Certifications

Introduction

The “AiOps Certified Professional” (AIOCP) designation typically refers to a certification program aimed at individuals who want to demonstrate their expertise in the field of Artificial Intelligence for IT Operations (AIOps). This certification would likely cover a range of topics pertinent to AIOps, including but not limited to machine learning, data analytics, automation, monitoring, and incident response within IT operations.

Purpose of AIOCP Certification:

  • Validate Skills: It serves to validate the skills and knowledge of professionals in using AI technologies and practices to improve IT operations.
  • Industry Recognition: It provides recognition within the industry, indicating a professional level of competency in the AIOps domain.

Potential Content of AIOCP Program:

  • Fundamentals of AI and Machine Learning: Understanding the basics of AI and ML, how they apply to IT operations.
  • Data Management and Analysis: Techniques for managing and analyzing large volumes of IT data.
  • Automation in IT Operations: Using AI to automate routine tasks, incident responses, and workflow optimization.
  • Monitoring and Observability: Implementing AI-driven monitoring tools and practices for better visibility into IT systems.
  • Incident Management and Response: Leveraging AI for quicker and more effective incident resolution.
  • Integration of AI Tools and Platforms: Best practices for integrating various AI tools (like machine learning libraries, monitoring tools, etc.) into IT environments.
  • Case Studies and Real-World Applications: Learning from real-world scenarios and case studies where AIOps has been successfully implemented.

Target Audience:

  • IT professionals, system administrators, and operations engineers seeking to integrate AI into their workflows.
  • Professionals aiming to specialize in the field of AIOps.
  • Teams and organizations looking to enhance their IT operations with AI technologies.

Format and Requirements:

  • The program may include a mix of theoretical learning, practical exercises, and case studies.
  • It might require passing an examination that tests the candidate’s knowledge and understanding of AIOps principles and practices.

Benefits of AIOCP:

  • Professional Growth: Enhances career opportunities and professional growth in the rapidly evolving field of IT operations.
  • Skills Enhancement: Helps in staying current with the latest AI technologies and practices in IT operations.
  • Organizational Impact: Enables professionals to contribute more effectively to their organizations by optimizing IT operations through AI.

What you’ll learn

  • AIOps Foundations
  • AIOps Implementation Roadmap
  • AIOps Project workflow
  • AIops Deployment Types & storages
  • AIops Industry Use cases
  • AIOps Vs DevOps Vs MLops Lifec cycle
  • AIOps Popular Solutions
  • AIOps Challenges
  • AIops Tools
  • AIOps Best Practices
  • AIOps supporting DevOps & SRE

Day 1: Understanding of AiOps

Half Day: Overview of AiOps

  1. Benefits of Artificial Intelligence for IT Operations (AIOps)                          
  2. Artificial Intelligence for IT Operations (AIOps) Overview              
  3. Benefits of AIOps                          
  4. Use Case: Evaluating the Benefits of AIOps                        
  5. Implications of AIOps for Business                         
  6. Implications of AIOps for Business                         
  7. Use Case: Implications of AIOps for Business                     
  8. Key Capabilities of Artificial Intelligence for IT Operations (AIOps)                            
  9. Key Capabilities of AIOps                           
  10. Use Case: Understanding Key Capabilities of AIOps                        
  11. Key Dimensions of IT Operations Monitoring                     
  12. IT Operations Monitoring: Overview and Relevance                       
  13. Understanding Key Dimensions of IT Operations Monitoring                      
  14. Key Dimensions of IT Operations Monitoring and AIOps                
  15. Use Case: Understanding Key Dimensions of IT Operations Monitoring
  16. AIops Deployment Types & storages
  17. AIops Industry Use cases
  18. AIOps Vs DevOps Vs MLOps Life cycle
  19. AIOps Challenges
  20. AIOps Popular Solutions
  21. AIOps Best Practices
  22. AIOps supporting DevOps & SRE

Second Half: Metrics collection: Prometheus, Grafana

Hour 1: Introduction to Prometheus

  • Overview of Prometheus (15 mins)
  • Brief history and purpose
  • Key features and architecture
  • Basic Installation and Configuration (15 mins)
  • Quick setup guide
  • Overview of configuration files and settings
  • Understanding Metrics and Data Model (15 mins)
  • Introduction to Prometheus metrics
  • Data types and structure
  • Q&A Session (15 mins)

Hour 2: Basic Monitoring with Prometheus

  • Instrumentation and Metrics Collection (20 mins)
  • How to add Prometheus metrics to an application
  • Best practices for metric collection
  • Introduction to Prometheus Query Language (PromQL) (20 mins)
  • Basic syntax and queries
  • Creating simple alerts
  • Hands-On Exercise (20 mins)
  • Quick setup of basic monitoring for a demo application

Hour 3: Introduction to Grafana and Dashboard Creation

  • Overview of Grafana (15 mins)
  • Key features and integration with Prometheus
  • Setting Up Grafana (15 mins)
  • Connecting Grafana to Prometheus
  • Creating Basic Dashboards in Grafana (15 mins)
  • Introduction to dashboard creation and configuration
  • Overview of visualization types
  • Hands-On Exercise (15 mins)
  • Participants create a basic dashboard for the demo application

Hour 4: Advanced Features and AIOps Integration

  • Advanced Dashboard Techniques in Grafana (20 mins)
  • Dynamic dashboards with variables
  • Setting up basic alerts in Grafana
  • Integrating Prometheus and Grafana with AIOps (20 mins)
  • How these tools fit into an AIOps strategy
  • Brief on AIOps concepts relevant to monitoring and observability
  • Wrap-Up and Q&A (20 mins)
  • Recap of key concepts
  • Open floor for questions and discussion on real-world applications

Day 2:  Data Collection and Monitoring Tools

 

First Half: Log management: ELK Stack (Elasticsearch, Logstash, Kibana)

Hour 1: Introduction to the ELK Stack

  • Overview of ELK Stack (15 mins)
  • Introduction to Elasticsearch, Logstash, and Kibana
  • Role of ELK in AIOps
  • Basic architecture and flow of data within the ELK Stack
  • Introduction to Elasticsearch (15 mins)
  • Understanding Elasticsearch basics: Indexes, Documents, and Nodes
  • Basic Elasticsearch operations: CRUD (Create, Read, Update, Delete)
  • Q&A Session (15 mins)
  • Address initial queries and clarifications

Hour 2: Deep Dive into Logstash and Data Ingestion

  • Understanding Logstash (20 mins)
  • Logstash fundamentals: Input, Filter, and Output plugins
  • Configuring Logstash for data ingestion
  • Hands-On Exercise: Setting Up Logstash (20 mins)
  • Walkthrough of setting up a basic Logstash pipeline
  • Ingesting sample data into Elasticsearch

Hour 3: Kibana for Data Visualization and Analysis

  • Introduction to Kibana (20 mins)
  • Kibana Dashboard, Visualization, and Discover features
  • Connecting Kibana to Elasticsearch
  • Hands-On Exercise: Creating Visualizations and Dashboards (20 mins)
  • Participants create basic visualizations and dashboards using the ingested data
  • Exploration of Kibana’s features relevant to AIOps

Hour 4: ELK Stack in AIOps and Advanced Topics

  • ELK Stack in the Context of AIOps (20 mins)
  • Integrating ELK with AIOps workflows
  • Real-world use cases of ELK in AIOps (e.g., anomaly detection, performance monitoring)
  • Advanced ELK Features (20 mins)
  • Brief on advanced Elasticsearch queries
  • Overview of X-Pack features (security, alerting, machine learning)
  • Wrap-Up and Q&A (20 mins)
  • Recap of key points
  • Open Q&A session to discuss practical applications and address any remaining questions

Second Half: Event streaming: Kafka

Hour 1: Introduction to Apache Kafka

  • Overview of Kafka (15 mins)
  • 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 (15 mins)
  • Setting up a basic Kafka environment
  • Overview of Kafka configuration files
  • Kafka Producers and Consumers (15 mins)
  • Understanding Producers and Consumers
  • Writing basic producers and consumers
  • Q&A Session (15 mins)
  • Address initial queries and clarifications

Hour 2: Kafka in Depth – Topics, Partitions, and Replication

  • Deep Dive into Kafka Topics and Partitions (20 mins)
  • Creating and managing Topics
  • Understanding Partitions for scalability and reliability
  • Kafka Replication and Fault Tolerance (20 mins)
  • Concept of replication for high availability
  • Leader and follower partitions

Hour 3: Kafka Streams and Kafka Connect

  • Introduction to Kafka Streams (20 mins)
  • Understanding stream processing in Kafka
  • Basics of Kafka Streams API
  • Kafka Connect for Integration (20 mins)
  • Overview of Kafka Connect
  • Setting up connectors for data import/export

Hour 4: Kafka in AIOps and Practical Exercise

  • Using Kafka in an AIOps Context (20 mins)
  • 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 (20 mins)
  • Building a simple pipeline for data ingestion and processing
  • Monitoring and managing Kafka performance
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and best practices
  • Open floor for final questions and discussions

Day 3: Data Collection and Monitoring Tools

First Half: Machine learning libraries: TensorFlow

Hour 1: Introduction to TensorFlow and Machine Learning Basics

  • Overview of TensorFlow (15 mins)
  • Introduction to TensorFlow and its relevance in AIOps
  • Core features and capabilities of TensorFlow
  • Machine Learning Fundamentals (15 mins)
  • Brief overview of machine learning concepts
  • How TensorFlow supports machine learning operations
  • Setting Up TensorFlow (15 mins)
  • Installation and setup of TensorFlow
  • Introduction to TensorFlow’s programming model
  • Q&A Session (15 mins)
  • Address initial queries and clarifications

Hour 2: TensorFlow Basics – Operations, Graphs, and Sessions

  • TensorFlow Core Concepts (20 mins)
  • Understanding Tensors, Operations, Graphs, and Sessions
  • Building simple computation graphs
  • Hands-On Exercise: Basic TensorFlow Operations (20 mins)
  • Creating and executing a simple TensorFlow program
  • Introduction to TensorFlow data types and operations

Hour 3: Building Machine Learning Models with TensorFlow

  • Introduction to Neural Networks in TensorFlow (20 mins)
  • Basic concepts of neural networks
  • Building a simple neural network in TensorFlow
  • Practical Exercise: Building a Basic ML Model (20 mins)
  • Step-by-step construction of a machine learning model for a simple problem (e.g., regression or classification)

Hour 4: TensorFlow in AIOps and Advanced Topics

  • TensorFlow in the Context of AIOps (20 mins)
  • Discussing the role of TensorFlow in AIOps (e.g., anomaly detection, predictive maintenance)
  • Real-world examples of TensorFlow applications in AIOps
  • Advanced TensorFlow Features (20 mins)
  • Overview of advanced features like TensorFlow Extended (TFX), Keras for deep learning, and distributed training
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and best practices
  • Open floor for final questions and discussions on practical TensorFlow applications in AIOps

Second Half: Data analysis tools: Jupyter Notebook

Hour 1: 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

Hour 2: Data Analysis Basics in Jupyter Notebook

  • Data Import and Manipulation (20 mins)
  • Importing data from various sources (CSV, databases)
  • Basic data manipulation using Pandas
  • Hands-On Exercise: Working with Data (20 mins)
  • Participants practice importing and manipulating a sample dataset

Hour 3: Advanced Data Analysis and Visualization

  • Advanced Data Analysis Techniques (20 mins)
  • Exploring more complex data manipulation and transformation
  • Introduction to time series analysis relevant to AIOps
  • Data Visualization in Jupyter (20 mins)
  • Using Matplotlib and Seaborn for data visualization
  • Creating plots and charts relevant to AIOps data (e.g., performance metrics)

Hour 4: Jupyter Notebooks in AIOps Context and Best Practices

  • Applying Jupyter Notebooks in AIOps (20 mins)
  • 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 (20 mins)
  • Tips for effective use of Jupyter Notebooks
  • Overview of advanced features like JupyterLab, extensions
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and functionalities
  • Open floor for final questions and in-depth discussions

Day 4:  Analysis and Automation

First Half: Configuration management tools: Ansible

Hour 1: Introduction to Ansible and Configuration Management

  • Overview of Ansible (15 mins)
  • Introduction to Ansible and its role in AIOps
  • Key features and advantages of using Ansible for configuration management
  • Ansible Architecture and Components (15 mins)
  • Understanding Ansible architecture: Playbooks, Roles, Tasks, Modules, Inventory
  • YAML syntax basics
  • Setting Up Ansible (15 mins)
  • Installation and basic setup of Ansible
  • Setting up an inventory file
  • Q&A Session (15 mins)
  • Addressing initial queries and clarifications

Hour 2: Basic Playbooks and Ad-hoc Commands

  • Writing Your First Ansible Playbook (20 mins)
  • Creating a simple playbook
  • Defining tasks and running the playbook
  • Ansible Ad-hoc Commands (20 mins)
  • Introduction to ad-hoc commands in Ansible
  • Practical examples of common ad-hoc commands

Hour 3: Advanced Ansible Features

  • Variables, Templates, and Roles (20 mins)
  • Using variables and templates for dynamic configurations
  • Organizing playbooks with roles
  • Error Handling and Debugging (20 mins)
  • Best practices for error handling in Ansible playbooks
  • Using Ansible’s debugging tools

Hour 4: Ansible in AIOps and Hands-On Exercise

  • Applying Ansible in an AIOps Context (20 mins)
  • 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 (20 mins)
  • Participants work on creating a basic pipeline using Ansible
  • Automating a simple operational task relevant to AIOps
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and functionalities
  • Open floor for final questions and in-depth discussions

Second Half:  Infrastructure-as-code software tool: Terraform

Hour 1: Introduction to Terraform and Infrastructure as Code

  • Overview of Terraform (15 mins)
  • Introduction to Terraform and its role in infrastructure automation
  • Key features and benefits of using Terraform in AIOps
  • Terraform Basics (15 mins)
  • Understanding Terraform’s syntax and structure
  • Core concepts: Providers, Resources, Variables, State
  • Setting Up Terraform (15 mins)
  • Installing Terraform
  • Basic setup and configuration
  • Q&A Session (15 mins)
  • Addressing initial queries and clarifications

Hour 2: Writing Terraform Configuration

  • Creating Your First Terraform Configuration (20 mins)
  • Writing a basic Terraform configuration file
  • Managing infrastructure as code
  • Understanding Terraform Workflow (20 mins)
  • The Terraform workflow: init, plan, apply, destroy
  • Hands-on demo of managing a simple infrastructure

Hour 3: Advanced Terraform Concepts

  • Modules and Remote State (20 mins)
  • Using modules to organize and reuse code
  • Managing state in complex environments
  • Dynamic Infrastructure with Terraform (20 mins)
  • Dynamic configurations with loops and conditionals
  • Integrating with cloud providers (AWS, Azure, GCP)

Hour 4: Terraform in AIOps and Practical Exercise

  • Terraform in an AIOps Context (20 mins)
  • Real-world use cases of Terraform in AIOps
  • Automating and maintaining AIOps infrastructure with Terraform
  • Hands-On Exercise: Implementing an AIOps Scenario (20 mins)
  • Participants implement a small-scale infrastructure setup relevant to AIOps
  • Practicing Terraform commands and configurations
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and best practices
  • Open floor for final questions and discussions on practical applications

Day 5: CI/CD and Automation

First Half: Continuous integration tools: Jenkins

Hour 1: Introduction to Jenkins and Continuous Integration

  • Overview of Jenkins (15 mins)
  • Introduction to Jenkins and its importance in CI/CD pipelines
  • The role of Jenkins in AIOps
  • Jenkins Architecture and Key Concepts (15 mins)
  • Understanding Jenkins architecture: master, agents, plugins
  • Core concepts: Jobs, Builds, Plugins, Pipelines
  • Setting Up Jenkins (15 mins)
  • Installing and configuring Jenkins
  • Navigating the Jenkins interface
  • Q&A Session (15 mins)
  • Addressing initial queries and clarifications

Hour 2: Building Jobs and Basic Pipelines in Jenkins

  • Creating Your First Jenkins Job (20 mins)
  • Setting up a freestyle project
  • Configuring source code management (SCM), build triggers, and build steps
  • Introduction to Jenkins Pipelines (20 mins)
  • Creating a basic pipeline using Jenkinsfile
  • Pipeline syntax and scripted vs. declarative pipelines

Hour 3: Advanced Jenkins Usage and Integration

  • Automated Testing and Notifications (20 mins)
  • Integrating automated testing into Jenkins pipelines
  • Configuring build notifications (e.g., email, Slack)
  • Integrating Jenkins with Other Tools (20 mins)
  • Connecting Jenkins with version control systems (like Git)
  • Using Jenkins with containerization tools (like Docker)

Hour 4: Jenkins in AIOps and Practical Exercise

  • Jenkins in the Context of AIOps (20 mins)
  • 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 (20 mins)
  • Participants create a simple CI/CD pipeline relevant to AIOps
  • Emphasizing on automated deployment and testing
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and functionalities
  • Open floor for final questions and discussions

Second Half: Runbook Automation Platform: Rundeck

Hour 1: Introduction to Rundeck and Runbook Automation

  • Overview of Rundeck (15 mins)
  • Introduction to Rundeck and its significance in AIOps
  • Understanding the role of runbook automation in IT operations
  • Rundeck Architecture and Key Features (15 mins)
  • Core components: Jobs, Nodes, Projects, Commands
  • Overview of Rundeck’s UI and basic navigation
  • Setting Up Rundeck (15 mins)
  • Installation and basic configuration
  • Setting up projects and access controls
  • Q&A Session (15 mins)
  • Addressing initial queries and clarifications

Hour 2: Creating and Managing Jobs in Rundeck

  • Defining and Executing Jobs (20 mins)
  • Creating your first job in Rundeck
  • Configuring job workflows, options, and scheduling
  • Advanced Job Features (20 mins)
  • Using job plugins for extended functionality
  • Handling job outputs and logs

Hour 3: Integrating Rundeck with Other Tools and Services

  • Rundeck Integrations (20 mins)
  • Integrating with version control systems (e.g., Git)
  • Connecting Rundeck with monitoring tools (e.g., Nagios, Splunk)
  • API and CLI Usage (20 mins)
  • Utilizing Rundeck’s API for automation
  • Command-line interface for Rundeck management

Hour 4: Rundeck in AIOps and Practical Exercise

  • Applying Rundeck in an AIOps Context (20 mins)
  • Case studies or examples of Rundeck used in AIOps scenarios
  • Automating routine operations and incident response
  • Hands-On Exercise: Implementing a Runbook Automation Scenario (20 mins)
  • Participants implement a basic runbook automation task relevant to AIOps
  • Emphasizing on automated problem resolution and reporting
  • Wrap-Up and Q&A Session (20 mins)
  • Recap of key concepts and functionalities
  • Open floor for final questions and discussions on practical applications