Applied AI for IT Operations

Solve common challenges in IT operations using the power of AI. Review use cases in the world of IT ops and learn how to apply AI technologies to address key problems.

Introduction

• Artificial intelligence and its many uses
• What you should know

1. IT Operations and AI

• Introduction to ITOps
• ITOps challenges
• AI and ITOps
• ITOps use cases overview
• Setting up the exercise files

2. Use Case 1: Root Cause Analysis

• What is root cause analysis?
• Classification with deep learning
• Data for root cause analysis (RCA)
• Preprocessing RCA data
• Building a classification model with Keras
• Predicting root causes with Keras

3. Use Case 2: Self-Help Service Desk

• Automating helpdesk functions
• Latent semantic analysis (LSA) and latent semantic indexing (LSI)
• Data for the help desk
• Building a document vector
• Creating the LSI model
• Recommending FAQs

4. Use Case 3: Service Load Forecasting

• Time series forecasting
• Recurrent neural network (RNN) and long short-term memory (LSTM)
• Preparing sequence data
• Building an LSTM model with Keras
• Testing the time series model
• Forecasting future service loads with Keras

5. Other ITOps Use Cases

• Anomaly detection
• Predicting alerting
• Incident categorization
• Spam filtering
• Network traffic analysis

6. Generative AI for ITOps

• Generative AI review
• Text generation with LLMs
• Log data extraction
• Incident summarization
• Documentation self-help chatbot
• Code generation for scripts
• Code generation example

7. ITOps Best Practices

• Model development best practices
• Using machine learning platforms
• Model serving best practices
• Security and privacy best practices

Conclusion

• Next steps