Automated Edge Device Log Management and Analysis

This workflow automates the collection, processing, and storage of logs from edge devices. It starts with a webhook trigger that captures incoming log data, which is then chunked and processed for semantic understanding using language models. The logs are embedded into vector space for efficient retrieval and stored in a Redis database. Additionally, the workflow allows querying these logs based on semantic similarity, generating insights via conversational AI, and finally logging the processed information into a Google Sheet for record-keeping. This setup is ideal for monitoring, troubleshooting, and analyzing logs from distributed edge devices in real-time, ensuring quick response and data-driven decisions.