Using AI/ML to Drive Operational Excellence: Keys to AWS Optimization - Episode 4

Overview

Discover how to leverage Amazon CloudWatch's AI/ML capabilities for enhanced telemetry analytics and application monitoring, gaining deeper operational insights through data-driven investigations.

Syllabus

• Introduction to AI/ML in AWS for Operational Excellence
Overview of AI/ML capabilities in cloud environments
The role of AI/ML in enhancing operational excellence
• Understanding Amazon CloudWatch
Introduction to Amazon CloudWatch
Key features and functionalities
• AI/ML Capabilities in Amazon CloudWatch
Utilizing AI/ML for telemetry analytics
Machine Learning models in CloudWatch
Automating anomaly detection and alert management
• Enhanced Application Monitoring
Setting up performance and error monitoring
Leveraging AI/ML for application health insights
Case studies: CloudWatch in action
• Data-Driven Investigations
Techniques for in-depth operational insights
Using AI/ML for root cause analysis
Interactive dashboards and visualizations
• Best Practices for AWS Optimization
Operational best practices with AI/ML
Cost optimization strategies with CloudWatch
Security and compliance considerations
• Practical Exercises & Hands-On Labs
Configuring CloudWatch with AI/ML capabilities
Real-world scenario analyses
Monitoring and response workflows
• Conclusion and Future Trends
Summary of key learnings
Emerging trends in AI/ML for cloud operations
Resources for further study and development

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Subjects

Programming