Build self-service AWS Health analytics to find actionable health insights with AI agents powered by Amazon Bedrock | Amazon Web Services
On a typical Monday morning, an enterprise operations team receives multiple AWS Health notifications about Amazon Linux 2 end-of-life, RDS version deprecations, and EC2 instance retirements across 50+ accounts. Without self-service analytics, the team has no way to quickly identify the events that affect production systems, the events that require immediate action versus long-term planning, and the business impact of each event category.
Operations teams also spend time waiting for Technical Account Managers (TAMs) to interpret health events, adding delays to critical operational decisions. The result is time spent on reactive firefighting rather than innovation.
In this post, we show you how to build Chaplin(Customer Health and Planned Lifecycle Intelligence Nexus), an open source solution that uses AI agents exposed through the Model Context Protocol (MCP) to provide self-service health event analytics. With Chaplin, teams can ask questions in natural language directly from MCP-compatible AI assistants and receive precise,...
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