SQL Server on Kubernetes
Build a modern data platform by deploying SQL Server in Kubernetes. Modern application deployment needs to be fast and consistent to keep up with business objectives and Kubernetes is quickly becoming the standard for deploying container-based applications, fast. This book introduces Kubernetes and its core concepts. Then it shows you how to build and interact with a Kubernetes cluster. Next, it goes deep into deploying and operationalizing SQL Server in Kubernetes, both on premises and in cloud environments such as the Azure Cloud. You will begin with container-based application fundamentals and then go into an architectural overview of a Kubernetes container and how it manages application state. Then you will learn the hands-on skill of building a production-ready cluster. With your cluster up and running, you will learn how to interact with your cluster and perform common administrative tasks. Once you can admin the cluster, you will learn how to deploy applications and SQL Serve ...
Build a modern data platform by deploying SQL Server in Kubernetes. Modern application deployment needs to be fast and consistent to keep up with business objectives and Kubernetes is quickly becoming the standard for deploying container-based applications, fast. This book introduces Kubernetes and its core concepts. Then it shows you how to build and interact with a Kubernetes cluster. Next, it goes deep into deploying and operationalizing SQL Server in Kubernetes, both on premises and in cloud environments such as the Azure Cloud. You will begin with container-based application fundamentals and then go into an architectural overview of a Kubernetes container and how it manages application state. Then you will learn the hands-on skill of building a production-ready cluster. With your cluster up and running, you will learn how to interact with your cluster and perform common administrative tasks. Once you can admin the cluster, you will learn how to deploy applications and SQL Serve ...
AI and Machine Learning for On-Device Development
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android. Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today. Explore the options for implementing ML and AI on mobile devices; Create ML models for iOS and Android; Write ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOS; Choose the best techniques and tools for your use case, such as cloud-based versus on-device infere ...
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android. Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and tools, then walks you through writing Android and iOS apps powered by common ML models like computer vision and text recognition, using tools such as ML Kit, TensorFlow Lite, and Core ML. If you're a mobile developer, this book will help you take advantage of the ML revolution today. Explore the options for implementing ML and AI on mobile devices; Create ML models for iOS and Android; Write ML Kit and TensorFlow Lite apps for iOS and Android, and Core ML/Create ML apps for iOS; Choose the best techniques and tools for your use case, such as cloud-based versus on-device infere ...
Just Enough R
If your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer. However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory. If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...
If your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer. However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory. If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...
Data Engineering on Azure
Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft's own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. In Data Engineering on Azure you'll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, p ...
Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft's own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. In Data Engineering on Azure you'll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, p ...
App Modernization on Azure Succinctly
What's the right way to move existing applications to the cloud to better use its power while enabling new features? In App Modernization on Azure Succinctly, Lorenzo Barbieri will help you understand how to modernize existing apps without completely rewriting them. This ebook will guide you through moving your app to the cloud, refactoring, rearchitecting, and choosing which cloud services will improve your app and experience. Most of the concepts in this book are also valid for a complete rewrite of an app directly in the cloud, or new apps built directly in the cloud. ...
What's the right way to move existing applications to the cloud to better use its power while enabling new features? In App Modernization on Azure Succinctly, Lorenzo Barbieri will help you understand how to modernize existing apps without completely rewriting them. This ebook will guide you through moving your app to the cloud, refactoring, rearchitecting, and choosing which cloud services will improve your app and experience. Most of the concepts in this book are also valid for a complete rewrite of an app directly in the cloud, or new apps built directly in the cloud. ...
Systematic Cloud Migration
This book is your systematic cloud migration guide. Experiences shared by the author are drawn from real-life migration projects and contain practical advice, as well as step-by-step architecture, design, and technical implementation instructions using sample application code on GitLab. Following the guidance in this book will provide much needed support to your teams, and help you successfully complete the application cloud migration journey. Systematic Cloud Migration consists of four major parts. Part one starts with a fundamental introduction of cloud computing to establish the context for migration, including paradigm changes in five important areas: software application, DevSecOps, operations, infrastructure, and security. And these are the areas that the book follows throughout. Next, it introduces a real-life migration process that your team can follow. Part two presents the migration process for the application code, including architecture diagrams and presented by demo ...
This book is your systematic cloud migration guide. Experiences shared by the author are drawn from real-life migration projects and contain practical advice, as well as step-by-step architecture, design, and technical implementation instructions using sample application code on GitLab. Following the guidance in this book will provide much needed support to your teams, and help you successfully complete the application cloud migration journey. Systematic Cloud Migration consists of four major parts. Part one starts with a fundamental introduction of cloud computing to establish the context for migration, including paradigm changes in five important areas: software application, DevSecOps, operations, infrastructure, and security. And these are the areas that the book follows throughout. Next, it introduces a real-life migration process that your team can follow. Part two presents the migration process for the application code, including architecture diagrams and presented by demo ...
Pro Java Microservices with Quarkus and Kubernetes
Build and design microservices using Java and the Red Hat Quarkus Framework. This book will help you quickly get started with the features and concerns of a microservices architecture. It will introduce Docker and Kubernetes to help you deploy your microservices. You will be guided on how to install the appropriate tools to work properly. For those who are new to enterprise development using Quarkus, you will be introduced to its core principles and main features through a deep step-by-step tutorial. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes. By the end of reading this book, you will have practical hands-on experience of building microservices using Quarkus and you will master deploying them to Kubernetes. ...
Build and design microservices using Java and the Red Hat Quarkus Framework. This book will help you quickly get started with the features and concerns of a microservices architecture. It will introduce Docker and Kubernetes to help you deploy your microservices. You will be guided on how to install the appropriate tools to work properly. For those who are new to enterprise development using Quarkus, you will be introduced to its core principles and main features through a deep step-by-step tutorial. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes. By the end of reading this book, you will have practical hands-on experience of building microservices using Quarkus and you will master deploying them to Kubernetes. ...
AWS Cookbook
This 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. Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further. Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you: Redact personal identifiable information (PII) from text using Ama ...
This 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. Authors John Culkin and Mike Zazon share real-world examples that incorporate best practices. Each recipe includes a diagram to visualize the components. Code is provided so that you can safely execute in an AWS account to ensure solutions work as described. From there, you can customize the code to help construct an application or fix an existing problem. Each recipe also includes a discussion to provide context, explain the approach, and challenge you to explore the possibilities further. Go beyond theory and learn the details you need to successfully build on AWS. The recipes help you: Redact personal identifiable information (PII) from text using Ama ...
Ethical Hacking
Ethical Hacking is a crash course in modern hacking techniques. It's already being used to prepare the next generation of offensive security experts. In its many hands-on labs, you'll explore crucial skills for any aspiring penetration tester, security researcher, or malware analyst. You'll begin with the basics: capturing a victim's network traffic with an ARP spoofing attack and then viewing it in Wireshark. From there, you'll deploy reverse shells that let you remotely run commands on a victim's computer, encrypt files by writing your own ransomware in Python, and fake emails like the ones used in phishing attacks. In advanced chapters, you'll learn how to fuzz for new vulnerabilities, craft trojans and rootkits, exploit websites with SQL injection, and escalate your privileges to extract credentials, which you'll use to traverse a private network. You'll work with a wide range of professional penetration testing tools - and learn to write your own tools in Python - as you pra ...
Ethical Hacking is a crash course in modern hacking techniques. It's already being used to prepare the next generation of offensive security experts. In its many hands-on labs, you'll explore crucial skills for any aspiring penetration tester, security researcher, or malware analyst. You'll begin with the basics: capturing a victim's network traffic with an ARP spoofing attack and then viewing it in Wireshark. From there, you'll deploy reverse shells that let you remotely run commands on a victim's computer, encrypt files by writing your own ransomware in Python, and fake emails like the ones used in phishing attacks. In advanced chapters, you'll learn how to fuzz for new vulnerabilities, craft trojans and rootkits, exploit websites with SQL injection, and escalate your privileges to extract credentials, which you'll use to traverse a private network. You'll work with a wide range of professional penetration testing tools - and learn to write your own tools in Python - as you pra ...
Data Science on the Google Cloud Platform, 2nd Edition
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud; Automate and schedule data ingest using Cloud Run; Create and populate a dashboard in Data Studio; Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery; Conduct interactive data exploration with BigQuery; Create a Bayesian model with Spark on Cloud Dataproc; Fore ...
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. Throughout this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud; Automate and schedule data ingest using Cloud Run; Create and populate a dashboard in Data Studio; Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery; Conduct interactive data exploration with BigQuery; Create a Bayesian model with Spark on Cloud Dataproc; Fore ...