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Free Practical DevOps
Free Packt eBook by Joakim Verona (valid through 9/19 at 19:00 EST). This book covers DevOps, IoT.
DevOps is a practical field that focuses on delivering business value as efficiently as possible. DevOps encompasses all the flows from code through testing environments to production environments. It stresses the cooperation between different roles, and how they can work together more closely, as the roots of the word imply—Development and Operations.
After a quick refresher to DevOps and continuous delivery, we quickly move on to looking at how DevOps affects architecture. You’ll create a sample enterprise Java application that you’ll continue to work with through the remaining chapters. Following this, we explore various code storage and build server options. You will then learn how to perform code testing with a few tools and deploy your test successfully. Next, you will learn how to monitor code for any anomalies and make sure it’s running properly. Finally, you will discover how to handle logs and keep track of the issues that affect processes
What You Will Learn
- Appreciate the merits of DevOps and continuous delivery and see how DevOps supports the agile process
- Understand how all the systems fit together to form a larger whole
- Set up and familiarize yourself with all the tools you need to be efficient with DevOps
- Design an application that is suitable for continuous deployment systems with Devops in mind
- Store and manage your code effectively using different options such as Git, Gerrit, and Gitlab
- Configure a job to build a sample CRUD application
- Test the code using automated regression testing with Jenkins Selenium
- Deploy your code using tools such as Puppet, Ansible, Palletops, Chef, and Vagrant
- Monitor the health of your code with Nagios, Munin, and Graphite
- Explore the workings of Trac—a tool used for issue tracking
About the Author
Joakim Verona is a consultant with a specialty in Continuous Delivery and DevOps. He has worked with all aspects of systems development since 1994. He has actively contributed as the lead implementer of complex multilayered systems such as web systems, multimedia systems, and mixed software/hardware systems. His wide-ranging technical interests led him to the emerging field of DevOps in 2004, where he has stayed ever since. Joakim completed his masters in computer science at Linköping Institute of Technology. He has also worked as a consultant in a wide range of assignments in various industries, such as banking and finance, telecom, industrial engineering, press and publishing, and game development. He is also interested in the Agile field and is a certified Scrum master, Scrum product owner, and Java professional.
$9.99 Apress eBook by Robert Stackowiak, Art Licht, Venu Mantha, Louis Nagode. This book covers Big Data, IoT, Information Architecture.
Enterprise Information Architecture for a New Age: Big Data and The Internet of Things, provides guidance in designing an information architecture to accommodate increasingly large amounts of data, massively large amounts of data, not only from traditional sources, but also from novel sources such everyday objects that are fast becoming wired into global Internet. No business can afford to be caught out by missing the value to be mined from the increasingly large amounts of available data generated by everyday devices.
The text provides background as to how analytical solutions and enterprise architecture methodologies and concepts have evolved (including the roles of data warehouses, business intelligence tools, predictive analytics, data discovery, Big Data, and the impact of the Internet of Things). Then you’re taken through a series of steps by which to define a future state architecture and create a plan for how to reach that future state.
Enterprise Information Architecture for a New Age: Big Data and The Internet of Things helps you gain an understanding of the following:
- Implications of Big Data from a variety of new data sources (including data from sensors that are part of the Internet of Things) upon an information architecture
- How establishing a vision for data usage by defining a roadmap that aligns IT with line-of-business needs is a key early step
- The importance and details of taking a step-by-step approach when dealing with shifting business challenges and changing technology capabilities
- How to mitigate risk when evaluating existing infrastructure and designing and deploying new infrastructure
Enterprise Information Architecture for a New Age: Big Data and The Internet of Things combines practical advice with technical considerations. Author Robert Stackowiak and his team are recognized worldwide for their expertise in large data solutions, including analytics. Don’t miss your chance to read this book and gain the benefit of their advice as you look forward in thinking through your own choices and designing your own architecture to accommodate the burgeoning explosion in data that can be analyzed and converted into valuable information to drive your business forward toward success.
50% off Data Munging with R
50% off Manning’s eBook by Dr. Jonathan Carroll. This book covers R, Big Data, Data Visualization, Data Munging.
Data Munging with R shows you how to take raw data and transform it for use in computations, tables, graphs, and more. Whether you already have some programming experience or you’re just a spreadsheet whiz looking for a more powerful data manipulation tool, this book will help you get started. You’ll discover the ins and outs of using the data-oriented R programming language and its many task-specific packages. With dozens of practical examples to follow, learn to fill in missing values, make predictions, and visualize data as graphs. By the time you’re done, you’ll be a master munger, with a robust, reproducible workflow and the skills to use data to strengthen your conclusions!
About the technology
Data munging - manipulating raw data - is a cornerstone of data science. Munging techniques include cleaning, sorting, parsing, filtering, and pretty much anything else you need to make data truly useful. The R language, with its intuitive RStudio environment, is the perfect data munging tool. R provides a rich ecosystem of community-driven packages and utilities for finance and accounting, marketing, web-scraping, and all manner of data science tasks. And getting started with R is so easy, even managers have been known to use it for ad hoc data analysis!
- Learning to program
- Critical R structures and operators
- Handling R packages
- Tidying and refining your data
- Plotting your data
About the reader
If you have beginner programming skills or you’re comfortable with writing spreadsheet formulas, you have everything you need to get the most out of this book.
About the author
Dr. Jonathan Carroll holds a PhD from the University of Adelaide in theoretical astrophysics, currently working in statistical modelling. He contributes packages to R, is a frequent contributor of answers on StackOverflow and an avid science communicator.
50% off Visualizing Graph Data
50% off Manning’s eBook by Corey Lanum. This book covers Data Visualization, Gephi, KeyLines, D3.js.
Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools. This book is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations.
About the technology
Assume you are doing a great job collecting data about your customers and products. Are you able to turn your rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts.
About the book
Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging book gently introduces graph data visualization through fascinating examples and compelling case studies. You’ll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you’ll have a conceptual foundation as well as the practical skills to explore your own data with confidence.
- Techniques for creating effective visualizations
- Examples using the Gephi and KeyLines visualization packages
- Real-world case studies
About the reader
No prior experience with graph data is required.
About the author
Corey Lanum has decades of experience building visualization and analysis applications for companies and government agencies around the globe.
50% off Introducing Data Science Big data, machine learning, and more, using Python tools
50% off Manning’s eBook by Davy Cielen, Arno D. B. Meysman, Mohamed Ali. This book covers Big Data, Data Science, Python, Machine Learning.
Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you’ll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science.
About the technology
Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started.
About the book
Introducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You?ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You?ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you?ll have the solid foundation you need to start a career in data science.
- Handling large data
- Introduction to machine learning
- Using Python to work with data
- Writing data science algorithms
About the reader
About the authors
Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors.
Practical Concurrent Haskell With Big Data Applications by Stefania Loredana Nita, Marius Mihailescu. This book covers Haskell, Big Data.
Learn to use the APIs and frameworks for parallel and concurrent applications in Haskell. This book will show you how to exploit multicore processors with the help of parallelism in order to increase the performance of your applications.
Practical Concurrent Haskell teaches you how concurrency enables you to write programs using threads for multiple interactions. After accomplishing this, you will be ready to make your move into application development and portability with applications in cloud computing and big data. You’ll use MapReduce and other, similar big data tools as part of your Haskell big data applications development.
What You’ll Learn
- Program with Haskell
- Harness concurrency to Haskell
- Apply Haskell to big data and cloud computing applications
- Use Haskell concurrency design patterns in big data
- Accomplish iterative data processing on big data using Haskell
- Use MapReduce and work with Haskell on large clusters
Who This Book Is For
Those with at least some prior experience with Haskell and some prior experience with big data in another programming language such as Java, C#, Python, or C++.
About the authors
Stefania Loredana Nita holds two B.Sc., one in Mathematics (2013) and one in Computer Science (2016) from the University of Bucharest, Faculty of Mathematics and Computer Science; she received her M.Sc. in Software Engineering (2016) from University of Bucharest, faculty of Mathematics and Computer Science. She has worked as developer for an insurance company (Gothaer Insurance), and as a teacher of Mathematics and Computer Science in private centers of educations. Currently, she is Ph.D. student in Computer Science (from 2016) at Faculty of Mathematics and Computer Science from University of Bucharest. Also, she is teaching assistant at the same university and works since 2015 as researcher and developer at Institute for Computers, Bucharest, Romania. Her domains of interest are cryptography applied in cloud computing and big data, parallel computing and distributed systems, software engineering.
Marius Mihailescu received his B.Sc. in Science and Information Technology (2008) and B.Eng. in Computer Engineering (2009) from the University of Southern Denmark; he holds two M.Sc., one in Software Engineering (2010) from the University of Bucharest and the second one in Information Security Technology (2011) from the Military Technical Academy. His Ph.D. is in Computer Science (2015) from the University of Bucharest, Romania with a thesis on security of biometrics authentication protocols. From 2005 to 2011 he worked as a software developer and researcher for different well-known companies (Softwin, NetBridge Investments, Declic) from Bucharest, Romania (software and web development, business analysis, parallel computing, cryptography researching, distributed systems). Starting in 2012 until 2015 he has been an assistant in the Informatics department, University of Titu Maiorescu and Computer Science department, University of Bucharest. Since 2015, he is a lecturer at the University of South-East Lumina.
Amazon Web Services in Action, Second Edition by Andreas Wittig, Michael Wittig. This book covers AWS.
Amazon Web Services in Action, Second Edition is a comprehensive introduction to computing, storing, and networking in the AWS cloud. You’ll find clear, relevant coverage of all the essential AWS services you to know, emphasizing best practices for security, high availability and scalability. The practical, hands-on examples include different approaches to deploying applications on AWS, how to secure your infrastructure by isolating networks, and controlling traffic and managing access to AWS resources. You’ll also learn to integrate AWS services into your own applications using SDKs and gain handy ideas on how to design applications for high availability, fault tolerance, and scalability.
Fully updated to include the latest revisions and updates to AWS; this new edition also offers three new chapters covering the latest additions to the AWS platform: serverless infrastructure automation with AWS Lambda, sharing data volumes between machines with EFS, and caching data in memory with ElastiCache!
About the technology
Whether you’re analyzing real-time data, hosting enterprise software, or running an e-commerce site, Amazon Web Services offers you a reliable cloud-based platform with services that scale to fit your needs. The most mature cloud platform available, AWS provides basic infrastructure resources like connectivity, networking, computing power, and storage - all on a pay-as-you-go basis so you can get just what you need when you need it.
- An overview of AWS cloud concepts and best practices
- Managing servers on EC2 for cost-effectiveness
- Infrastructure automation with Infrastructure as Code (AWS CloudFormation)
- Deploying applications on AWS
- Storing data on AWS
- Integrating Amazon’s pre-built services
- Architecting highly available and fault tolerant systems
About the reader
Written for developers and DevOps engineers moving distributed applications to the AWS platform.
About the authors
Andreas Wittig and Michael Wittig are software engineers and consultants focused on AWS and web development. They migrated the first bank in Germany to AWS along with other heavily regulated businesses with legacy applications.
GET MORE WITH MANNING
An eBook copy of the previous edition, Amazon Web Services in Action (First Edition), is included at no additional cost. It will be automatically added to your Manning Bookshelf within 24 hours of purchase.
O’Reilly Media, Inc.
- JupyterCon 2017 - New York, NY (Video) by O’Reilly Media, Inc.
- Learning TensorFlow (Book) by Itay Lieder, Yehezkel S. Resheff, Tom Hope
- Mobile Game Development with Unity (Book) by Paris Buttfield-Addison, Jon Manning
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- Data Management and Preparation Using R (Video) by Martin Burger
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- Understanding the Programming Models of Azure Service Fabric (Video) by Ivan Gavryliuk