Why SREs need AI and ML for observability and IT resilience

David Hope

Director of Product Marketing

Elastic

Ayan Ray

Sr. Partner Solutions Architect, Generative AI

AWS

Discover how Elastic Observability and AWS are collaborating to elevate customer experience and IT resilience in your application environment. In this webinar, we'll explore how AI and machine learning can revolutionize your incident resolution process through contextual observability and Amazon Bedrock.

Elastic Observability offers a comprehensive solution that provides accurate AI-driven insights and delivers extensive visibility across your entire system. Our unified view encompasses logs, metrics, traces, and business data, all stored in a single, signal-agnostic data store. This approach eliminates blind spots and enhances operational efficiency.

We'll demonstrate how our open, OpenTelemetry-first solution seamlessly integrates with your existing technology stack and adapts to your evolving needs. Learn about our AI-driven insights powered by retrieval augmented generation (RAG) and both out-of-the-box and custom ML models, enabling faster issue identification and resolution.

Join us to discover how you can reduce SRE toil and future-proof your observability strategy with Elastic and AWS. Experience the next generation of observability with AI-powered Elastic Observability and see how it can transform your operations.

Highlights

• The advantages of open and unified full-stack observability
• Key AWS AI and ML use cases for SREs
• Leveraging Amazon Bedrock and LLMs for proactive service management
• Integrating Amazon Bedrock with Elastic Observability

Additional resources

• AWS VPC Flow log analysis with GenAI in Elastic
• Wait… Elastic Observability monitors metrics for AWS services in just minutes?
• Using the Elastic Agent to monitor Amazon ECS and AWS Fargate with Elastic Observability
• Getting started with the Elastic AI Assistant for Observability and Amazon Bedrock