K8sGPT is a tool for scanning Kubernetes clusters, diagnosing issues in simple English, and enriching data with AI. It helps with workload health analysis, security CVE review, and more.
MIT researchers have developed a method using large language models to detect anomalies in complex systems without the need for training. The approach, called SigLLM, converts time-series data into text-based inputs for the language model to process. Two anomaly detection approaches, Prompter and Detector, were developed and showed promising results in initial tests.
Apply sound data-based anomalous behavior detection, diagnose the root cause via object detection concurrently, and inform the user via SMS.
