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raviadapa-ai/README.md

πŸ‘‹ Hi, I'm Ravi

πŸš€ AIOps Engineer | Platform & Reliability Engineering | Agentic AI for Operations

I build intelligent operational systems at the intersection of:

  • βš™οΈ Platform Engineering & Distributed Systems
  • 🌐 Infrastructure, Networking & Reliability
  • πŸ“Š Observability (Logs, Metrics & Traces)
  • πŸ€– Agentic AI, AIOps & Operational Intelligence

🧠 What I'm Building

I am focused on building production-style AIOps and Agentic Operations platforms that transform operational telemetry into actionable intelligence.

Current areas of focus:

  • Statistical Noise Reduction
  • Signal Correlation & Incident Detection
  • Evidence-Based Root Cause Analysis (RCA)
  • Splunk MCP Investigation Workflows
  • Human-in-the-Loop Remediation
  • AI-Assisted Operational Intelligence
  • Reliability Engineering & Platform Operations

βš™οΈ Tech Stack

Infrastructure & Platform Engineering

  • Linux
  • Networking & Communication Systems
  • Docker
  • Kubernetes (Learning Path)
  • Platform Engineering Concepts
  • Site Reliability Engineering (SRE)

Backend & APIs

  • Python
  • FastAPI
  • REST APIs
  • PostgreSQL
  • JSON Event Pipelines

Observability & AIOps

  • Splunk Enterprise
  • Splunk MCP Server
  • Logs, Metrics & Traces
  • Incident Correlation
  • Root Cause Analysis
  • Operational Intelligence
  • Anomaly Detection
  • Forecasting & Predictive Analytics

Data & AI

  • NumPy
  • Pandas
  • Scikit-Learn
  • Ollama
  • LLM Workflows
  • Agentic AI Systems

Engineering

  • Git
  • GitHub
  • VS Code
  • Jupyter Lab
  • WSL Linux

πŸš€ Featured Projects

πŸ”₯ Splunk Agentic Ops Incident Copilot

An AgenticOps platform that reduces operational noise, correlates signals into incidents, performs MCP-driven investigations, generates evidence-based RCA, and enables human-governed remediation through Splunk operational intelligence.

Key Features:

  • Statistical Noise Reduction
  • Signal Correlation
  • MCP-Powered Investigation
  • Evidence-Based RCA
  • Human-in-the-Loop Remediation
  • Splunk Write-Back
  • Incident Lifecycle Management
  • Operational Intelligence Dashboard

πŸ”₯ System Metrics Anomaly Detection

A lightweight observability simulator that generates infrastructure telemetry, performs anomaly detection using statistical techniques, and correlates incidents into actionable signals.

πŸ‘‰ https://github.com/raviadapa-ai/system-metrics-anomaly-detection


πŸ”₯ Python for AI/ML β€” AIOps Edition

Engineering-focused repository covering:

  • Log Analysis
  • Event Correlation
  • Infrastructure Telemetry
  • Statistical Analysis
  • Foundations of Machine Learning for AIOps

πŸ‘‰ https://github.com/raviadapa-ai/python-for-ai-ml


πŸ”₯ AIOps Monitoring Platform (Private)

Production-style AIOps platform focused on:

  • Telemetry Collection
  • Correlation
  • RCA
  • AI-Assisted Investigation
  • Operational Automation

🎯 Career Direction

I am pursuing roles and opportunities in:

  • AIOps Engineering
  • Site Reliability Engineering (SRE)
  • Platform Engineering
  • AI Infrastructure Engineering
  • Operational Intelligence Platforms
  • Technical Co-Founder Opportunities

πŸ“ˆ Engineering Philosophy

  • Systems Thinking Over Tool Thinking
  • Reliability Is a Feature
  • Observability Enables Intelligence
  • Correlation Is More Valuable Than Raw Alerts
  • AI Should Augment Human Decision-Making
  • Automation Requires Governance

⚑ Current Mission

Building next-generation AgenticOps platforms that transform:

Logs + Metrics + AI + Operational Context β†’ Actionable Operational Intelligence


πŸ“« Connect


πŸš€ Platform Engineering β†’ Observability β†’ Agentic AI β†’ AIOps

Pinned Loading

  1. mini-aiops-monitoring-agent mini-aiops-monitoring-agent Public

    A lightweight AIOps monitoring agent that analyzes logs in real-time, detects failures, and performs automated self-healing actions.

    Python

  2. system-metrics-anomaly-detection system-metrics-anomaly-detection Public

    System metrics anomaly detection pipeline using NumPy. Simulates CPU, memory, and latency data, detects anomalies using statistical methods, and correlates incidents.

    Python

  3. python-for-ai-ml python-for-ai-ml Public

    Hands-on Python for AIOps β€” covers Python fundamentals, NumPy & Pandas through real-world scenarios: log parsing, server metrics analysis, anomaly detection & incident reporting. Scikit-learn comin…

    Jupyter Notebook

  4. AIOps-research AIOps-research Public

    Forked from OpsPAI/awesome-AIOps

    A curated list of awesome academic researches and industrial materials about Artificial Intelligence for IT Operations (AIOps).