Software technology advances adopted for In-memory systems

Data compression

No aggregate tables

Insert-only tables

Column, row, and hybrid storage

Partitioning

NoSQL databases

Benefits of NoSQL

Data visualization

Data visualization application

Data science

Summary

DevOps Framework

DevOps process

DevOps best practices

DevOps process

Source Code Management (SCM)

Code review

Configuration Management

Build management

Artifacts repository management

Release management

Test automation

Continuous integration

Continuous delivery

Continuous deployment

Infrastructure as Code

Routine automation

Key application performance monitoring/indicators

DevOps frameworks

DevOps maturity life cycle

DevOps maturity map

DevOps progression framework/readiness model

DevOps maturity checklists

Agile framework for DevOps process projects

Agile ways of development

Summary

Big Data Hadoop Ecosystems

Big data Hadoop ecosystems

Inbuilt tools and capabilities in Hadoop ecosystem

Big data clusters

Hadoop cluster attributes

High availability

Load balancing

High availability and load balancing

Distributed processing and parallel processing

Usage of Hadoop big data cluster

Hadoop big data cluster nodes

Types of nodes and their roles

Commercial Hadoop distributions

Hadoop Cloudera enterprise distribution

Data integration services

Hadoop data storage

Data access services

Database

Unified (common) services

Cloudera proprietary services and operations/cluster management

A Hadoop Hortonworks framework

Data governance and schedule pipeline

Cluster management

Data access

Data workflow

A Hadoop MapR framework

Machine learning

SQL stream

Storage, retrieval, and access control

Data integration and access

Provisioning and coordination

Pivotal Hadoop platform HD Enterprise

A Hadoop ecosystem on IBM big data

A Hadoop ecosystem on AWS

Microsoft Hadoop platform is HDInsight hosted on Microsoft Azure

Capacity planning for systems

Guideline for estimating and capacity planning

Cluster-level sizing estimates

For master node

Worker node

Gateway node

Summary

Cloud Computing

Cloud computing technologies

Cloud technology concepts

Authentication and security

Multi-tier cloud architecture model

Presentation tier

Business logic tier

Data tier

Relational databases

NoSQL database

Data storage

Cloud architectures

Public cloud

Private cloud

Hybrid cloud

Community cloud model

Cloud offerings

Software as a Service (SaaS)

Single tenant

Multi-tenancy

Multi-instance

Benefits of SaaS

Platform as a Service (PaaS)

Development as a Service (DaaS)

Data as a Service with Paas

Database as a Service with Paas

PaaS tied to SaaS environment

PAAS tied to an operating environment

Open-platform PaaS

Microsoft Azure Portal

Amazon Web Services

Salesforce offerings on cloud

Network as a Service (NaaS)

Identity as a service (IDaaS)

Single Sign-On

Federated Identity Management (FIDM)

OpenID

Cloud security

Data encryption

Encryption in transit

Encryption-at-rest

End-to-end encryption

Backup and recovery

Summary

Building Big Data Applications

Traditional enterprise architecture

Principles to build big data enterprise applications

Big data systems life cycle

Data discovery into the system

Data discovery stages

Data quality

Batch processing

RDBMS to NoSQL

Flume

Stream processing

Real-time

Lambda architecture

The data storage layer

Data storage - best practices for better organization and effectiveness

Landing

Raw

Work

Gold

Quarantine

Business

Outgoing

Computing and analyzing data

Apache Spark analytic platform

Spark Core Engine

Spark SQL

Spark Streaming

Visualization with big data systems

Data governance

People and collaboration in accordance with DevOps core concept

Environment management

Documentation

Architecture board

Development and build best practices

Version control

Release management

Building enterprise applications with Spark

Client-services presentation tier

Data catalog services

Workflow catalog

Usage and tracking

Security catalog

Processing framework

Ingestion services

Data science

Approach to data science

Supervised models

Neural network

Multi layer perceptron

Decision tree

Unsupervised models

Clusters

Distances

Normalization

K-means

Summary

DevOps - Continuous Integration and Delivery

Best practices for CI/CD

Jenkins setup

Prerequisites to install Jenkins

Standalone Installation

Linux system installation on Ubuntu

Git (SCM) integration with Jenkins

Integrating GitHub with Jenkins

Maven (Build) tool Integration with Jenkins

Building jobs with Jenkins

Source code review - Gerrit

Installation of Gerrit

Repository management

Testing with Jenkins

Setting up unit testing

Automated test suite

Continuous delivery- Build Pipeline

Jenkins features

Security in Jenkins

Summary

DevOps Continuous Deployment

Chef

Chef landscape components

Chef server

Features of Chef server

Chef client on nodes

Ohai

Workstations

Chef repo

Extended features of Chef

Habitat

InSpec

Chef Automate workflow

Compliance

Ansible

Prominent features

Benefits of Ansible

Ansible terminology, key concepts, workflow, and usage

CMDB

Playbooks

Modules

Inventory

Plugins

Ansible Tower

Ansible Vault

Ansible Galaxy

Testing strategies with Ansible

Monitoring

Splunk

Nagios monitoring tool for infrastructure

Nagios – enterprise server and network monitoring software

Integrated dashboards for network analysis, monitoring, and bandwidth

Summary

Containers, IoT, and Microservices

Virtualization

Hypervisor

Types of virtualization

Emulation

Paravirtualization

Container-based virtualization

Containers

Docker containers

Java EE containers as a part of Java EE

Java EE server and containers

Amazon ECS container service

Containers and images

Task definitions

Tasks and scheduling

Clusters

Container agent

Pivotal container services

Google container services

Container orchestration

Orchestration tools

Kubernetes

Docker orchestration tools

Internet of Things (IoT)

IoT - eco system

Standard devices

Data synthesis

Data collection

Device integration

Real-time analytics

Application and process extension

Technology and protocols

IoT - application in multiple fields

IoT platforms for development

ThingWorx

Virtualized Packet Core (VPC)

Electric Imp

Predix

Eclipse IoT

SmartHome

Eclipse SCADA

Contiki

Contiki communication

Dynamic module loading

The Cooja network simulator

Microservices

Microservices core patterns

Microservices architecture

Microservice decision

Microservices deployment patterns

Distribution patterns

Microservice chassis

Communication mode

Data management options

API interface

Service discovery

Summary

DevOps for Digital Transformation

Digital transformation

Big data and DevOps

Planning effectively on software updates

Lower error rates

Consistency of development and production environments

Prompt feedback from production

Agility of big data projects

Big Data as a service

The ETL datamodels

Methodology 1

Methodology 2

Methodology 3

Methodology 4

Methodology 5

Methodology 6

Cloud migration - DevOps

Migration strategy/approach

Migration to microservices - DevOps

Strategy 1 - standalone microservice

Strategy 2 - separate frontend and backend

Strategy 3 - extraction of services

Prioritizing the modules for conversion to services

The process to extract a module

Stage 1

Stage 2

Apps modernization

Architecture migration approach

Data coupling

Microservices scalability

Best practices for architectural and implementation considerations

Domain modeling

Service size

Testing

Service discovery

Deployment

Build and release pipeline

Feature flags

Developer productivity with microservices adoption

Monitoring and operations

Organizational considerations

DevOps for data science

The DevOps continuous analytics environment

DevOps for authentication and security

Kerberos realm

The user and the authentication server

Client and the HTTP service

DevOps for IoT systems

Security by design

Summary

DevOps Adoption by ERP Systems

DevOps Periodic Table

Business Intelligence Trends

Testing Types and Levels

Java Platform SE 8