Automated API Stats Charting and Logging Workflow

This n8n workflow automates the process of capturing, analyzing, and logging API statistics, while also providing alerts for any errors. It begins with a webhook trigger that receives incoming data related to API usage or metrics. The workflow then splits the data into manageable chunks using a Text Splitter node, and generates semantic embeddings with OpenAI’s embedding model. These embeddings are stored in a Pinecone vector database, enabling efficient similarity searches.

The workflow includes querying Pinecone to retrieve relevant vectors and processing them through a language model (via the Chat Model node) to analyze or summarize the data. A RAG (Retrieval-Augmented Generation) agent then consolidates the insights and updates a Google Sheet with the status information. If any errors occur during the process, a Slack alert notifies the relevant team members.

This setup is ideal for monitoring API performance, generating reports, or maintaining logs in a structured manner, ensuring data-driven decision-making and prompt issue detection.