• Benefits of Artificial Intelligence for IT Operations (AIOps)
• Artificial Intelligence for IT Operations (AIOps) Overview
• Benefits of AIOps
• Use Case: Evaluating the Benefits of AIOps
• Implications of AIOps for Business
• Implications of AIOps for Business
• Use Case: Implications of AIOps for Business
• Key Capabilities of Artificial Intelligence for IT Operations (AIOps)
• Key Capabilities of AIOps
• Use Case: Understanding Key Capabilities of AIOps
• Key Dimensions of IT Operations Monitoring
• IT Operations Monitoring: Overview and Relevance
• Understanding Key Dimensions of IT Operations Monitoring
• Key Dimensions of IT Operations Monitoring and AIOps
• Use Case: Understanding Key Dimensions of IT Operations Monitoring
• AIops Deployment Types & storages
• AIops Industry Use cases
• AIOps Vs DevOps Vs MLOps Life cycle
• AIOps Challenges
• AIOps Popular Solutions
• AIOps Best Practices
• AIOps supporting DevOps & SRE

Introduction to Prometheus

• Overview of Prometheus
• Brief history and purpose
• Key features and architecture
• Basic Installation and Configuration
• Quick setup guide
• Overview of configuration files and settings
• Understanding Metrics and Data Model
• Introduction to Prometheus metrics
• Data types and structure
• Q&A Session

Basic Monitoring with Prometheus

• Instrumentation and Metrics Collection
• How to add Prometheus metrics to an application
• Best practices for metric collection
• Introduction to Prometheus Query Language (PromQL)
• Basic syntax and queries
• Creating simple alerts
• Hands-On Exercise
• Quick setup of basic monitoring for a demo application

Introduction to Grafana and Dashboard Creation

• Overview of Grafana
• Key features and integration with Prometheus


• Setting Up Grafana
• Connecting Grafana to Prometheus


• Creating Basic Dashboards in Grafana
• Introduction to dashboard creation and configuration
• Overview of visualization type


• Hands-On Exercise
• Participants create a basic dashboard for the demo application

Advanced Features and AIOps Integration

• Advanced Dashboard Techniques in Grafana
• Dynamic dashboards with variables
• Setting up basic alerts in Grafana


• Integrating Prometheus and Grafana with AIOps
• How these tools fit into an AIOps strategy
• Brief on AIOps concepts relevant to monitoring and observability


• Wrap-Up and Q&A
• Recap of key concepts
• Open floor for questions and discussion on real-world applications

Introduction to the ELK Stack

• Overview of ELK Stack
• Introduction to Elasticsearch, Logstash, and Kibana
• Role of ELK in AIOps
• Basic architecture and flow of data within the ELK Stack


• Introduction to Elasticsearch
• Understanding Elasticsearch basics: Indexes, Documents, and Nodes
• Basic Elasticsearch operations: CRUD (Create, Read, Update, Delete)


• Q&A Session
• Address initial queries and clarifications

Deep Dive into Logstash and Data Ingestion

• Understanding Logstash
• Logstash fundamentals: Input, Filter, and Output plugins
• Configuring Logstash for data ingestion


• Hands-On Exercise: Setting Up Logstash
• Walkthrough of setting up a basic Logstash pipeline
• Ingesting sample data into Elasticsearch

Kibana for Data Visualization and Analysis

• Introduction to Kibana
• Kibana Dashboard, Visualization, and Discover features
• Connecting Kibana to Elasticsearch


• Hands-On Exercise: Creating Visualizations and Dashboards
• Participants create basic visualizations and dashboards using the ingested data
• Exploration of Kibana's features relevant to AIOps

ELK Stack in AIOps and Advanced Topics

• ELK Stack in the Context of AIOps
• Integrating ELK with AIOps workflows
• Real-world use cases of ELK in AIOps (e.g., anomaly detection, performance monitoring)


• Advanced ELK Features
• Brief on advanced Elasticsearch queries
• Overview of X-Pack features (security, alerting, machine learning)


• Wrap-Up and Q&A
• Recap of key points
• Open Q&A session to discuss practical applications and address any remaining questions

Introduction to Kibana

• What is Apache Kafka and why it's important in AIOps
• Kafka's architecture and core components (Brokers, Topics, Producers, Consumers)


• Kafka Installation and Basic Configuration
• Setting up a basic Kafka environment
• Overview of Kafka configuration files


• Kafka Producers and Consumers
• Understanding Producers and Consumers
• Writing basic producers and consumers


• Q&A Session
• Address initial queries and clarifications

Kafka in Depth - Topics, Partitions, and Replication

• Deep Dive into Kafka Topics and Partitions
• Creating and managing Topics
• Understanding Partitions for scalability and reliability


• Kafka Replication and Fault Tolerance
• Concept of replication for high availability
• Leader and follower partitions

Kafka Streams and Kafka Connect

• Introduction to Kafka Streams
• Understanding stream processing in Kafka
• Basics of Kafka Streams API


• Kafka Connect for Integration
• Overview of Kafka Connect
• Setting up connectors for data import/export

Kafka in AIOps and Practical Exercise

• Using Kafka in an AIOps Context
• Role of Kafka in event-driven architectures for AIOps
• Real-world use cases: Log aggregation, metrics collection, real-time analytics


• Hands-On Exercise: Setting Up a Kafka Pipeline
• Building a simple pipeline for data ingestion and processing
• Monitoring and managing Kafka performance


• Wrap-Up and Q&A Session
• Recap of key concepts and best practices
• Open floor for final questions and discussions

Introduction to TensorFlow and Machine Learning Basics

• Overview of TensorFlow
• Introduction to TensorFlow and its relevance in AIOps
• Core features and capabilities of TensorFlow


• Machine Learning Fundamentals
• Brief overview of machine learning concepts
• How TensorFlow supports machine learning operations


• Setting Up TensorFlow
• Installation and setup of TensorFlow
• Introduction to TensorFlow’s programming model


• Q&A Session
• Address initial queries and clarifications

TensorFlow Basics - Operations, Graphs, and Sessions

• TensorFlow Core Concepts
• Understanding Tensors, Operations, Graphs, and Sessions
• Building simple computation graphs


• Hands-On Exercise: Basic TensorFlow Operations
• Creating and executing a simple TensorFlow program
• Introduction to TensorFlow data types and operations

Building Machine Learning Models with TensorFlow

• Introduction to Neural Networks in TensorFlow
• Basic concepts of neural networks
• Building a simple neural network in TensorFlow


• Practical Exercise: Building a Basic ML Model
• Step-by-step construction of a machine learning model for a simple problem (e.g., regression or classification)

TensorFlow in AIOps and Advanced Topics

• TensorFlow in the Context of AIOps
• Discussing the role of TensorFlow in AIOps (e.g., anomaly detection, predictive maintenance)
• Real-world examples of TensorFlow applications in AIOps


• Advanced TensorFlow Features
• Overview of advanced features like TensorFlow Extended (TFX), Keras for deep learning, and distributed training


• Wrap-Up and Q&A Session
• Recap of key concepts and best practices
• Open floor for final questions and discussions on practical TensorFlow applications in AIOps

Introduction to Jupyter Notebooks

• Overview of Jupyter Notebooks (15 mins)
• Introduction to Jupyter Notebooks and their importance in data analysis
• Key features and benefits in the context of AIOps


• Setting Up Jupyter Notebooks (15 mins)
• Installation and basic setup
• Navigating the Jupyter Notebook interface


• Basic Operations in Jupyter Notebook (15 mins)
• Creating and managing notebooks
• Overview of Markdown, code cells, and kernel management


• Q&A Session (15 mins)
• Addressing initial queries and clarifications

Data Analysis Basics in Jupyter Notebook

• Data Import and Manipulation
• Importing data from various sources (CSV, databases)
• Basic data manipulation using Pandas


• Hands-On Exercise: Working with Data
• Participants practice importing and manipulating a sample dataset

Advanced Data Analysis and Visualization

• Advanced Data Analysis Techniques
• Exploring more complex data manipulation and transformation
• Introduction to time series analysis relevant to AIOps


• Data Visualization in Jupyter
• Using Matplotlib and Seaborn for data visualization
• Creating plots and charts relevant to AIOps data (e.g., performance metrics)

Jupyter Notebooks in AIOps Context and Best Practices

• Applying Jupyter Notebooks in AIOps
• Case studies or examples of Jupyter Notebooks used in AIOps scenarios
• Integrating Jupyter Notebooks with other AIOps tools and platforms


• Best Practices and Advanced Features
• Tips for effective use of Jupyter Notebooks
• Overview of advanced features like JupyterLab, extensions


• Wrap-Up and Q&A Session
• Recap of key concepts and functionalities
• Open floor for final questions and in-depth discussions

Introduction to Ansible and Configuration Management

• Overview of Ansible
• Introduction to Ansible and its role in AIOps
• Key features and advantages of using Ansible for configuration management


• Ansible Architecture and Components
• Understanding Ansible architecture: Playbooks, Roles, Tasks, Modules, Inventory
• YAML syntax basics


• Setting Up Ansible
• Installation and basic setup of Ansible
• Setting up an inventory file


• Q&A Session
• Addressing initial queries and clarifications

Basic Playbooks and Ad-hoc Commands

• Writing Your First Ansible Playbook
• Creating a simple playbook
• Defining tasks and running the playbook


• Ansible Ad-hoc Commands
• Introduction to ad-hoc commands in Ansible
• Practical examples of common ad-hoc commands

Advanced Ansible Features

• Variables, Templates, and Roles
• Using variables and templates for dynamic configurations
• Organizing playbooks with roles


• Error Handling and Debugging
• Best practices for error handling in Ansible playbooks
• Using Ansible's debugging tools

Ansible in AIOps and Hands-On Exercise

• Applying Ansible in an AIOps Context
• Case studies or examples of Ansible used in AIOps scenarios
• Integration of Ansible with monitoring and alerting tools


• Hands-On Exercise: Building an AIOps Pipeline
• Participants work on creating a basic pipeline using Ansible
• Automating a simple operational task relevant to AIOps


• Wrap-Up and Q&A Session
• Recap of key concepts and functionalities
• Open floor for final questions and in-depth discussions

Introduction to Terraform and Infrastructure as Code

• Overview of Terraform
• Introduction to Terraform and its role in infrastructure automation
• Key features and benefits of using Terraform in AIOps


• Terraform Basics
• Understanding Terraform's syntax and structure
• Core concepts: Providers, Resources, Variables, State


• Setting Up Terraform
• Installing Terraform
• Basic setup and configuration


• Q&A Session
• Addressing initial queries and clarifications

Writing Terraform Configuration

• Creating Your First Terraform Configuration
• Writing a basic Terraform configuration file
• Managing infrastructure as code


• Understanding Terraform Workflow
• The Terraform workflow: init, plan, apply, destroy
• Hands-on demo of managing a simple infrastructure

Advanced Terraform Concepts

• Modules and Remote State
• Using modules to organize and reuse code
• Managing state in complex environments


• Dynamic Infrastructure with Terraform
• Dynamic configurations with loops and conditionals
• Integrating with cloud providers (AWS, Azure, GCP)

Terraform in AIOps and Practical Exercise

• Terraform in an AIOps Context
• Real-world use cases of Terraform in AIOps
• Automating and maintaining AIOps infrastructure with Terraform


• Hands-On Exercise: Implementing an AIOps Scenario
• Participants implement a small-scale infrastructure setup relevant to AIOps
• Practicing Terraform commands and configurations


• Wrap-Up and Q&A Session
• Recap of key concepts and best practices
• Open floor for final questions and discussions on practical applications

Introduction to Jenkins and Continuous Integration

• Overview of Jenkins
• Introduction to Jenkins and its importance in CI/CD pipelines
• The role of Jenkins in AIOps


• Jenkins Architecture and Key Concepts
• Understanding Jenkins architecture: master, agents, plugins
• Core concepts: Jobs, Builds, Plugins, Pipelines


• Setting Up Jenkins
• Installing and configuring Jenkins
• Navigating the Jenkins interface


• Q&A Session
• Addressing initial queries and clarifications

Building Jobs and Basic Pipelines in Jenkins

• Creating Your First Jenkins Job
• Setting up a freestyle project
• Configuring source code management (SCM), build triggers, and build steps


• Introduction to Jenkins Pipelines
• Creating a basic pipeline using Jenkinsfile
• Pipeline syntax and scripted vs. declarative pipelines

Advanced Jenkins Usage and Integration

• Automated Testing and Notifications
• Integrating automated testing into Jenkins pipelines
• Configuring build notifications (e.g., email, Slack)


• Integrating Jenkins with Other Tools
• Connecting Jenkins with version control systems (like Git)
• Using Jenkins with containerization tools (like Docker)

Jenkins in AIOps and Practical Exercise

• Jenkins in the Context of AIOps
• Discussing the role of Jenkins in automated operations
• Use cases of Jenkins in monitoring, alerting, and auto-remediation


• Hands-On Exercise: Implementing a CI/CD Pipeline
• Participants create a simple CI/CD pipeline relevant to AIOps
• Emphasizing on automated deployment and testing


• Wrap-Up and Q&A Session
• Recap of key concepts and functionalities
• Open floor for final questions and discussions

Introduction to Rundeck and Runbook Automation

• Overview of Rundeck
• Introduction to Rundeck and its significance in AIOps
• Understanding the role of runbook automation in IT operations


• Rundeck Architecture and Key Features
• Core components: Jobs, Nodes, Projects, Commands
• Overview of Rundeck’s UI and basic navigation


• Setting Up Rundeck
• Installation and basic configuration
• Setting up projects and access controls


• Q&A Session
• Addressing initial queries and clarifications

Creating and Managing Jobs in Rundeck

• Defining and Executing Jobs
• Creating your first job in Rundeck
• Configuring job workflows, options, and scheduling


• Advanced Job Features
• Using job plugins for extended functionality
• Handling job outputs and logs

Integrating Rundeck with Other Tools and Services

• Rundeck Integrations
• Integrating with version control systems (e.g., Git)
• Connecting Rundeck with monitoring tools (e.g., Nagios, Splunk)


• API and CLI Usage
• Utilizing Rundeck’s API for automation
• Command-line interface for Rundeck management

Rundeck in AIOps and Practical Exercise

• Applying Rundeck in an AIOps Context
• Case studies or examples of Rundeck used in AIOps scenarios
• Automating routine operations and incident response


• Hands-On Exercise: Implementing a Runbook Automation Scenario
• Participants implement a basic runbook automation task relevant to AIOps
• Emphasizing on automated problem resolution and reporting


• Wrap-Up and Q&A Session
• Recap of key concepts and functionalities
• Open floor for final questions and discussions on practical applications