios.•Chapter 4, Security of ApplicationsChapter Goal:o Creating a book inventory application composed of UI, API and DBo Using cloud services instead of reinventing the wheelo Using and understand Istio for TLS Encryption and monitoring.o Understanding authentication/authorization and RBAC systems.o Leverage all the services available rather than developing things to secure all microservices.•Chapter 5, Networking of ApplicationsChapter Goal:o Understanding the basics of networking in Kubernetes.o How containers/pod reach each other via overlay networking.o Different ways networking is configured in Kubernetes cluster.o Using name-based DNS routing in applications rather than IP’so Understanding load balancers and the features provided by it.o Using Istio to create a service mesh of microservices and see the flow of traffic between them.o Configuring Kubernetes objects such as Ingress, Service, Endpoints.•Chapter 6, Scaling of Software SolutionChapter Goal:o Identify which microservice of the solution is becoming a bottlenecko Creating HPA rules in Kubernetes to scale specific microservice.o Use case and real-world problems and solutions to them via scaling. •Chapter 7, Building a SaaS SolutionChapter Goal:o Start with nothing but a simple k8s cluster.o Create microservice with your own hands one by one.o Identify what all services are required for building a sample SaaS e commerce solution.o Creating/Configuring a UI, API, DB, business logic, monitoring software stack.o Architecting the entire solution.o Bring the stack up and testing it against load and autoscaling the solution to support any number of requests.

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Book SynopsisGet introduced to Azure Arc-enabled Data Services and the powerful capabilities to deploy and manage local, on-premises, and hybrid cloud data resources using the same centralized management and tooling you get from the Azure cloud. This book shows how you can deploy and manage databases running on SQL Server and Postgres in your corporate data center or any cloud as if they were part of the Azure platform. This second edition has been updated to the latest codebase, allowing you to use this book as your handbook to get started with Azure Arc-enabled Data Services today. Learn how to benefit from Azure's centralized management, the automated rollout of patches and updates, managed backups, and more.This book is the perfect choice for anyone looking for a hybrid or multi-vendor cloud strategy for their data estate. The authors walk you through the possibilities and requirements to get Azure SQL Managed Instance and PostgresSQL Hyperscale deployed outside of Azure, so the services are accessible to companies that cannot move to the cloud or do not want to use the Microsoft cloud exclusively. The technology described in this book will benefit those required to keep sensitive services, such as medical databases, away from the public cloud equally as those who can't move to a public cloud for other reasons such as infrastructure constraints but still want to benefit from the Azure cloud and the centralized management and tooling that it supports. What You Will LearnUnderstand the fundamentals and architecture of Azure Arc-enabled data servicesBuild a multi-cloud strategy based on Azure Data ServicesDeploy Azure Arc-enabled data services on premises or in any cloudDeploy Azure Arc-enabled SQL Managed Instance on premises or in any cloudDeploy Azure Arc-enabled PostgreSQL Hyperscale on premises or in any cloudBackupand Restore your data that is managed by Azure Arc-enabled data servicesManage Azure-enabled data services running outside of AzureMonitor Azure-enabled data services through Grafana and KibanaMonitor Azure-enabled data services running outside of Azure through Azure MonitorWho This Book Is ForDatabase administrators and architects who want to manage on-premises or hybrid cloud data resources from the Microsoft Azure cloud. Especially for those wishing to take advantage of cloud technologies while keeping sensitive data on premises and under physical control.Table of Contents1. A Kubernetes Primer2. Azure Arc-Enabled Data Services3. Getting Ready for Deployment4. Installing Kubernetes5. Deploying a Data Controller in Indirect Mode 6. Deploying a Data Controller in Direct Mode 7. Deploying an Azure Arc-Enabled SQL Managed Instance8. Deploying Azure Arc-Enabled PostgreSQL Hyperscale 9. Monitoring and Management

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Book SynopsisDesign and implement a modern data lakehouse on the Azure Data Platform using Delta Lake, Apache Spark, Azure Databricks, Azure Synapse Analytics, and Snowflake. This book teaches you the intricate details of the Data Lakehouse Paradigm and how to efficiently design a cloud-based data lakehouse using highly performant and cutting-edge Apache Spark capabilities using Azure Databricks, Azure Synapse Analytics, and Snowflake. You will learn to write efficient PySpark code for batch and streaming ELT jobs on Azure. And you will follow along with practical, scenario-based examples showing how to apply the capabilities of Delta Lake and Apache Spark to optimize performance, and secure, share, and manage a high volume, high velocity, and high variety of data in your lakehouse with ease. The patterns of success that you acquire from reading this book will help you hone your skills to build high-performing and scalable ACID-compliant lakehouses using flexible and cost-efficient decoupled storTable of ContentsIntroductionPart I. Getting Started1. The Lakehouse Paradigm2. Mount Lakes to DatabricksPart II. Lakehouse Platforms3. Snowflake Data Warehouse4. Synapse Analytics Serverless Pools5. Databricks SQL AnalyticsPart III. Apache Spark6. PySpark7. Extract, Load, Transform JobsPart IV. Delta Lake8. Delta Schema Evolution9. Delta Change Feed10. Delta Clones11. Delta Live Tables12. Delta SharingPart V. Optimizing Performance13. Dynamic Partition Pruning for Querying Star Schemas14. Z-Ordering and Data Skipping15. Adaptive Query Execution16. Bloom Filter Index17. HyperspacePart VI. Lakehouse Capabilities18. Auto Loader Resource Management19. Advanced Schema Evolution with Auto Loader 20. Python Wheels21. Security and Controls22. Unity Catalog

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Book SynopsisGain insights into the different challenges that can be solved using Go, with a focus on containers, Linux, security, networking, user interfaces and other relevant cloud based topics. This book reviews the necessary tools to create container-based cloud solutions with Go, a programming language that was born out of the need to address scalable, high availability cloud computing architecture needs inside Google. Go, also known as Golang, has been adopted across different industries and products with many popular Open Source projects that power cloud computing technologies such as Docker and Kubernetes being written with Go. As the complexity of cloud technology increases, so does the need for people to understand how things work under-the-hood and to fix them when they''re broken. What You Will Learn Understand how the various components of a container-based system works Tackle complex technical isTable of ContentsSoftware Development with Go Part 1: System Programming Chapter 1 - System Calls Chapter 2 - System Calls Using Go Chapter 3 - Accessing proc File System Part 2: Containers Chapter 4 - Simple Containers Chapter 5 - Containers with Networking Chapter 6 - Docker Security Part 3: Application Security Chapter 7 - Gosec and AST Chapter 8 – Scorecard Part 4: Networking Chapter 9 - Simple Networking Chapter 10 - System Networking Chapter 11 - Google gopacket Chapter 12 - Epoll Library Part 5: Securing Linux Chapter 13 - Vulnerability Scanner Chapter 14 – CrowdSec Part 6: Terminal User Interface Chapter 15 - ANSI and UI Chapter 16 - TUI Framework Part 7: Linux System Chapter 17 – systemd Chapter 18 – cadvisor

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Book SynopsisGet ready to develop microservices using open source Eclipse MicroProfile and Jakarta EE, and deploy them on Kubernetes/Docker. This book covers best practices for developing cloud-native applications with MicroProfile and Jakarta EE. This book introduces you to cloud-native applications and teaches you how to set up your development environment. You'll learn about the various components of MicroProfile, such as fault tolerance, config, health check, metrics, and JWT auth. You'll develop a RESTful web service made up of some microservices. You'll deploy your application on Docker and Kubernetes. After reading this book, you'll come away with the fundamentals you need to build and deploy your first cloud-native Java-based app. What You'll LearnBuild your first cloud-native Java-based app with the open source MicroProfile platform, and Jakarta EE 10 APIsDevelop a RESTful web service using MicroProfile and Jakarta EEDiscover and explore the key components of the MicroProfile fraTable of Contents1. Introduction to Cloud-Native Applications1.1. What are Cloud-Native Applications?1.2. Why Use Cloud-Native Applications?1.3. What are the Benefits of Using Cloud-Native Applications?2. Setting Up Your Development Environment2.1. Prerequisites2.2. Installing Java SE 172.3. Installing Kubernetes2.4. Installing Docker3. Creating a Config Component3.1. What is a Config Component?3.2. Setting Up the Config Component3.3. Accessing the Configuration Data in Your Application 4. Using the Fault Tolerance Component4.1. What is the Fault Tolerance Component?4.2. Configuring the Fault Tolerance Component4.3. Handling Failures in Your Application5. Using the Health Check Component5.1. What is the Health Check Component?5.2. Configuring the Health Check Component5.3. Checking the Health of Your Application6. Using the Metrics Component6.1. What is the Metrics Component?6.2. Collecting Metrics Data in Your Application 7. Using the JWT Authentication Component7.1. What is the JWT Authentication Component?7.2. Configuring the JWT Authentication Component7.3. Authenticating Users in Your Application8. Developing a RESTful Web Service8.1. What is a RESTful Web Service?8.2. Developing a RESTful Web Service8.3. Implementing the HTTP Methods9. Deploying an Application on Kubernetes/Docker9.1. What is Kubernetes?9.2. What is Docker?9.3. Installing Kubernetes9.4. Creating a Kubernetes Cluster9.5. Installing Docker on Kubernetes9.6. Deploying an Application on Kubernetes/Docker9.7. Benefits of using Jakarta EE and Kubernetes/Docker for developing cloud-native applications.

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Book SynopsisAudience Level: Intermediate to AdvancedTable of ContentsPart I. Getting Started1. The Core Essentials2. AWS Tools for .NET3. Additional ToolsPart II. Hosting Your Applications4. Virtual Machines5. Containers6. ServerlessPart III. Storing Your Data7. S3 Object Storage8. Microsoft SQL Server9. Other RDS Databases10. NoSQL Databases and AWS11. Purpose-built DatabasesPart IV. Moving Existing Apps to AWS12. Moving to Virtual Machines.13. Containerizing 14. Migrating your Data15. Re-platforming and RefactoringPart V. Building Cloud Native Applications16. Events and Messaging17. Monitoring and Observability

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Book SynopsisIntermediate to AdvancedTable of Contents1. Why Spring Cloud FunctionsThis chapter takes the reader through the need for Spring Cloud Functions and KNative. The rationale for Spring Cloud Functions will be elucidated through example implementation on on-prem and cloud infrastructures. The chapter highlights the “code once deploy anywhere” characteristic of Spring Cloud Functions. Subtitles1. Writing functions and deploying to any hyperscaler2. Example code3. Spring Cloud Functions on AWS (EKS, Fargate)4. Spring Cloud Functions on Azure (AKS)5. Spring Cloud Functions on Google (Cloud Run)6. Spring Cloud Functions on VMWare Tanzu (TKG, PKS)7. Spring Cloud Functions on RedHat OpenShift (OCP)2. Getting Started with Spring Cloud FunctionsThis chapter walks the reader through the steps required to get started with Spring Serverless on their platform of choice, either locally, on-prem or on the cloud. Step by Step instructions take the reader through the process of getting the environment set up for coding.Subtitles1. Step by Step: Setup locally with Kubernetes and KNative with Spring Cloud Functions2. Step by Step: Setup on AWS with EKS and KNative with Spring Cloud Functions3. Step by Step: Setup on GCP with Cloud Run/GKE and KNative with Spring Cloud Functions4. Step by Step: Setup on Azure with AKS and KNative with Spring Cloud Functions5. Step by Step: Setup on VMWare Tanzu TKG and KNative6. Step by Step: Setup on RedHat Openshift and KNative3. Coding, testing, and deploying with Spring Cloud FunctionsThis chapter covers the coding, testing, and deploying using your favorite IDE like Eclipse, Eclipse Che, Intelij IDEA, Redhat Code Ready Workspace. The reader will build an example and deploy to their favorite platforma. Building a simple example with Spring Cloud Functionsb. Testing the example will sample datac. Setting up a CI/CD pipeline for deploying to a target platformd. Deploying to the target platfomi. AWSii. GCPiii. Azureiv. VMWare Tanzuv. RedHat Openshift4. Building Event Driven Data pipelines with Spring Cloud FunctionsEvent Driven data pipelines act as a conduit to flow of data based on a specific event. The event can be a purchase order triggered on the website that initiate a data flow chain that includes aggregation of data from various data sources and splitting the data to various consumers. This chapter will discuss the various ways that Spring Spring Serverless can be implemented in the various Cloud providersSubtitles1. Spring Cloud Functions and Spring Cloud Data Flow and Spring Cloud Streams2. Spring Cloud Functions and AWS Glue3. Spring Cloud Functions and Google Cloud Data Flow4. Spring Cloud Functions and Azure Data Factory5. AI/ML Trained Serverless Endpoints with Spring Cloud FunctionsConversational AI models are one of the complex implementations that may lead to heavy use of resources in the cloud. Leveraging Serverless infra and functions can help alleviate the costs by being invoked only when needed. This chapter will help layout the blueprint of how to leverage Spring Serverless with on-prem or cloud-based AI/ML environmentsSubtitles1. Spring Cloud Functions with Google Cloud Functions and Tensor Flow2. Spring Cloud Functions with AWS Glue and AWS Sage or AI/ML3. Spring Cloud Functions with Azure Data Factory and Azure ML4. Spring Cloud Functions with Apache AI/ML on-prem VMWare Tanzu and Openshift6. Spring Cloud Functions and IOTThis chapter will take the reader through blueprints and architect diagrams of how Spring serverless works in conjunction with IOT on various Hyperscalers (Cloud Providers) or SaaS IOT Gateway providers. Subtitles1. Spring Cloud Functions on the Cloud with AWS IOT2. Spring Cloud Functions on the cloud with Azure IOT3. Spring Cloud Functions on the cloud with GCP IOT4. Spring Cloud Functions on-prem with IOT gateway on a SaaS provider (Eg, SmartSense)7. Industry specific examples with Spring Cloud FunctionsThis chapter will provide industry specific examples and use cases that will help the reader understand how Spring Serverless can be leveraged within their specific business use case1. Oil/ Natural gas pipeline tracking with Spring Cloud Functions, IOT and Spring Cloud Data Flow2. Enabling ubiquitous health care with Spring Cloud Functions and Big Data Pipelines3. Connected vehicles with Spring Cloud Functions4. Conversational AI in Retail with Spring Cloud Functions

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Book SynopsisIntermediate user levelTable of Contents1. Getting Started with MySQL in the Cloud2. Oracle Cloud Infrastructure3. A Brief Tutorial of MySQL4. MySQL Database Service5. Backup and Restore6. Point-in-Time Recovery7. Data Import and Export8. High Availability9. OCI Command-Line Interface and Application Programming Interfaces10. Migrating to MDS

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Book SynopsisOverhaul your debugging techniques and master the theory and tools needed to debug and troubleshoot cloud applications in production environments. This book teaches debugging skills that universities often avoid, but that typically consume as much as 60% of our time as developers. The book covers the use of debugger features such as tracepoints, object marking, watch renderers, and more. Author Shai Almog presents a scientific approach to debugging that is grounded in theory while being practical enough to help you to chase stubborn bugs through the maze of a Kubernetes deployment. Practical Debugging at Scale assumes a polyglot environment as is common for most enterprises, but focuses on JVM environments. Most of the tooling and techniques described are applicable to Python, Node, and other platforms, as well as to Java and other JVM languages. The book specifically covers debugging in production, an often-neglected discipline but an all too painful reaTable of ContentsIntroductionPart I. Basics1. Know Your Debugger2. The Checklist3. The Auxiliary Tools4. Logging, Testing, and Fail Fast5. Time Travel DebuggingPart II. The Modern Production Environment6. Debugging Kubernetes7. Serverless Debugging8. Fullstack Debugging9. Observability and Monitoring10. Developer ObservabilityPart III. In Practice11. Tools of Learning12. Performance and Memory13. Security14. Bug Strategies

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Book SynopsisExplore the serverless world using Amazon Web Services (AWS) and develop various architectures, including those for event-driven and disaster recovery designs. This book will give you an understanding of different distributed serverless architectures and how to build them using AWS components. You will begin with an introduction to serverless components and architectures, before progressing to data platforms and containers. Next, you''ll dig deeper into these serverless architectures and how they leverage AWS components through practical use cases. You will also explore designing systems in a multi-cloud paradigm. Author Jithin Jude Paul then demonstrates how efficient serverless architectures are, and the benefits of designing distributed systems globally in a cost-effective way while incorporating a microservices architectural style. Distributed Serverless Architectures with AWS concludes with a discussion of current and future trends in serverlTable of ContentsChapter 1: Introduction to Serveless ArchitecturesChapter Goal: Introduction to serverless components and architectureNo of pages 20Sub -Topics1. Serverless description2. Significance of serverless architectures3. Serverless vs containerized environments4. Main components of serverless architectureChapter 2: Distributed Serverless ArchitecturesChapter Goal: Overview of types of serverless architecturesNo of pages: 40Sub - Topics 1. Event driven architectures2. Disaster recovery architectures3. High availability architectures4. Global and cross region architectures5. Database and backend architectures6. Hybrid serverless architectureChapter 3: Event Driven ArchitecturesChapter Goal: In depth view of Event Driven ArchitecturesNo of pages : 30Sub - Topics: 1.General architecture and AWS components used 2.Explanation 3. Use cases where event driven architecture can be utilized4. Security and performance of this architecture5. QuickStart template (CloudFormation/ Terraform/ Serverless Framework)Chapter 4: Disaster Recovery ArchitecturesChapter Goal: Designing resilient architectures so that in the event of a disaster, the system keeps runningNo of pages: 40Sub - Topics: 1. General architecture and AWS components used 2. Explanation 3. Use cases where disaster recovery architecture can be implemented4. Active – active and active – passive configurations using this architecture5. Security and performance of this architecture6. QuickStart template(CloudFormation/ Terraform/ Serverless Framework)Chapter 5: High Availability ArchitecturesChapter Goal: Architect highly available systems using serverless Pages: 30 1. The general architecture and AWS components used 2. Explanation 3. Use cases where disaster recovery architecture can be implemented4. Active-active and active-passive configurations using this architecture5. Security and performance of this architecture6. QuickStart template(CloudFormation/ Terraform/ Serverless Framework)Chapter 6: Global and Cross Region ArchitecturesChapter Goal: Architect globally/ multi region systems using serverlessPages: 30 1. The general architecture and AWS components used 2. Explanation 3. Use cases where disaster recovery architecture can be implemented4. Active-active and active-passive configurations using this architecture5. Security and performance of this architecture6. QuickStart template(CloudFormation/ Terraform/ Serverless Framework)Chapter 7: Authentication, CICD and Databases in Serverless Chapter Goal: Describe authentication components, CICD Pipeline and databases for serverless architecturesPages: 40 1.Architecting authentication modules a) Overview and implementation of different Auth modulesb) Use cases of different Auth modules2. Using the correct database for serverless architecturesa) Stateful vs serverless databasesb) Implementation of serverless databases in AWS c) Use cases for various database available in AWS3. Designing CICD for serverless architecture4. QuickStart template(CloudFormation/ Terraform/ Serverless Framework)Chapter 7: Hybrid Serverless ArchitecturesChapter Goal: How serverless can co exist with traditional architectures with stateful componentsPages: 30 1. Need for hybrid architectures 2. Integrating serverless components into an existing environment3.Use cases of hybrid architectures4.Scaling of serverless and Non serverless components in a hybrid architecture5. Security and performance of this architecture6. QuickStart Template(CloudFormation/ Terraform/ Serverless Framework)Chapter 8: Microservices Architecture using ServerlessChapter Goal: How to utilize serverless environment to architect microservices architecturesPages: 20 1. Need for microservices based architecture 2. General pointers while architecting microservices using serverless components3.Use cases and advantages of this architecture4. QuickStart Template(CloudFormation/ Terraform/ Serverless Framework)Chapter 9: Looking through the Well Architected Framework lensChapter Goal: How well do serverless architectures fare when looking through AWS’ Well Architected Framework toolPages: 30 1. Serverless components used to achieve operational excellence pillar2. Serverless components used to achieve security pillar3. Serverless components used to achieve reliability pillar4. Serverless components used to achieve performance efficiency pillar5. Serverless components used to achieve cost optimization pillarChapter 10: Looking AheadChapter Goal: Discuss the latest and future trends in serverlessPages: 5-101. Latest and future trends in serverless

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Book SynopsisImprove your odds of passing one of the most highly sought-after exams for developers working with Microsoft''s cloud platform: Exam AZ-204: Developing Solutions for Microsoft Azure. This book guides you through practical examples of each of the technologies covered by the exam while exposing you to the settings and interactions between platform solutions that you will need to be in command of to prepare for the exam and to use on your job in Azure development. Chapters in this book correspond directly to the exam skills outline and are delivered in a from-the-ground-up approach, allowing you to build your knowledge as you go. This approach serves to help even novice developers get up to speed quickly, while allowing more experienced developers to find the exact topics and scenarios they need to hone their skill sets as they both prepare for the exam and reference information for real-world solutions. As you work through each chapTable of ContentsIntroductionPart I. Develop for Azure1. Develop Solutions that Use Blob Storage2. Develop Solutions that Use Cosmos DB StoragePart II. Develop Azure Compute Solutions3. Implement IaaS Solutions4. Create Azure App Service Web Apps5. Azure Container Ecosystem6. Implement Azure FunctionsPart III. Implement Azure Security7. Implement User Authentication and Authorization8. Implement Secure Cloud SolutionsPart IV. Monitor, Troubleshoot, and Optimize Azure Solutions9. Implement Caching for Solutions10. Troubleshoot Solutions by Using Metrics and Log Data Part V. Connect to and Consume Azure Services and Third-Party Services11. Implement API Management12. Develop Event-Based Solutions13. Develop Message-Based Solutions

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Book SynopsisWhile many guides exist to help software engineers learn cloud networking design and architecture concepts, and even prepare for cloud network certifications on AWS and Azure, far fewer resources are available covering the Google Cloud Platform (GCP) Professional Cloud Network Engineer certification exam. Well, look no further! This self-paced guide book is designed to help engineers learn cloud networking best practices on GCP, and prepare for the GCP Professional Cloud Network Engineer certification exam.You will waste no time when you use this study companion. It lets you dive in and learn how GCP differs from other public cloud providers (AWS and Microsoft Azure). You will understand GCP''s unique ability to allow virtual private clouds (VPCs) that span across multiple regions. You will know how to leverage GCP as a competitive advantage in the IT engineering community. Key concepts covered on the exam are called out and applied in each chapter of this book, giving you boTable of Contents1. Exam Overview1.1. Exam Subject Areas1.2. Exam Format1.3. Supplemental Study Materials1.4. Sign up for a Free Tier1.5. Register for the Exam1.5.1. Schedule the Exam1.5.2. Rescheduling and Cancellation Policy1.5.3. Exam Results1.5.4. Retake Policy1.6. Summary2. Designing, planning, and prototyping a Google Cloud network2.1. Designing an overall network architecture2.1.1. High availability, failover, and disaster recovery strategies2.1.2. DNS strategy (e.g., on-premises, Cloud DNS)2.1.3. Security and data exfiltration requirements2.1.4. Load balancing2.1.5. Applying quotas per project and per VPC2.1.6. Hybrid connectivity (e.g., Google private access for hybrid connectivity)2.1.7. Container networking2.1.8. SaaS, PaaS, and IaaS services2.2. Designing Virtual Private Cloud (VPC) instances2.2.1. VPC Specifications2.2.2. Subnets2.2.3. IP address management and brin your own IP (BYOIP)2.2.4. Standalone vs. Shared VPC2.2.5. Multiple vs. single2.2.6. Regional vs. multi-regional2.2.7. VPC Network Peering2.2.8. Firewalls (e.g., service account-based, tag-based)2.2.9. Custom routes2.3. Designing a hybrid and multi-cloud network2.3.1. Drivers for Hybrid and Multi-cloud strategy2.3.2. Overall goals2.3.3. Designing a Hybrid and Multi-cloud strategy2.3.4. Dedicated Interconnect vs. Partner Interconnect2.3.5. Direct vs. Carrier Peering2.3.6. IPsec VPN2.3.7. Bandwidth and constraints provided by hybrid connectivity solutions2.3.8. Cloud Router2.3.9. Multi-cloud and Hybrid topologies2.3.10. Regional vs. global VPC routing mode2.3.11. Failover and Disaster Recovery strategy2.3.12. Accessing Google Services/APIs privately from on-premises locations2.3.13. IP address management across on-premises locations and cloud2.4. Designing an IP addressing plan for Google Kubernetes Engine2.4.1. GKE VPC-native clusters2.4.2. Optimizing GKE IP ranges2.4.3. Expanding GKE IP ranges2.4.4. Public and private cluster nodes2.4.5. Control plane public vs. private endpoints2.5. Summary2.6. Exam questions3. Implementing Virtual Private Cloud (VPC) instances3.1. Configuring VPC resources3.1.1. Creating VPCs3.1.2. Creating subnets3.1.3. Listing subnets3.1.4. Listing VPCs3.1.5. Deleting VPCs3.2. Configuring VPC Network Peering3.3. Creating a Shared VPC network and sharing subnets with other projects3.3.1. Host and service project concepts3.3.2. Shared VPC deep dive3.3.3. Assigning roles to principals3.3.4. Creating the shared VPC3.3.5. Creating the service projects3.3.6. Enabling Compute API for service and host projects3.3.7. Enabling host project3.3.8. Attaching service projects3.3.9. Assigning individual subnet-level roles to service projects3.4. Using a Shared VPC3.4.1. Listing usable subnets3.4.2. Creating VMs3.4.3. Verifying VMs connectivity3.4.4. Deleting VMs3.5. Sharing subnets using folders3.6. Configuring API access to Google services (e.g., Private Google Access, public interfaces)3.6.1. Configuring Private Google Access (PGA)3.6.2. Configuring Private Service Connect (PSC)3.7. Expanding VPC subnet ranges after creation3.8. Configuring routing3.8.1. Static vs. dynamic routing3.8.2. Global vs. regional dynamic routing3.8.3. Routing policies using tags and priority3.8.4. Internal load balancer as a next hop3.8.5. Custom route import/export over VPC Network Peering3.9. Configuring and maintaining Google Kubernetes Engine clusters. Considerations include:3.9.1. VPC-native clusters using alias IPs3.9.2. Clusters with Shared VPC3.9.3. Creating Cluster Network Policies3.9.4. Private clusters and private control plane endpoints3.9.5. Adding authorized networks for cluster control plane endpoints3.10. Configuring and managing firewall rules. Considerations include:3.10.1. Target network tags and service accounts3.10.2. Rule priority3.10.3. Protocols and Ports3.10.4. Direction3.10.5. Firewall rule logs3.10.6. Summary4. Implementing VPC Service Controls4.1. Creating and configuring access levels and service perimeters4.2. Service perimeter deep dive4.3. VPC accessible services4.4. Perimeter bridges4.5. Audit logging4.6. Dry run mode4.7. Dry-run perimeter deep dive4.8. Exam questions5. Configuring load balancing5.1. Google Cloud load balancers family5.2. Backend services and network endpoint groups (NEGs)5.3. Firewall rules to allow traffic and health checks to backend services5.4. Health checks for backend services and target instance groups5.5. Configuring backends and backend services with balancing method (e.g., RPS, CPU, Custom), session affinity, and capacity scaling/scaler5.6. TCP and SSL proxy load balancers5.7. Load balancers (e.g., External TCP/UDP Network Load Balancing, Internal TCP/UDP Load Balancing, External HTTP(S) Load Balancing, Internal HTTP(S) Load Balancing)5.8. Protocol forwarding5.9. Accommodating workload increases using autoscaling vs. manual scaling5.10. Configuring Google Cloud Armor policies. Considerations include:5.11. Security policies5.12. Web application firewall (WAF) rules (e.g., SQL injection, cross-site scripting, remote file inclusion)5.13. Attaching security policies to load balancer backends5.14. Configuring Cloud CDN. Considerations include:5.15. Enabling and disabling5.16. Cloud CDN5.17. Cache keys5.18. Invalidating cached objects5.19. Signed URLs5.20. Custom origins6. Configuring advanced networking services6.1. Configuring and maintaining Cloud DNS6.1.1. Managing zones and records6.1.2. Migrating to Cloud DNS6.1.3. DNS Security Extensions (DNSSEC)6.1.4. Forwarding and DNS server policies6.1.5. Integrating on-premises DNS with Google Cloud6.1.6. Split-horizon DNS6.1.7. DNS peering6.1.8. Private DNS logging6.2. Configuring Cloud NAT6.2.1. Addressing6.2.2. Port allocations6.2.3. Customizing timeouts6.2.4. Logging and monitoring6.2.5. Restrictions per organization policy constraints6.3. Configuring network packet inspection 6.3.1. Packet Mirroring in single and multi-VPC topologies6.3.2. Capturing relevant traffic using Packet Mirroring source and traffic filters6.3.3. Routing and inspecting inter-VPC traffic using multi-NIC VMs (e.g., next-generation firewall appliances)6.3.4. Configuring an internal load balancer as a next hop for highly available multi-NIC VM routing7. Implementing hybrid interconnectivity7.1. Configuring Cloud Interconnect7.1.1. Dedicated Interconnect connections and VLAN attachments7.1.2. Partner Interconnect connections and VLAN attachments7.2. Configuring a site-to-site IPsec VPN7.2.1. High availability VPN (dynamic routing)7.2.2. Classic VPN (e.g., route-based routing, policy-based routing)7.3. Configuring Cloud Router7.3.1. Border Gateway Protocol (BGP) attributes (e.g., ASN, route priority/MED, link-local addresses)7.3.2. Custom route advertisements via BGP7.3.3. Deploying reliable and redundant Cloud Routers8. Managing network operations8.1. Logging and monitoring with Google Cloud’s operations suite8.1.1. Reviewing logs for networking components (e.g., VPN, Cloud Router, VPC Service Controls)8.2. Monitoring networking components (e.g., VPN, Cloud Interconnect connections and interconnect attachments, Cloud Router, load balancers, Google Cloud Armor, Cloud NAT)8.3. Managing and maintaining security8.4. Firewalls (e.g., cloud-based, private)8.5. Diagnosing and resolving IAM issues (e.g., Shared VPC, security/network admin)8.6. Maintaining and troubleshooting connectivity issues8.6.1. Draining and redirecting traffic flows with HTTP(S) Load Balancing8.6.2. Monitoring ingress and egress traffic using VPC Flow Logs8.6.3. Monitoring firewall logs and Firewall Insights8.6.4. Managing and troubleshooting VPNs8.6.5. Troubleshooting Cloud Router BGP peering issues8.7. Monitoring, maintaining, and troubleshooting latency and traffic flow8.8. Testing network throughput and latency8.9. Diagnosing routing issues8.10. Using Network Intelligence Center to visualize topology, test connectivity, and monitor performance

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Book SynopsisThis book provides Kafka administrators, site reliability engineers, and DataOps and DevOps practitioners with a list of real production issues that can occur in Kafka clusters and how to solve them. The production issues covered are assembled into a comprehensive troubleshooting guide for those engineers who are responsible for the stability and performance of Kafka clusters in production, whether those clusters are deployed in the cloud or on-premises. This book teaches you how to detect and troubleshoot the issues, and eventually how to prevent them. Kafka stability is hard to achieve, especially in high throughput environments, and the purpose of this book is not only to make troubleshooting easier, but also to prevent production issues from occurring in the first place. The guidance in this book is drawn from the author's years of experience in helping clients and internal customers diagnose and resolve knotty production problems and stabilize their Kafka environments. The book Table of Contents

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Book SynopsisLearn how to use Google Cloud Platform (GCP) and its services to design, build, and deploy applications. This book includes best practices, practical examples, and code snippets written in Java, making it a key resource for developers seeking hands-on experience with GCP.You'll begin with an introduction to GCP services and a review of what Java offers while developing applications for GCP. Next, you'll be walked through how to set up Google App Engine, Google Storage Cloud, and Google Cloud SQL with use cases, as well as application development and deployment. As the book progresses, you'll be exposed to advanced GCP services, deploying and scaling applications on GCP services, and troubleshooting and optimization of Java applications on GCP. The book uses real-world examples to help you understand how GCP services can solve everyday problems. After completing this book, you will understand Google Cloud Platform and its services, and will have the knowledge needed to design, build, Table of ContentsChapter 1: Introduction to Google Cloud Platform.- Chapter 2: Setting up the Development Environment.- Chapter 3: Google App Engine.- Chapter 4: Data Storage in Google Cloud.- 5: Google Cloud SQL.- Chapter 6: Advanced GCP Services.- Chapter 7: Deployment and Scaling.- Chapter 8: Troubleshooting and Optimization.- Chapter 9: Conclusion.

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Book SynopsisSalesforce Field Service (formerly Field Service Lightning) connects customers, workforce, and products on a single platform to deliver exceptional on-site services. This book guides Field Service enthusiasts in creating, managing, and automating support with use cases and real-time examples. You will learn Salesforce Field Service which will help you better manage your customers, internal users, and field technicians. As you advance, you'll learn the whole end-to-end life cycle of creating work orders, associating service appointments to work orders, scheduling and dispatching service appointments to field technicians, and completing the work orders. By the end of this book, you'll be able to implement, test and deploy Salesforce Field Service for both Desktop and Mobile apps. What you'll learn Basics of Field Service Field Service objects and data model Field Service schedulingand optimization Configuring Salesforce Field Service Managing Salesforce Field ServiceTable of ContentsChapter 1: Intro to Salesforce Field Service · Basics of Field Service and Field Service Life Cycle · Field Service Personas, Objects and Data Model · Common Field Service Terminology · How Salesforce can help build Field Service and understanding Salesforce Licenses Chapter 2: Step by Step Field Service Implementation · Installing Field Service Managed App Exchange Package · Using Field Service Guided Setup · Using Dispatcher Console for dispatching Service Appointments Chapter 3: Extending Field Service to Mobile · Configuring Field Service Mobile App · How Field Technicians use Mobile App Chapter 4: Reporting in Field Service · Configure Reports and Dashboards to understand Field Service performance Chapter 5: Cracking Salesforce Field Service Lightning Certification · Understanding exam outline, key tips and strategies

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Book SynopsisThis book is a comprehensive guide covering modern cloud strategies and leadership approaches for building and scaling organizations to maturity on their cloud adoption journey. The book starts by examining technical topics from the perspective of the cloud leader, who is responsible for cloud teams and accountable for cloud products and platforms within their organization. Through a series of practical insights and real-world examples, you will gain a deep understanding of the key considerations for leading a cloud-driven organization. These considerations include understanding the benefits of digital transformation, managing global tech teams, and delivering excellence through platform ownership. Towards the end of the book, you will explore the latest trends and best practices for strategically innovating and scaling your organization in the cloud. With the knowledge gained from this book, you will be able to harness the poTable of Contents​ Part I: Leadership Essentials.- 1. The Art of Cloud Leadership.- 2. Influencing Change and Driving Cloud Adoption.- 3. Managing Teams in the Digital Age.- 4. Supporting Employee Health & Turnover.- Part II: Innovation Strategies.- 5. Adopting a Cloud Platform.- 6. Democratizing Data & Democratizing Analytics.- 7. Applying DevOps.- 8. New Horizons in Distributed Cloud Computing.- 9. Impacts of Modern AI and ML Trends.- Part III: Platform Ownership.- 10. Owning a Portfolio of Agile Cloud Products.- 11.Designing a Secure Data Lake.- 12. Administering and Auditing the Cloud.- 13. Collaborating with Cloud Vendors and Providers.- Part IV: Delivery Excellence.- 14. Creating a Technology Delivery Roadmap.- 15. Cloud Transformation Roles and Responsibilities.- 16. Delivering Strategic Cloud Innovation and Excellence.- 17. Managing Agile Cloud Projects.- 18. Achieving Digital Transformation Success.

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Book SynopsisLearn how to deploy information assurance risk management strategies that align with the National Institute of Standards and Technology's recommendations. This book will show you how to implement information assurance risk management strategies within your organization.Aimed at system administrators and cybersecurity practitioners, author Bradley Fowler first walks you through how to assess known risks in your organization, understand why using a risk mitigation security strategy control profile is essential, and how to create one for your organization. You will then learn how to develop a risk factor table, outlining descriptions for each risk factor within your organization and which software applications you'll need to rely on for daily business communication and operations. You will also see how to assess and categorize the level of risk within each technology tool, as well as the impact of an information security breach on the organization.As you progress through the book, you'll Table of Contents

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Book SynopsisThis book will show you how to build Java-based microservices architecture using the popular Spring Boot framework by evolving a small monolith application to an event-driven architecture composed of several services. This third edition has been updated to cover Spring Boot 3, including its compatibility with Java 17 and Jakarta EE 10, and employs an incremental approach to teach the structure of microservices, test-driven development, and common patterns in distributed systems such as service discovery, load balancing, routing, centralized logs, per-environment configuration, and containerization. Authors Moisés Macero and Tarun Telang get the ball rolling by introducing you to the fundamentals of microservices and Spring Boot before walking you through the development of a basic Spring Boot application. You'll then see how to build a front end using React, and learn how to use the data layer to read and write data from and to other systems via Spring Boot and its access to Spring DTable of Contents

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Book SynopsisGet valuable tips and techniques for automating your cloud deployments with Azure PowerShell cmdlets, and learn how to provision Azure services on the fly. In this hands-on guide, Microsoft cloud technology expert Michael Washam shows you how to automate various management tasks and deploy solutions that are both complex and at scale.

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Book SynopsisFor many organizations, a big part of DevOps' appeal is software automation using infrastructure-as-code techniques. This book presents developers, architects, and infra-ops engineers with a more practical option.

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Book SynopsisThis practical hands-on guide examines effective architecture, design, and cultural patterns to help you transform your organization into a cloud native enterprisewhether you're moving from older architectures or creating new systems from scratch..

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Book SynopsisWith cloud providers running servers and managing machine resources, companies now can focus solely on the application's business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure.

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Book SynopsisThis practical book shows data scientists, data engineers, and platform architects how to plan and execute a Kubeflow project to make their Kubernetes workflows portable and scalable.

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Book SynopsisWant to run your Kubernetes workloads safely and securely? This practical book provides a threat-based guide to Kubernetes security. Authors Andrew Martin and Michael Hausenblas share best-practice configuration to help you harden clusters from possible angles of attack.

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Book SynopsisWith this practical book, new and experienced developers and operators will learn specific techniques and examples for operationalizing OpenShift and Kubernetes in the enterprise.

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Book SynopsisThis practical book shows you how to build a true cloud native infrastructure on Microsoft Azure, following guidelines from the Cloud Native Computing Foundation (CNCF).

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Book SynopsisThis practical guide provides over 70 self-contained recipes to help you creatively solve common AWS challenges you'll encounter on your cloud journey. If you're comfortable with rudimentary scripting and general cloud concepts, this cookbook provides what you need to address foundational tasks and create high-level capabilities.

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Book SynopsisWhether you're looking for practical ways to apply microservices, AI, analytics, security, or networking solutions, these recipes take you step-by-step through the process and provide discussions that explain how and why the recipes work.

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Book SynopsisWith this practical, developer-oriented book, DevOps engineers, developers, IT architects, and SREs will learn the most useful recipes and examples for following GitOps practices.

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Book SynopsisIf you're tasked with designing, delivering, or approving IT systems that support business growth, this book will teach you the principles and strategies you need to break out of silos, reassess traditional thinking, provide the business a better competitive position, and achieve cloud success across the company.

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Book SynopsisWith this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage.

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Book SynopsisPreparing for your SAP Extension Suite development associate exam? Make the grade with this certification study guide! From user interfaces to security, this guide will review the key technical knowledge you need to pass the test. Explore test methodology, key concepts for each topic area, and practice questions and answers. Your path to SAP Extension Suite certification begins here! Highlights include: 1) Exam C_CPE_13 2) SAP S/4HANA 3) SAP Extension Suite 4) SAP Integration Suite 5) SAP API Business Hub 6) SAP Business Application Studio 7) SAP Business Technology Platform (SAP BTP) 8) SAP Fiori 9) APIs 10) Continuous integration and continuous delivery (CI/CD) 11) Extensibility 12) Security

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Book SynopsisTransform your datacenter for breakthrough flexibility, agility, and scalability! Using public, private, and hybrid cloud services, you can transform your datacenter to serve fast-changing workloads, process and analyze enormous amounts of data, and achieve unprecedented flexibility and value. In this guide, two world-renowned experts in Microsoft datacenter technology show how to effectively leverage current legacy systems as you incorporate your optimal mix of cloud services. Drawing on extensive experience implementing Microsoft cloud solutions, they walk you step-by-step through your entire transition: strategy, deployment, security, identity protection, management, PowerShell automation, and more. Two concluding chapters offer indispensable advice for maximizing datacenter efficiency and supporting future innovation. Two leading enterprise cloud and Windows Server experts show how to: Move from legacy IT models to an agile service structure Implement managed self-service, iteration-based software updates, immutable infrastructure, and other elements of a modern IT environment Plan and smoothly integrate on-premises, Azure, Azure Stack, and Hybrid Cloud components Fortify IT security now and in the future Safeguard identities via new models and tools, including Remote Credential Guard Protect the OS, on premises and in the cloud Optimize datacenter efficiency via enterprise-class virtualization and other advanced technologies Promote innovation via microservices, DevOps, and NanoServer containerization Table of Contents1. Introduction: This book is for you... 2. Modern IT-the coming inflection point 3. Azure and the Azure Stack 4. Upping your security game 5. Application migration 6. Delivering datacenter efficiency 7. Supporting Innovation

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Book SynopsisCloud computing enables on-demand access to shared computing resources providing services more quickly and at a lower cost than having agencies maintain these resources themselves. Chapter 1 discusses selected agencies' progress in implementing cloud services, the extent to which those agencies increased cloud service spending and achieved savings or cost avoidances, and examples of agency-reported cloud investments with notable benefits. The Office of Management and Budget (OMB) has developed a new strategy to accelerate agency adoption of cloud-based solutions: Cloud Smart. Chapter 2 reports on the strategy of successful cloud adoption: security, procurement, and workforce. The Department of Defense (DoD) has entered the modern age of warfighting where the battlefield exists as much in the digital world as it does in the physical. Cloud is a fundamental component of the global infrastructure that will empower the warfighter with data and is critical to maintaining our military's technological advantage as reported in chapter 3. Chapter 4 discusses accelerated adoption of the Joint Enterprise Defense Infrastructure (JEDI) Cloud program. In the Clarifying Lawful Overseas Use of Data (CLOUD) Act, Congress enacted one of the first major changes in years to U.S. law governing cross-border access to electronic communications held by private companies. Chapter 5 reports on the major components of the CLOUD Act. Chapter 6 discusses United States v. Microsoft Corp as it pertains to the CLOUD Act.Table of ContentsPrefaceCloud Computing: Agencies Have Increased Usage and Realized Benefits, but Cost and Savings Data Need to Be Better TrackedFederal Cloud Computing StrategyDoD Cloud StrategyThe DoDs JEDI Cloud ProgramCross-Border Data Sharing Under the CLOUD ActSupreme Court to Hear Digital Privacy Case: Can the Government Obtain Emails Stored Abroad?Index.

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Book SynopsisThe “servicemesh” pattern, implemented by platforms like Istio, helps you push operational issues into the infrastructure so the application code is easier to understand, maintain, and adapt. Istio in Action teaches you how to implement a full-featured Istio-based service mesh to manage a microservices application. Istio in Action is a comprehensive guide to handling authentication, routing, retrying, load balancing, collecting data, security, and other common network-related tasks using the Istio service mesh platform. With helpful diagrams and hands-on examples, you'll learn how to use this open-source service mesh to control routing, secure container applications, and monitor network traffic. You will also bring Istio to legacy systems without changes to your applications and discover how to use Istio in amulti-cloud world with the data layer deployed on a cluster like Kubernetes. Cloud-native applications can include thousands of clustered containers, distributed components, and complex interactions. To build them effectively, developers need a new approach to infrastructural concerns like monitoring, storage, scaling, orchestration, and security. The Istio platform offers a configurable infrastructure layer called a service mesh that reliably and efficiently manages day-to-day concerns like service discovery, load balancing, encryption, authentication and authorization, circuit breakers, and more. Open source andcloud-ready, Istio is a welcome upgrade from manually managed microservices infrastructure.Trade Review“The definitive guide to understand Istio and when it's worthusing it.” Andrea Cosentino “If you are looking for how to setup and use Istio, this is thebook for you.” Michael J. Haller “The perfect blend of how and why.” Morgan Nelson “Istio: how to use it, when to use it, what it is, and most importantly, what it is not.” Andrea Tarocchi “Provides detailed information on an exciting technology with aton of real-world examples. The authors walk readers through a difficult subject with ease. Highly recommended.” Morgan Nelson “A thorough treatment of Istio with excellent examples you can reproduce. I learnt a lot about Service Mesh, its "raison d'etre",and Istio's capabilities. Excellent resource!” Michael Bright

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Book SynopsisAzure Data Engineering teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system. Readers should be comfortable with RDBMS systems like SQL Server and scripting using a language like PowerShell, Bash, or Python. Book examples use PowerShell and C#. The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage. The Microsoft Azure cloud platform can host virtually any sort of computing task, from simple web applications to full-scale enterprise systems. With many pre-built services for everything from data storage to advanced machine learning, Azure offers all the building blocks for scalable big data analysis systems including ingestion, processing, querying, and migration. • Azure cloud services architecture • Building a data warehouse in Azure • How to choose the right Azure technology for your task • Calculating fixed and variable costs • Hot and cold path analytics Richard Nuckolls is a senior developer building a big data analytics and reporting system in Azure. During his nearly 20 years of experience, he’s done server and database administration, desktop and web development, and more recently has led teams in building a production content management system in Azure.

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Book SynopsisTerraform is a provisioning tool for building, changing, and combining cloud infrastructure safely and efficiently. By defining infrastructure as code, Terraform empowers its users to deploy their entire stack to the cloud at the touch of a button. • Cloud architecture with Terraform • Sharing Terraform modules and the private module registry • Running Terraform securely in a multitenant environment • Strategies for performing Blue/Green deployments with Terraform By treating your infrastructure as a codeable application, you can instantaneously create and launch new components and respond efficiently to changes in demand and other use requirements. Terraform in Action introduces the Infrastructure-as-Code model using the amazing Terraform automation tool, teaching readers how to design and manage servers that can be provisioned, shared, changed, tested, and deployed at the touch of a button. Readers will unlock the full potential of Terraform to manage your infrastructure as easily as they manage their codebase. Written for readers experienced with major cloud platforms such as AWS or Google Cloud. Examples are in the Go language.

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Book SynopsisFrom its humble beginnings a container orchestration system, Kubernetes has become the de facto infrastructure for cloud native applications. Kubernetes impacts every aspect of the application development lifecycle, from design through deployment. To build and operate reliable cloud native systems, you need to understand what's going on below the surface. Core Kubernetes is packed with experience-driven insights and practical techniques, and takes you inside Kubernetes to teach you what you'll need to know to keep your system running like a well-oiled machine and prevent those panicked 3 AM phone calls. about the technologyKubernetes is a platform-independent layer for deploying scalable container-based applications. Kubernetes provides abstractions for clustering, replicating, and scaling system components in real time. It's especially well-suited for microservices applications, where you can easily balance the load among services. Kubernetes has become a core component of cloud native applications, and all major cloud vendors now offer hosted versions of Kubernetes. Kubernetes was initially developed by Google and is now governed as an open source project by the Cloud Native Computing Foundation (CNCF). about the bookCore Kubernetes is a reference guide designed to teach operators, SREs, and developers how to improve reliability and performance of Kubernetes-based systems. In it, Kubernetes experts Chris Love and Jay Vyas provide a guided tour through all major aspects of Kubernetes, from managing iptables to setting up dynamically scaled clusters that respond to changes in load. You'll understand the unique security concerns of container-based applications, discover tips to minimize costly unused capacity, and get pro tips for maximizing performance. This awesome collection of undocumented internals, expert techniques, and practical guidance has invaluable information you won't find anywhere else. what's inside- Kubernetes base components- Kubernetes networking- Storage and the Container Storage Interface- External load balancing and ingress- Kubernetes security- Different ways of creating a Kubernetes cluster- Configuring Kubernetes to use a GPU about the readerWritten for readers with a working knowledge of Kubernetes and microservices applications. about the authorAfter earning his PhD, Jay Vyas started his career contributing to Kubernetes' core features at RedHat, and next, he focused on helping multiple companies migrate to Cloud-Native solutions. He now resides at VMWare, once again contributing to Kubernetes and associated projects. When not coding, Jay likes to play with his video games, his synthesizers, and hang out in his Pod. As a thought leader in the Kubernetes and DevOps segment, Chris Love is a founder of multiple technology companies with over 20 years' experience in software engineering. A Google Cloud Certified Fellow, Chris has contributed to several open-source projects including Kubernetes, Bazel, and Terraform. He enjoys speaking around the world about DevOps and Kubernetes and practices martial arts in his free time.

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