RAG TimeSeriesDB AIOps App: Querying & Format Influx DB Data for Prompt ...

🧠 RAG TimeSeriesDB AIOps App: Querying & Format Influx DB Data for Prompt Creation for LLMs | Part23

🚀 Welcome to Part 23 of our RAG Series! We're pushing the boundaries of our multi-source RAG AI application beyond static documents and databases to integrate dynamic, real-time knowledge from Time-Series Databases (TSDBs) like InfluxDB. Building on our explanation of why time-series data requires a different RAG approach (Part 22) and setting up InfluxDB with data (Part 21), we now tackle the crucial step of querying InfluxDB from Python and formatting the results for our Large Language Model.

In this video, We are extracting & formatting TIMESERIES data for Payment Service api latency to build prompt for LLMs to help System monitoring, Automated Insights, Enhanced Decision making. This will help Site Reliability Engineers who are interested in knowing system performance especially for API latency Cause, probability of occurring and other performance issues related to latency. This step-by-step tutorial is perfect for developers and data enthusiasts aiming to harness the power of time-series databases with RAG powered AI application to make intelligent decision way ahead of time.

🔧/📦 We'll cover:

✅ Setting up and configuring InfluxDB for time-series data.

✅ Implements robust health checks with retry logic to handle transient network issues.

✅ Executes Flux queries to retrieve specific time-series data (like payment service API latency) and analyzes monitoring data.

✅ Formatting data outputs for seamless integration with Large Language Models (LLMs) to Leverage RAG techniques to enhance AIOps capabilities 

🎯 This is the start of building a truly intelligent AI application that can reason over time-sensitive data! We have copy of real time data for payment service with regular spikes so now we need to do most challenging & interesting part to integrate with RAG powered AI Application to do not only System monitoring but also help SREs or concerned group aware with intelligent patterns, trends about stored timeseries data for services.

👍 If this video helps you understand querying and formatting InfluxDB data for LLMs, please give it a thumbs up, share it, and subscribe for the next part where we build the natural language handler!