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.

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.

Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES ● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML. ● Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS. ● Includes ready-made, purpose-built models as AI services and proven methods to adopt MLOps techniques. DESCRIPTION Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation. In this book, you'll learn how to build data lakes, build and train machine learning models, automate MLOps, ensure maximum data reusability and reproducibility, and much more. The applications presented in the book show how to make the most of several different AWS offerings, including Amazon Comprehend, Amazon Rekognition, Amazon Lookout, and AutoML. This book teaches you to manage massive data lakes, train artificial intelligence models, release these applications into production, and track their progress in real-time. You will learn how to use the pre-trained models for various tasks, including picture recognition, automated data extraction, image/video detection, and anomaly detection. Every step of your Machine Learning and AI project's development process is optimised throughout the book by utilising Amazon's pre-made, purpose-built AI services. WHAT YOU WILL LEARN ● Learn how to build, deploy, and manage large-scale AI and ML applications on AWS. ● Get your hands dirty with AWS AI services like SageMaker, Comprehend, Rekognition, Lookout, and AutoML. ● Master data transformation, feature engineering, and model training with Amazon SageMaker modules. ● Use neural networks, distributed learning, and deep learning algorithms to improve ML models. ● Use AutoML, SageMaker Canvas, and Autopilot for Model Deployment and Evaluation. ● Acquire expertise with Amazon SageMaker Studio, Jupyter Server, and ML frameworks such as TensorFlow and MXNet. WHO THIS BOOK IS FOR Data Engineers, Data Scientists, AWS and Cloud Professionals who are comfortable with machine learning and the fundamentals of Python will find this book powerful. Familiarity with AWS would be helpful but is not required. TABLE OF CONTENTS 1. Introducing the ML Workflow 2. Hydrating the Data Lake 3. Predicting the Future With Features 4. Orchestrating the Data Continuum 5. Casting a Deeper Net (Algorithms and Neural Networks) 6. Iteration Makes Intelligence (Model Training and Tuning) 7. Let George Take Over (AutoML in Action) 8. Blue or Green (Model Deployment Strategies) 9. Wisdom at Scale with Elastic Inference 10. Adding Intelligence with Sensory Cognition 11. AI for Industrial Automation 12. Operationalized Model Assembly (MLOps and Best Practices)

Gain the expertise needed for the Google Cloud Digital Leader certification with the help of industry insights, effective testing strategies, and exam questions designed to help you make informed tech decisions aligned with business goals Key Features Learn about data management, AI, monetization, security, and the significance of infrastructure modernization Build a solid foundation in Google Cloud, covering all technical essentials necessary for a Google Cloud Digital Leader Test your knowledge of cloud and digital transformation through realistic exam questions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTo thrive in today's world, leaders and technologists must understand how technology shapes businesses. As organizations shift from self-hosted to cloud-native solutions, embracing serverless systems, strategizing data use, and defining monetization becomes imperative. The Google Cloud Digital Leader Certification Guide lays a solid foundation of industry knowledge, focused on the Google Cloud platform and the innovative ways in which customers leverage its technologies. The book starts by helping you grasp the essence of digital transformation within the Google Cloud context. You’ll then cover core components of the platform, such as infrastructure and application modernization, data innovation, and best practices for environment management and security. With a series of practice exam questions included, this book ensures that you build comprehensive knowledge and prepare to certify as a Google Cloud Digital Leader. Going beyond the exam essentials, you’ll also explore how companies are modernizing infrastructure, data ecosystems, and teams in order to capitalize on new market opportunities through platform expertise, best practices, and real-world scenarios. By the end of this book, you'll have learned everything you need to pass the Google Cloud Digital Leader certification exam and have a reference guide for future requirements.What you will learn Leverage Google Cloud’s AI and ML solutions to create business value Identify Google Cloud solutions for data management and smart analytics Acquire the skills necessary to modernize infrastructure and applications on GCP Understand the value of APIs and their applications in cloud environments Master financial governance and implement best practices for cost management Understand the cloud security approach and benefits of Google Cloud security Find out how IT operations must adapt to thrive in the cloud Who this book is for This Google Cloud fundamentals book is suitable for individuals with both technical and non-technical backgrounds looking for a starting point to pursue more advanced Google Cloud certifications. No prior experience is required to get started with this book; only a keen interest in learning and exploring cloud concepts, with a focus on Google Cloud.

Discover how Google Cloud services can help you to reduce operational tasks and focus on delivering business value with your applications Key FeaturesDesign, develop, and deploy end-to-end cloud-native applications using Google Cloud servicesPrepare for the GCP developer exam with the help of a fictitious business case and a Q&A sectionGet hands-on with implementing code examples of different GCP services in your applicationsBook Description Google Cloud Platform is one of the three major cloud providers in the industry, exhibiting great leadership in application modernization and data management. This book provides a comprehensive introduction for those who are new to cloud development and shows you how to use the tools to create cloud-native applications by integrating the technologies used by Google. The book starts by taking you through the basic programming concepts and security fundamentals necessary for developing in Google Cloud. You'll then discover best practices for developing and deploying applications in the cloud using different components offered by Google Cloud Platform such as Cloud Functions, Google App Engine, Cloud Run, and other GCP technologies. As you advance, you'll learn the basics of cloud storage and choosing the best options for storing different kinds of data as well as understand what site reliability engineers do. In the last part, you'll work on a sample case study of Hip Local, a community application designed to facilitate communication between people nearby, created by the Google Cloud team. By the end of this guide, you'll have learned how to design, develop, and deploy an end-to-end application on the Google Cloud Platform. What you will learnGet to grips with the fundamentals of Google Cloud Platform developmentDiscover security best practices for applications in the cloudFind ways to create and modernize legacy applicationsUnderstand how to manage data and databases in Google CloudExplore best practices for site reliability engineering, monitoring, logging, and debuggingBecome well-versed with the practical implementation of GCP with the help of a case studyWho this book is for This book is for cloud engineers or developers working or starting to work on Google Cloud Platform and looking to take advantage of cloud-native applications. You'll also find this book useful if you are preparing for the GCP developer exam.

Get the knowledge and skills you need to become a certified Google Cloud Developer KEY FEATURES ● Learn everything you need to know about the Google Professional Cloud Developer exam and its objectives. ● Explore the different services GCP offers, such as Compute Engine, Cloud Storage, and Cloud SQL. ● Test your knowledge and prepare for the exam with practice exercises and quizzes. DESCRIPTION The Google Professional Cloud Developer Exam Guide is a comprehensive study guide for the Google Professional Cloud Developer exam. It covers all the topics you need to master to design, develop, deploy, and manage cloud-native applications on Google Cloud Platform (GCP). The book starts with an introduction to the certification and the skills and knowledge you need to pass the exam. Then, it covers the different development environments for GCP development, the most important GCP products and services, and the principles of designing high-performance and secure applications. The book also covers designing and building cloud-native applications, different application deployment strategies, and how to deploy apps and services on GCP. It also shows how to integrate applications with GCP services and how to monitor and manage app workloads. To help you prepare for the exam, the book ends with a chapter of quiz solutions. Overall, this book is a great resource for anyone preparing for the Google Professional Cloud Developer exam. WHAT YOU WILL LEARN ● Learn about the basics of cloud computing, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). ● Learn about serverless architectures and how to use them to build scalable and reliable applications. ● Learn how to debug and profile code to improve its performance and reliability. ● Learn about source control management and how to use it to track changes to code. ● Learn about performance testing and how to use it to ensure that applications meet their performance requirements. ● Learn about service-level agreements (SLAs), service-level objectives (SLOs), and service-level indicators (SLIs) and how to use them to measure the performance of applications. WHO THIS BOOK IS FOR This book is for software engineers, developers, and IT professionals who want to learn about cloud computing and how to develop and deploy applications on Google Cloud Platform. Readers should have a basic understanding of programming and cloud computing concepts. TABLE OF CONTENTS 1. The Professional Cloud Developer 2. Development Environments 3. GCP Products and Services 4. Designing High-performance Applications 5. Designing and Managing Secure Applications 6. Writing and Building Cloud-native Applications 7. Application Deployment Strategies 8. Deploying Apps and Services 9. Integrating Applications with GCP Services 10. Monitoring and Managing App Workloads 11. Answers to Quizzes