This book covers topics related to creating Java microservices and deploy them to Kubernetes and OpenShift.
Traditionally, Java developers have been used to developing large, complex monolithic applications. The experience of developing and deploying monoliths has been always slow and painful. This book will help Java developers to quickly get started with the features and the concerns of the microservices architecture. It will introduce Docker, Kubernetes and OpenShift to help them deploying their microservices.
The book is written for Java developers who wants to build microservices using the Spring Boot/Cloud stack and who wants to deploy them to Kubernetes and OpenShift.
You will be guided on how to install the appropriate tools to work properly. For those who are new to Enterprise Development using Spring Boot, you will be introduced to its core principles and main features thru a deep step-by-step tutorial on many components. For experts, this book offers some recipes that illustrate how to split monoliths and implement microservices and deploy them as containers to Kubernetes and OpenShift.
The following are some of the key challenges that we will address in this book:
- Introducing Spring Boot/Cloud for beginners
- Splitting a monolith using the Domain Driven Design approach
- Implementing the cloud & microservices patterns
- Rethinking the deployment process
- Introducing containerization, Docker, Kubernetes and OpenShift
By the end of reading this book, you will have practical hands-on experience of building microservices using Spring Boot/Cloud and you will master deploying them as containers to Kubernetes and OpenShift.
Nebrass is a passionate Java developer, Apache NetBeans Committer since January 2018 and a former NetBeans Dream Team member until December 2017.
He is also working as a Project Leader in the OWASP Foundation, since March 2013, on the Barbarus Project.
He is the author of the books
- Playing with Java Microservices on Kubernetes and OpenShift published with Leanpub on November 2018.
- Pairing Apache Shiro with Java EE 7 published with InfoQ on May 2016.
Nebrass is graduated with a M.Sc Degree in Information Systems Security and a Bachelor's Degree in Management & Computing sciences from the Higher Institute of Management of Tunis, Tunisia.
Over the past 7 years, he has been working on Java SE/EE projects, in many sectors, including Business Management, Petroleum, Finance & Banking, Medical & healthcare, and Defence & Space. He has developed applications using many frameworks and Java-related technologies, such as native Java EE APIs and 3rd-party frameworks & tools (Spring, Hibernate, Primefaces, JBoss Forge). He has been managing and using infrastructure and programming tools such as DBMS, Java EE servers (Glassfish and JBoss), Quality & Continuous integration tools (Sonar, Jenkins, and Husdon), Docker & Kubernetes & Openshift.
The CISSP certification is the most prestigious, globally-recognized, vendor neutral exam for information security professionals. Over 100,000 professionals are certified worldwide, with many more joining their ranks. This new third edition is aligned to cover all of the material in the most current version of the exam’s Common Body of Knowledge. All domains are covered as completely and concisely as possible, giving users the best possible chance of acing the exam.Completely updated for the most current version of the exam’s Common Body of KnowledgeProvides the only guide you need for last-minute studyingAnswers the toughest questions and highlights core topicsStreamlined for maximum efficiency of study, making it ideal for professionals updating their certification or for those taking the test for the first time
Each chapter contains hands-on examples and exercises that are designed to teach learners how to interpret results and utilize those results in later phases. Tool coverage includes: Backtrack Linux, Google reconnaissance, MetaGooFil, dig, Nmap, Nessus, Metasploit, Fast Track Autopwn, Netcat, and Hacker Defender rootkit. This is complemented by PowerPoint slides for use in class.
This book is an ideal resource for security consultants, beginning InfoSec professionals, and students.Each chapter contains hands-on examples and exercises that are designed to teach you how to interpret the results and utilize those results in later phases.Written by an author who works in the field as a Penetration Tester and who teaches Offensive Security, Penetration Testing, and Ethical Hacking, and Exploitation classes at Dakota State University.Utilizes the Kali Linux distribution and focuses on the seminal tools required to complete a penetration test.
Aspiring digital businesses need overall IT agility, not just development team agility. In Agile IT Organization Design , IT management consultant and ThoughtWorks veteran Sriram Narayan shows how to infuse agility throughout your organization. Drawing on more than fifteen years’ experience working with enterprise clients in IT-intensive industries, he introduces an agile approach to “Business–IT Effectiveness” that is as practical as it is valuable.
The author shows how structural, political, operational, and cultural facets of organization design influence overall IT agility—and how you can promote better collaboration across diverse functions, from sales and marketing to product development, and engineering to IT operations. Through real examples, he helps you evaluate and improve organization designs that enhance autonomy, mastery, and purpose: the key ingredients for a highly motivated workforce.
You’ll find “close range” coverage of team design, accountability, alignment, project finance, tooling, metrics, organizational norms, communication, and culture. For each, you’ll gain a deeper understanding of where your organization stands, and clear direction for making improvements. Ready to optimize the performance of your IT organization or digital business? Here are practical solutions for the long term, and for right now.Govern for value over predictability Organize for responsiveness, not lowest cost Clarify accountability for outcomes and for decisions along the way Strengthen the alignment of autonomous teams Move beyond project teams to capability teams Break down tool-induced silos Choose financial practices that are free of harmful side effects Create and retain great teams despite today’s “talent crunch” Reform metrics to promote (not prevent) agility Evolve culture through improvements to structure, practices, and leadership—and careful, deliberate interventions
"Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss:How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouseDemystifies data vault modeling with beginning, intermediate, and advanced techniquesDiscusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0
Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.comDemystifies data mining concepts with easy to understand languageShows how to get up and running fast with 20 commonly used powerful techniques for predictive analysisExplains the process of using open source RapidMiner toolsDiscusses a simple 5 step process for implementing algorithms that can be used for performing predictive analyticsIncludes practical use cases and examples