Kumar Chinnakali

8:24 PM, 16th Mar 2018

25 Free Must-Read Books in New Year 2018 on Open Source, Architecture, Cloud, AI, and Big Data.


Happy New 2018, this is my special post because just now I completed 100th post called “Apache Spark is Superstar; but it’s Supernova on Azure for Big Data Analytics Initiatives” and this is 101st on the curation of free books. Thanks for all support and encouragement, every negative comment makes and pushes me to give better, and all the likes takes me forward with energy to give more in the Cloud Computing, Big Data, and IoT Ecosystem.

Let’s start with question, what’s your new year 2018 resolution? My resolutions are to reduce the weekly no of beers, and must complete a public cloud architect certification (Google Cloud Platform or Azure).

New year post should be special, hence thought sharing with you all the glimpse of books and the list for download with out email id sharing. All credit goes to Cloud Standards Customer Council and O’Reilly.

1.      Getting Started with InnerSource

This book is written Andy Oram and he is an editor at O'Reilly Media, a highly respected book publisher and technology information provider. And in this book author talked about the powerful movement for developing open source system within the walls of a single enterprise, where the openness of a project extends across teams inside the organization. 1st the author reviews the principles that make open source development successful, and then by describing how InnerSource has created impact and worked at PayPal. And, he explained the InnerSource strategies like faster development, complete documentation, code reuse, cross-team collaboration, and development with Git-Hub. Click here to read, happy reading.

2.      Open by Design

The Open by Design book is written by Philip Estes & Doug Davis, and they discussed about the transformation of the Cloud through Open Source and Open Governance. And in this book, they have presented case studies to illustrate the current direction of collaboration and growth in the open cloud, and then they envision the next phase of collaboration—one that includes standardized interfaces for orchestration, cluster management, and distribution and deployment across multiple cloud infrastructure types, such as VMs and containers. Click here to read, happy reading.

3.      Ten Steps to Linux Survival

This book is all about the essentials and importance for navigating the bash jungle, which is written by Jim Lehmer. He is currently working in a Windows shop coding primarily in C#, but with his background in cross-platform development. He discussed about how to connect to a Linux system with OpenSSH and PuTTY secure shells, how to list files and directories, and move around within the file system, how to safely inspect the file contents without changing them, how to determine real-time system state to find underlying problems, and much more. Click here to read, happy reading.

4.      Open Source in Brazil

In the above report Open Source in Brazil, the author talks about Open Source in Brazil, on how to grow despite of barriers. It is written by Andy Oram, and he is specialized in open source, software engineering, and health IT, but his editorial output has ranged from a legal guide covering intellectual property to a graphic novel about teenage hackers. The author shares his view on Brazil Open Source ecosystem, despite a host of problems from government corruption to public health issues and rising crime; Brazil is still the most vibrant Latin American economy. With its strong extractive, manufacturing, and service industries, IT in Brazil is booming as companies seek to digitally transform their operations. Tech startups are also springing to life, and free and open source software is everywhere. Click here to read, happy reading.

5.      Designing Autonomous Teams and Services

In this book, author talks about how to deliver continuous Business value through Organizational alignment. It is written by Scott Millett & Nick Tune. Scott, is the Director of IT for Iglu.com. Over the last 20 years he has held positions in all aspects of software development from junior developer to development lead, development manager to enterprise architect. Nick, is a Principal Engineer at Salesforce. He is passionate about delighting users, creating business impacts, and crafting quality software, placing an equal focus on improving both the delivery capabilities and alignment of an organization. In this book they have discussed about; learn how to align business goals, team boundaries, and software architecture to solve customer problems, how to create a culture of transparency by articulating strategic decisions throughout the organization, how to analyze your organization’s problem domains to minimize organizational and technical dependencies, how to learn techniques for modeling user journeys and business processes in our domains and subdomains, how to design antifragile systems that respond to changing market conditions and new opportunities, and how to apply successful architectural patterns to avoid couplings in our software and couplings between teams. Click here to read, happy reading.

6.      Migrating Java to the Cloud

In this report authors talk about modernizing the enterprise systems without starting from scratch. Authors Kevin Webber and Jason Goodwin cover proven steps and techniques that enable your company to take advantage of cloud infrastructure’s power and flexibility. And also we would be exploring three pillars of successful cloud adoption—infrastructure refresh, application modernization and migration, and security modernization—and learn how to treat the cloud as an unlimited pool of resources that brings both scale and resilience to our system. Along with that they shared Cloud transforming a monolithic legacy application into a cloud native system is no small feat, but with this in-depth report, our organization will learn ways to migrate classical Java applications to newly provisioned cloud infrastructure without requiring a significant rewrite. Click here to read, happy reading.

7.      What Is Serverless?

In this book authors talked about understanding the latest advances in Cloud and Service-Based Architecture. Authors Mike Roberts and John Chapin, co-founders of the Symphonia Serverless and cloud technology consultancy, takes us through the Serverless landscape—particularly the design considerations, tooling, and approaches to operational management we need to make it work. Is Serverless the right choice for us and our team? And the authors dive into this report and find out the followings on how to learn two major aspects of Serverless: Backend-as-a-Service and Functions-as-a-Service, how to compare Serverless application architecture with legacy non-server architecture, how to explore Serverless architecture’s five major benefits, and understand Serverless limitations, including the drawbacks of working with the cloud. Click here to read, happy reading.

8.      Microservices in Production

This book is written by Susan Fowler. She is editor in Chief of Increment and the author of two books about software architecture. In the past, she worked on microservice standardization at Uber, developed application platforms and infrastructure at several small startups, and studied particle physics at the University of Pennsylvania. In this book she talks about microservice's standard principles and requirements. And in this report, author shared the lessons learned from driving a production-readiness initiative across Uber’s more than one thousand microservices. We'll explore eight production-readiness requirements that she and her fellow SREs at Uber adopted after countless hours of research inside and outside the company—requirements that apply to every microservice while providing real, quantifiable results: stability, reliability, scalability, fault-tolerance, catastrophe-preparedness, performance, monitoring, and documentation. And this book is an excerpt of Fowler’s forthcoming book, Production-Ready Microservices, in which she shares standards-based strategies for bringing microservices to a production-ready state. Click here to read, happy reading.

9.      Microservices Anti Patterns and Pitfalls

The above book is written by Mark Richards, and he is an experienced hands-on software architect involved in the architecture, design, and implementation of Microservices Architectures, Service Oriented Architectures, and distributed systems in J2EE and other technologies. He has been involved in the software industry since 1983, and has significant experience and expertise in application, integration, and enterprise architecture. Mark served as the President of the New England Java Users Group from 1999 thru 2003. In this book he talked about what’s the difference between anti-patterns and pitfalls? As per the book, an anti-pattern seems like a good idea when we begin, but only leads us into trouble, while pitfalls are bad ideas from the start. Also, he shared how to learn to avert the most flagrant anti-patterns and pitfalls before we tussle with microservice granularity, data migration, and distributed processing. Along with the above he discussed about Data-Driven Migration Anti-Pattern, Timeout Anti-Pattern, I Was Taught to Share Anti-Pattern, Reach-in Reporting Anti-Pattern, Grains of Sand Pitfall, Developer Without a Cause Pitfall, Jump On The Bandwagon Pitfall, Static Contract Pitfall, Are We There Yet Pitfall, and Give it a Rest Pitfall. Click here to read, happy reading.

10.  Evolving Architectures of FinTech

This book is written by Mike Barlow, to share his view on structuring a New Generation of Financial Services with modular software and agile development strategies. Mike is an award-winning journalist, author and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in numerous industries. As this book he explains the integration between emerging technology and the entrenched financial services infrastructure is an ongoing challenge. According to him there is much progress, but many hurdles remain. And, he shared that many FinTech as another example of technological disruption, but FinTech solutions need to integrate with existing systems in the financial industry, not replace them. And, it will help us to learn how FinTech startups are creating novel types of business models in Africa and Asia, where there are far fewer traditional banks, and in Europe and the US, where financial institutions generally avoid the market for small business loans. Click here to read, happy reading 

11.  Software Architecture Patterns

The above book is written by Mark Richards, and he is an experienced hands-on software architect involved in the architecture, design, and implementation of Microservices Architectures, Service Oriented Architectures, and distributed systems in J2EE and other technologies. He has been involved in the software industry since 1983, and has significant experience and expertise in application, integration, and enterprise architecture. Mark served as the President of the New England Java Users Group from 1999 thru 2003. In this book he talks about patterns including Layered architecture, Event-driven architecture, Microkernel architecture, Microservices architecture, and Space-based architecture. Click her to read, happy reading.

12.  Migrating to Cloud-Native Application Architectures

This book is written by Matt Stine. Matt is a technical product manager at Pivotal. He is a 15 year veteran of the enterprise IT industry, with experience spanning numerous business domains. This book defines the unique characteristics of cloud-native application architectures such as microservices and twelve-factor applications. It includes discussing application architectures that includes, The Twelve-Factor App-a collection of cloud-native app architecture patterns Microservices: independently deployable services that do one thing well, Self-Service Agile Infrastructure-platforms for rapid, repeatable, and consistent provisioning of app environments and backing services, API-based Collaboration-published and versioned APIs that allow interaction between services in a cloud-native app architecture, Anti-Fragility-systems that get stronger when subjected to stress. Click here to read, happy reading.

13.  The Big Data Market

This report is written by Aman Naimat. He is the SVP Technology for Demandbase where he is working on creating the first Artificial Intelligence account-based marketing platform. Aman was previously co-founder and CTO of Spiderbook, a data-driven sales engine. This report helps us to have insights on data-driven analysis of companies using Hadoop, Spark, and Data Science. In this book author shared, Which companies have adopted technologies such as Hadoop and Spark, as well as data science in general? And which industries are lagging behind? With this report we can get the details of the relatively small number of companies using big data in production, Industries that have embraced big data the most—and the least, The amount of money spent on various big data use cases, How many companies actually use fast data, Geographical locations where companies have been quick to adopt big data, as well as the types of teams that use big data technology. Click here to read, happy reading.

14.  Integrated Analytics

This book is written by Courtney Webster. She is is a reformed chemist in the Washington, D.C. metro area. She spent a few years after grad school programming robots to do chemistry and is now managing web and mobile applications for clinical research trials. In this book she talks about the platforms and principles for centralizing our Data. And she presents a roadmap to data centralization that will help our organization make data accessible, flexible, and actionable. Building a genuine data-driven culture depends on our company’s ability to quickly act upon new findings. This helps and explains us how, to identify stakeholders to build a culture of trust and awareness among decision makers, data analysts, and quality management, how to create a data plan to define your needs, specify your metrics, identify data sources, and standardize metric definitions, how to centralize the data to evaluate each data source for existing common fields and, if we can, minor variances, and standardize data references, and find the right tools for the job to choose from legacy architecture tools, managed and cloud-only services, and data visualization or data exploration platforms. Click here to read, happy reading.

15.  Embedding Analytics in Modern Applications

This book is written by Courtney Webster. She is a reformed chemist in the Washington, D.C. metro area. She spent a few years after grad school programming robots to do chemistry and is now managing web and mobile applications for clinical research trials. In this she shared how to provide distraction-free Insights to End Users. She reviews several approaches and methods for embedding analytics capabilities into our applications like should we implement a separate reporting portal, an in-application reporting tab, or go all in with a fully embedded in-page analytics solution? And do we need to build our own or buy a solution out of the box?. This book help us to choose the right embedded analytics tool, and she examines seven challenges—from customization, usability, and capabilities to scalability, performance, and data structure support—and presents best practice solutions for each. Click here to read, happy reading.

16.  Data Science in the Cloud

This book is written by Stephen F. Elston to share his view on Data Science in the Cloud with Microsoft Azure Machine Learning and Python. He is Managing Director of Quantia Analytics, LLC is a big data geek and data scientist, with over two decades of experience using R and S/SPLUS for predictive analytics and machine learning. He holds a PhD degree in Geophysics from Princeton University. In this book he walks us through key steps in the data science process from problem definition, data understanding, and feature engineering, through construction of a regression model and presentation of results. We’ll also learn how to extend Azure ML with Python. Elston uses downloadable Python code and data to demonstrate how to perform data munging, data visualization, and in-depth evaluation of model performance. At the end, we’ll be able to learn how to publish your trained models as web services in the Azure cloud. Click here to read, happy reading.  

17.  Evaluating Machine Learning Models

This book is written by Alice. She is a technical leader in the field of Machine Learning. Her experience spans algorithm and platform development and applications. Currently, she is a Senior Manager in Amazon's Ad Platform. Author first introduces the machine-learning workflow, and then dives into evaluation metrics and model selection. The latter half of the book focuses on hyperparameter tuning and A/B testing, which may benefit more seasoned machine-learning practitioners. It includes how to learn the stages involved when developing a machine-learning model for use in a software application, how to understand the metrics used for supervised learning models, including classification, regression, and ranking, how to walk through evaluation mechanisms, such as hold/out validation, cross-validation, and bootstrapping, how to explore hyperparameter tuning in detail, and discover why it’s so difficult, how to learn the pitfalls of A/B testing, and examine a promising alternatives like multi-armed bandits, and she shared few suggestions for further reading, as well as useful software packages. Click here to read, happy reading.

18.  Artificial Intelligence Now

This is current Perspectives from O'Reilly Media. And they have shared about the AI landscape-the platforms, businesses, and business models shaping AI growth; plus a look at the emerging AI stack, Technology-AI’s technical underpinnings and deep learning capabilities, tools, and tutorials, Homebuilt autonomous systems- hobbyist applications that showcase AI tools, libraries, cloud processing, and mobile computing, Natural language-strategies for scoping and tackling NLP projects, Use cases- an analysis of two of the leading-edge use cases for artificial intelligence—chat bots and autonomous vehicles, Integrating human and machine intelligence-development of human-AI hybrid applications and workflows; using AI to map and access large-scale knowledge databases. Click here to read, happy reading.

19.  Practical Artificial Intelligence in the Cloud

This book is written by Mike Barlow. Mike Barlow is an award-winning journalist, author and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in numerous industries. He shared his view on exploring AI-as-a-Service for Business and Research. Through interviews with consumers and executives of AIaaS vendors, author examines the primary driver of this new approach including, AI is simply too big for any single device or system. But with AIaaS, developers can build applications that perform data collection and compression on devices, while advanced processes such as natural language processing and machine learning are performed in the cloud. Click here to read, happy reading.

20.  What is Artificial Intelligence?

This book is written by Mike Loukides & Ben Lorica. Mike Loukides is an editor for O'Reilly Media, Inc. He is the author of System Performance Tuning and UNIX for FORTRAN Programmers. Mike's interests are system administration, networking, programming languages, and computer architecture. Ben Lorica is the Chief Data Scientist and Director of Content Strategy for Data at O'Reilly Media, Inc.. He has applied Business Intelligence, Data Mining, Machine Learning and Statistical Analysis in a variety of settings including Direct Marketing, Consumer and Market Research, Targeted Advertising, Text Mining, and Financial Engineering. This books helps to have deeper look into the meaning of "general intelligence" when applied to AIs, Moving AIs from supervised learning to unsupervised learning, Why AIs can easily solve problems that humans find challenging, but not problems that humans find easy, The differences between autonomous AIs and assistive AIs that augment our intelligence,Factors that have made AI a hot topic in recent years, Today’s successful AI systems, such as machine learning and computer vision, and OpenAI and the push to make AI research open and visible to the public. Click here to read, happy reading.

21.  The Future of Machine Intelligence

In this book David, shared the perspectives of future of Machine Intelligence from Leading Practitioners. David is an investor with Amplify Partners, an early-stage VC focused on the next generation of infrastructure IT, data and information security companies. He began his career in technology as the co-founder and CEO of Chartio.com, a pioneering provider of cloud-based data visualization and analytics. He was subsequently part of the founding team at Patients Know Best, one of the world's leading cloud-based Personal Health Record (PHR) companies. In this book we can able to learn follwing topic from various practitioners and theoreticians. This includes, high-dimensional problems and non-convex optimization, Natural Language Processing and deep learning, deep learning meets genomic medicine, the startling creativity of evolutionary algorithms, a synthesis of machine learning and control theory, the autonomous car as a driving partner, using topology to uncover the shape of our data, the promise of unsupervised learning and attention model, sequence-to-sequence machine learning, the evolution of machine learning and the role of Spark. Click here to read, happy reading.

22.  What Are Conversational Bots ? 

This book is all an Introduction to and Overview of AI-Driven Chatbots. It is written by two authors, Mike Barlow is an award-winning journalist, author and communications strategy consultant. Jon Bruner is a data journalist who approaches questions that interest him by writing and coding. Before coming to O'Reilly, where he is editor-at-large, he was data editor at Forbes Magazine. In this book authors examine the promise of chatbots, as well as the challenges they faced. Driven by recent advances in artificial intelligence (AI), chatbots have a bright future in customer relations, healthcare, games and entertainment, and worker productivity (picture a bot as our personal assistant). And more over, Microsoft CEO Satya Nadella recently declared that, "bots are the new apps." And explore this book to explore today’s emerging chatbot landscape, including why chatbots now, messaging platforms/frameworks for bots, AI Platforms and Frameworks for bots, and Real-world examples. Click here to read, happy reading.

23.  Architecting for Access

In this book author shared his view on how to simplifying the analytics on big data infrastructure. Rich Morrow is a 20 year veteran of IT, and an expert big data technologies like Hadoop. He has been teaching Cloudera (Hadoop) and AWS for nearly 3 years, retains all certifications for both, and uses these technologies in his day to day consulting practice. He is a prolific writer on Cloud, Big Data, DevOps/Agile, Mobile, and IoT topics, having published many works for companies like GigaOM and Global Knowledge. He explained how the rapid changes to both backend storage and frontend analytics over the past decade, and provides a pragmatic list of requirements for an analytics stack that will centralize access to all of these data systems. With the we can able to examine current analytics platforms, including looker—a new breed of analytics and visualization tools built specifically to handle our fragmented data space. Click here to read, happy reading.

24.  Migrating Big Data Analytics into the Cloud

This book is written by Mike Barlow. He is an award-winning journalist, author and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in numerous industries. He shared his view on just how strong is the movement of big data analytics to the cloud? And he shares that the desire among corporations to adopt big data-as-a-service is gaining momentum-and that many organizations with big data cloud experience are likely to expand their use. With King's recent survey of IT and data professionals in finance, healthcare, technology, and telecom illustrates the ways many of them plan to use big data in the cloud-with predictive analytics leading the charge-and explains why others are still reluctant to join the migration. There are also some surprises, such as the continued popularity of relational databases and the lack of interest in social network analysis. If we are looking into big data cloud services, then this small book well worthwhile. Click here to read, happy reading.

25.  Azure for Developers

This book is written by John Adams. He is a senior cloud solutions architect building in-depth custom training material around Microsoft Azure. He delivers on-site training courses, recorded online training videos, and builds hands-on labs and other instructional materials. He currently works for Opsgility. In this book he shared about what programmers need to know about Microsoft's Cloud Platform. And he explains the Microsoft's Azure platform which has a vast array of features like cloud hosting, web hosting, data analytics, data storage, machine learning, and more—all integrated with Visual Studio, the tool that .NET developers already know. Click here to read, happy reading

Once again thanks for all your support in both way, which energize me create more content on the same line and to share with all our community.

Wish you to have a great new year 2018, what’s your resolution for this new year?

Please subscribe dataottam blog to keep yourself up-to-the-minute on ABC of Data (Artificial Intelligence, Big Data, Cloud Computing, and Cognitive Computing).

Reach us via [email protected], Happy Reading!

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