Hands-on DevOps

Transform yourself into a specialist in DevOps adoption for Big Data on cloud
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Hands-on DevOps

Sricharan Vadapalli

Transform yourself into a specialist in DevOps adoption for Big Data on cloud

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Book Details

ISBN 139781788471183
Paperback424 pages

Book Description

DevOps strategies have really become an important factor for big data environments.

This book initially provides an introduction to big data, DevOps, and Cloud computing along with the need for DevOps strategies in big data environments. We move on to explore the adoption of DevOps frameworks and business scenarios. We then build a big data cluster, deploy it on the cloud, and explore DevOps activities such as CI/CD and containerization. Next, we cover big data concepts such as ETL for data sources, Hadoop clusters, and their applications. Towards the end of the book, we explore ERP applications useful for migrating to DevOps frameworks and examine a few case studies for migrating big data and prediction models.

By the end of this book, you will have mastered implementing DevOps tools and strategies for your big data clusters.

Table of Contents

Chapter 1: Introduction to DevOps
DevOps application - business scenarios
Business drivers for DevOps adoption to big data
Planning the DevOps strategy
Benefits of DevOps
Summary
Chapter 2: Introduction to Big Data and Data Sciences
Big data 
In-memory technology
NoSQL databases
Data visualization
Data science
 Summary
Chapter 3: DevOps Framework
DevOps process
DevOps best practices
DevOps frameworks
Summary
Chapter 4: Big Data Hadoop Ecosystems
Big data Hadoop ecosystems
Big data clusters
Hadoop big data cluster nodes
Commercial Hadoop distributions
Capacity planning for systems
Summary
Chapter 5: Cloud Computing
Cloud computing technologies
Multi-tier cloud architecture model
Cloud architectures
Cloud offerings
Cloud security
Backup and recovery
Summary
Chapter 6: Building Big Data Applications
Traditional enterprise architecture
Principles to build big data enterprise applications
Big data systems life cycle
Building enterprise applications with Spark
Data science
Summary
Chapter 7: DevOps - Continuous Integration and Delivery
Best practices for CI/CD
Jenkins setup 
Git (SCM) integration with Jenkins
Maven (Build) tool Integration with Jenkins
Building jobs with Jenkins
Source code review - Gerrit
Installation of Gerrit
Repository management
Testing with Jenkins
Continuous delivery- Build Pipeline
Jenkins features
Summary
Chapter 8: DevOps Continuous Deployment
Chef
Ansible
Monitoring
Splunk
Nagios monitoring tool for infrastructure
Integrated dashboards for network analysis, monitoring, and bandwidth
Summary
Chapter 9: Containers, IoT, and Microservices
Virtualization
Containers
Container orchestration
Internet of Things (IoT)
Microservices
Summary
Chapter 10: DevOps for Digital Transformation
Digital transformation
Big data and DevOps
Cloud migration - DevOps
Migration to microservices - DevOps
Apps modernization
Architecture migration approach
Best practices for architectural and implementation considerations
DevOps for data science
DevOps for authentication and security
DevOps for IoT systems
Summary
Chapter 11: DevOps Adoption by ERP Systems
Chapter 12: DevOps Periodic Table
Chapter 13: Business Intelligence Trends
Chapter 14: Testing Types and Levels
Chapter 15: Java Platform SE 8

What You Will Learn

  • Learn about the DevOps culture, its frameworks, maturity, and design patterns
  • Get acquainted with multiple niche technologies microservices, containers, kubernetes, IoT, and cloud
  • Build big data clusters, enterprise applications and data science models
  • Apply DevOps concepts for continuous integration, delivery, deployment and monitoring
  • Get introduced to Open source tools, service offerings from multiple vendors
  • Start digital journey to apply DevOps concepts to migrate big data, cloud, microservices, IoT, security, ERP systems

Authors

Table of Contents

Chapter 1: Introduction to DevOps
DevOps application - business scenarios
Business drivers for DevOps adoption to big data
Planning the DevOps strategy
Benefits of DevOps
Summary
Chapter 2: Introduction to Big Data and Data Sciences
Big data 
In-memory technology
NoSQL databases
Data visualization
Data science
 Summary
Chapter 3: DevOps Framework
DevOps process
DevOps best practices
DevOps frameworks
Summary
Chapter 4: Big Data Hadoop Ecosystems
Big data Hadoop ecosystems
Big data clusters
Hadoop big data cluster nodes
Commercial Hadoop distributions
Capacity planning for systems
Summary
Chapter 5: Cloud Computing
Cloud computing technologies
Multi-tier cloud architecture model
Cloud architectures
Cloud offerings
Cloud security
Backup and recovery
Summary
Chapter 6: Building Big Data Applications
Traditional enterprise architecture
Principles to build big data enterprise applications
Big data systems life cycle
Building enterprise applications with Spark
Data science
Summary
Chapter 7: DevOps - Continuous Integration and Delivery
Best practices for CI/CD
Jenkins setup 
Git (SCM) integration with Jenkins
Maven (Build) tool Integration with Jenkins
Building jobs with Jenkins
Source code review - Gerrit
Installation of Gerrit
Repository management
Testing with Jenkins
Continuous delivery- Build Pipeline
Jenkins features
Summary
Chapter 8: DevOps Continuous Deployment
Chef
Ansible
Monitoring
Splunk
Nagios monitoring tool for infrastructure
Integrated dashboards for network analysis, monitoring, and bandwidth
Summary
Chapter 9: Containers, IoT, and Microservices
Virtualization
Containers
Container orchestration
Internet of Things (IoT)
Microservices
Summary
Chapter 10: DevOps for Digital Transformation
Digital transformation
Big data and DevOps
Cloud migration - DevOps
Migration to microservices - DevOps
Apps modernization
Architecture migration approach
Best practices for architectural and implementation considerations
DevOps for data science
DevOps for authentication and security
DevOps for IoT systems
Summary
Chapter 11: DevOps Adoption by ERP Systems
Chapter 12: DevOps Periodic Table
Chapter 13: Business Intelligence Trends
Chapter 14: Testing Types and Levels
Chapter 15: Java Platform SE 8

Book Details

ISBN 139781788471183
Paperback424 pages
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