Multi-Cloud Automation with Ansible : Automate, orchestrate, and scale in a multi-cloud world

✍ Scribed by Sabharwal, Pankaj;

• Publisher: BPB Publications
• Year: 2024
• Tongue: English
• Leaves: 298
• Category: Library

✦ Synopsis

One tool, endless possibilities: Multi-cloud mastery with Ansible KEY FEATURES ● Practical insights for efficient Ansible Tower use. ● Advanced use cases for network to edge computing. ● Multi-cloud infrastructure automation strategies. DESCRIPTION Across the modern IT landscape, managing infrastructure across diverse cloud platforms has become a formidable task. Ansible, a robust open-source automation tool, emerges as the ultimate weapon in your arsenal, unlocking efficiency and control over your multi-cloud environment, such as IBM, AWS, GCP, and Azure. Indulge in an in-depth venture through Ansible's fundamentals, architecture, and applications in multi-cloud environments with use cases. Gain a deep understanding of core concepts, such as playbooks, tasks, and roles, and learn to set up Ansible seamlessly across diverse operating systems and cloud providers. Master the creation of efficient playbooks to automate infrastructure provisioning, application deployment, and configuration management in multi-cloud scenarios. Dig into advanced areas like network automation, security automation, and edge computing, acquiring the skills to automate intricate tasks effortlessly. By the end of this book, you will emerge as a confident Ansible expert, capable of automating your multi-cloud operations with precision and efficiency. You will gain the skills to reduce manual effort, minimize errors, and achieve unprecedented agility in your cloud deployments. WHAT YOU WILL LEARN ● Write efficient Ansible Playbooks for automated system configurations. ● Deploy and manage cloud infrastructure across major providers seamlessly. ● Integrate Ansible with Kubernetes for container orchestration automation. ● Implement Ansible Automation Platform and Tower for enterprise scaling. ● Apply Ansible techniques to automate AI and deep learning pipelines. WHO THIS BOOK IS FOR This book is tailored for IT professionals, including system administrators, DevOps engineers, cloud architects, cloud security professionals, automation engineers, and network specialists seeking to leverage Ansible for automation. TABLE OF CONTENTS 1. Ansible in Multi-Cloud Environment 2. Ansible Setup Across OS and Cloud 3. Writing Tasks, Plays, and Playbooks 4. Infrastructure Automation Using Red Hat Ansible 5. Network Automation Using Ansible 6. App Automation Using Ansible 7. Security Automation Using Red Hat Ansible 8. Red Hat Ansible Automation for Edge Computing 9. Red Hat Ansible for Kubernetes and OpenShift Clusters 10. Using Ansible Automation Platform in Multi-Cloud 11. Red Hat Ansible for Deep Learning

✦ Table of Contents

Cover
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewers
Acknowledgement
Preface
Table of Contents
1. Ansible in Multi-Cloud Environment
Introduction
Structure
Objectives
Challenges in multi-cloud
Manual and error-prone deployments
Complex deployments
Environment inconsistencies
Business values Red Hat Ansible brings
Faster business agility
Increased efficiency of IT operations
Same technology across the board
Simple and agentless
Step-by-step reporting
Cloud agnostic
Ansible is the future for cloud automation
Provisioning
Configuration management
Application deployment
Continuous delivery
Security automation
Cloud automation
Orchestration
Endpoint protection
Conclusion
2. Ansible Setup Across OS and Cloud
Introduction
Structure
Objectives
Installing Ansible on Amazon Web Services EC2
Creating EC2 instance
Installing Ansible on Google cloud provider VM instance
Installing Ansible on Microsoft Azure VM
Creating Microsoft Azure VM
Installing Ansible on Docker container
Installing Ansible on MacOS
Installing Ansible on Windows OS
Installing Ansible in other Linux distros
Conclusion
3. Writing Tasks, Plays, and Playbooks
Introduction
Structure
Objectives
Basic Ansible concepts
Control node
Managed nodes
Inventory
Playbook
Modules
Plugins
Collections
Ansible Automation Platform
General structure of Ansible playbook
Understanding directory layout
Structure of Ansible playbook
Dynamic inventories with Ansible
Real-life example of Ansible playbook
Creating a playbook for NGINX
Running playbook for NGINX
Anatomy of playbook for NGINX
Conclusion
4. Infrastructure Automation Using Red Hat Ansible
Introduction
Structure
Objectives
Infrastructure automation using Ansible on AWS
ec2 module
ec2 module in EC2 instance
ec2_vpc_net module
Other modules
Storage on AWS
Infrastructure automation using Ansible on Azure
Infrastructure automation using Ansible on Google compute cloud
Conclusion
5. Network Automation Using Ansible
Introduction
Structure
Objectives
Gathering network information with Ansible
Naming of common network device modules
Naming of other network device modules
Modules that gather facts on network devices
Modules that run commands on network devices
Modules that configure network devices
Modules that configure layer 3 interfaces
Exploring vyos_facts and iso_facts
Viewing system settings
Backing up network device configurations
Configuring the host name of network device
Configuring the system settings of network device
Real-life scenario example
Conclusion
6. App Automation Using Ansible
Introduction
Structure
Objectives
Using Ansible for app deployment on AWS
Ansible role setup
Setup dynamic inventory file
Running the Ansible playbook
Using Ansible for app deployment on GCP
Using Ansible for app deployment on Azure
Conclusion
7. Security Automation Using Red Hat Ansible
Introduction
Structure
Objectives
Security challenges and how Ansible fits in
Enterprise firewall management
Intrusion detection and prevention system
Installing Snort and deploying Snort rules using Ansible
Security information and event management
Setting up Qradar using Ansible approach
Setting up log resources on QRadar
Offense management in QRadar using Ansible
Introduction to Splunk integration
Install Splunk using Ansible
Integrating systems with Splunk
Policy access management
Endpoint protection platforms
Setting up Symantec Endpoint Protection
Setting up Microsoft Defender ATP Endpoint Protection
Integrating security automation with ITSM and ticketing
Conclusion
8. Red Hat Ansible Automation for Edge Computing
Introduction
Structure
Objectives
Enterprise automation
Ansible Automation Platform
Automation mesh
Features provided by automation mesh
Industry use case
Transportation
Retail
Industry 4.0
Telecommunications
Financial services and insurance
Smarter cities
Health care
Conclusion
9. Red Hat Ansible for Kubernetes and OpenShift Clusters
Introduction
Structure
Objectives
Ansible for Kubernetes operators
Why Ansible for operators
Creating Kubernetes operator with Ansible
Kubernetes modules in Ansible
Creating Kubernetes object using ad hoc commands
Creating Kubernetes object using Ansible playbook
GitOps workflow using OpenShift GitOps operator
Managing Kubernetes/OpenShift clusters and Day2Ops operations with Ansible
Conclusion
10. Using Ansible Automation Platform in Multi-Cloud
Introduction
Structure
Objectives
AAP components
Understanding automation controller
Automation controller vs Ansible Tower
Example workflow
Reference architecture of AAP
Installing AAP in OpenShift cluster
Integrating AAP with source code management Git repo
Example workflow
Integrating AAP with RHACM
Use cases
End to end GitOps solutions
Scenario 1
Scenario 2
Policy management
Impact of AAP in multi-cloud environments
DevOps and GitOps best practices
Key benefits
Conclusion
11. Red Hat Ansible for Deep Learning
Introduction
Structure
Objectives
Use of Ansible in deep learning
Using Ansible to install deep learning components
Setting up TensorFlow using Ansible
Setting up CUDA drivers
Installing NVIDIA drivers
Installing Jupyter Notebook
Automating hyperparameter tuning and model training using Ansible
Integration with HyperOpt/Ray Tune
Benefits if integration with HyperOpt/Ray Tune
Installing other deep learning components
Installing PyTorch
Installing Keras
Installing Horovod
Installing OpenCV
Installing DVC
Conclusion
Index