🚀 Data Engineer Agent for Observability Tasks

Overview

Welcome to the Data Engineer Agent Project! This project aims to automate data ingestion pipelines and streamline Business Intelligence (BI) reporting using StateFlow and Large Language Models (LLMs). We're also exploring automation for DevOps teams by generating real-time incident response playbooks based on observability alerts and codebase knowledge. All powered by advanced AI, this agent will reduce manual intervention and boost system efficiency.

Key Features

• Automated Data Pipelines: No more manual data ingestion! We'll automate data workflows with tools like Apache NiFi and Airflow.
• SQL Query Generation: Translate business-level requests into SQL queries using LLMs and datasets like Spider.
• Business Intelligence Insights: Effortlessly generate BI reports using real-time data.
• Incident Response Automation: DevOps teams get instant playbooks based on live system behavior and code knowledge.
• Enterprise-Grade Robustness: Scaling for multi-cloud environments while ensuring trustworthiness and accuracy in complex data ecosystems.

Why This Matters

Managing data pipelines and handling BI requests can be time-consuming. With our Data Engineer Agent, we aim to achieve:

• 📊 Instant BI Reports: LLMs do the heavy lifting to provide quick, actionable insights.
• 🤖 Automated Playbooks: Real-time response playbooks for DevOps, generated on-the-fly based on system alerts.
• 🔍 Less Manual Work: Automated workflows mean you focus on strategy, not maintenance.

Research Focus

1. Automating Data Pipelines: Ensuring seamless data ingestion and management.
2. Streamlining BI Reporting: Transforming natural language requests into SQL queries.
3. Incident Response Automation: Generating playbooks from real-time observability data.
4. Tackling LLM Limitations: Mitigating hallucinations and ensuring data trustworthiness.
5. Enterprise Integration: Scaling across multi-cloud and complex data environments.

Tech Stack

• LLMs: Powering natural language to SQL transformations.
• StateFlow: Managing complex workflows.
• Work In Progress: Project is under construction, this section will be updated accordingly :D

🧠 Built On Top of Prior Work

We leverage advanced models like SQLNet, Codex, and frameworks like Spider to handle natural language-to-SQL translations, improving upon their limitations to manage complex queries and dynamic schemas. In DevOps, we’re taking observability tools like Prometheus to the next level with automated response actions.