Beyond metrics: Extracting actionable insights from Amazon EKS with Amazon Q Business
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📝 Summary
However, it can be very complex to monitor and understand the behavior of enterprise applications, and derive valuable insights from the extensive data produced by an application stack on Amazon EKS. Fortunately, the integration of Amazon EKS with Amazon Q Business provides a robust solution for uncovering actionable insights from your applications. Amazon Q Business is a generative AI–powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. Customers can use this fully managed service to query and analyze data from multiple sources, such as the control plane, data plane, request rates, and application logs. Furthermore, it offers organizations thorough insight into their applications and Kubernetes environments. In this post, we demonstrate a solution that uses Amazon Data Firehose to aggregate logs from the Amazon EKS control plane and data plane, and send them to Amazon Simple Storage Service (Amazon S3). Finally, we use Amazon Q Business and its Amazon S3 connector to synchronize the logs, index the log data in Amazon S3, and enable a chat experience powered by the generative AI capabilities of Amazon Q Business. The following architecture diagram shows the workflow that occurs when deploying the Terraform code that we use in this solution. The following steps detail how the EKS cluster is deployed with the retail sample application. Figure 1: Solution architecture diagram The user deploys the complete infrastructure stack including Amazon Virtual Private Cloud (Amazon VPC) , AWS Identity Access Management (IAM) roles, EKS cluster, and Amazon Q Business using a single Terraform execution. Application traffic flows through the Application Load Balancer (ALB) to the deployed sample retail application running on the EKS cluster. Amazon EKS Control Plane logs stored in Amazon CloudWatch get streamed to Amazon S3 through Amazon Data Firehose.