Program Outline: AI-Powered DevOps (AIOps)#
Duration:#
5 Days
Course Audience:#
DevOps Leads, Support Leads, Support Managers
Target Unit:#
Delivery CoE, Product, Internal Applications
Course Outline#
Day 1: Introduction to AIOps#
Morning Sessions 9:00 AM to 1:00 PM#
1. Session 1 - Foundations of AIOps (9:00 AM - 10:30 AM)
- What is AIOps?
- Evolution of AI in DevOps
- Key Benefits and Challenges
2. Session 2 - Core Concepts and Components of AIOps (10:45 AM - 1:00 PM)
- Data Sources in AIOps (Logs, Metrics, Events)
- Machine Learning and AI in DevOps
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
3. Session 3 - AIOps Tools Overview (2:00 PM - 3:30 PM)
- Popular AIOps Platforms (Splunk, Dynatrace, Moogsoft)
- Overview of Open-Source AIOps Tools
4. Session 4 - Case Studies and Industry Examples (3:45 PM - 5:00 PM)
- Real-World Success Stories of AIOps
Day 2: Data and Machine Learning for AIOps#
Morning Sessions 9:00 AM to 1:00 PM#
5. Session 5 - Data Preparation for AIOps (9:00 AM - 10:30 AM)
- Collecting and Cleaning Data for Analysis
- Importance of Data Quality
6. Session 6 - Machine Learning Models in AIOps (10:45 AM - 1:00 PM)
- Predictive Models for Incident Management
- Anomaly Detection Algorithms
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
7. Session 7 - Hands-On: Building Anomaly Detection Models (2:00 PM - 3:30 PM)
- Setting Up the Environment
- Training and Evaluating Models
8. Session 8 - Challenges in Applying ML to DevOps (3:45 PM - 5:00 PM)
- Model Drift and Retraining
- Overcoming Data Silos
Day 3: AIOps for Monitoring and Incident Management#
Morning Sessions 9:00 AM to 1:00 PM#
9. Session 9 - AI for Continuous Monitoring (9:00 AM - 10:30 AM)
- Monitoring Tools Powered by AI
- Metrics to Monitor in DevOps
10. Session 10 - Incident Detection and Resolution with AIOps (10:45 AM - 1:00 PM)
- Automated Root Cause Analysis
- Proactive Incident Resolution
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
11. Session 11 - Hands-On: Automating Alerts and Notifications (2:00 PM - 3:30 PM)
- Setting Up Alerting Systems
- Integrating AI for Prioritizing Alerts
12. Session 12 - Best Practices for AI-Driven Monitoring (3:45 PM - 5:00 PM)
- Designing Scalable Monitoring Architectures
- Ensuring Low False Positive Rates
Day 4: Automating DevOps Workflows with AIOps#
Morning Sessions 9:00 AM to 1:00 PM#
13. Session 13 - AI for CI/CD Pipelines (9:00 AM - 10:30 AM)
- Optimizing Build and Deployment Processes
- AI-Driven Code Quality Analysis
14. Session 14 - Automating Remediation and Rollbacks (10:45 AM - 1:00 PM)
- Self-Healing Systems
- Automated Rollbacks for Failures
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
15. Session 15 - Hands-On: Automating a CI/CD Pipeline (2:00 PM - 3:30 PM)
- Building AI-Powered CI/CD Workflows
- Testing Deployment Automation
16. Session 16 - Governance and Compliance in AIOps (3:45 PM - 5:00 PM)
- Ensuring Compliance with Automated Systems
- AI for Audit Trails
Day 5: Scaling and Advancing AIOps#
Morning Sessions 9:00 AM to 1:00 PM#
17. Session 17 - Scaling AIOps Across the Organization (9:00 AM - 10:30 AM)
- Integrating AIOps with Existing Systems
- Cross-Team Collaboration with AIOps
18. Session 18 - Emerging Trends and Technologies in AIOps (10:45 AM - 1:00 PM)
- AI Advancements Impacting DevOps
- Exploring Future Use Cases
Lunch 1:00 PM to 2:00 PM
Afternoon Sessions 2:00 PM to 5:00 PM#
19. Session 19 - Capstone Project: Building an End-to-End AIOps Workflow (2:00 PM - 4:00 PM)
- Group Activity: Solve a DevOps Challenge Using AIOps
- Presenting Solutions and Feedback
20. Session 20 - Wrap-Up and Next Steps (4:00 PM - 5:00 PM)
- Recap of Key Learnings
- Q&A and Certification Distribution
Key Outcomes:#
- Understand the principles and tools of AIOps.
- Leverage AI to optimize monitoring, alerting, and incident resolution.
- Automate CI/CD pipelines and remediation tasks.
- Design scalable, AI-integrated DevOps workflows.
Recommended Pre-Course Preparation:#
- Familiarity with basic DevOps concepts and tools.
- Review popular AIOps platforms and their features.
- Explore examples of AI in IT operations.
Materials Provided:#
- Course slides and notes.
- Access to trial AIOps tools.
- Sample scripts and workflows.
- Certificate of Completion.
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