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Building today, evolving for tomorrow.
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Building today, evolving for tomorrow.

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Anand-Bora-0001/README.md

A note on accuracy: I pulled your real repositories for this README. observability-platform, Enterprise-Digital-Transformation-Platform, Enterprise-Data-Platform, and HoneyCloud-X (co-authored with Ganesh Kambli) all exist and match the details described below. For the newer repos you listed β€” SentinelGrid-AI, Enterprise-MLOps-Platform, Real-Time-Data-Engineering-Platform, cloud-monitoring-dashboard, Bulk-Certificate-Generator, and the Anand-Bora portfolio repo β€” I could not pull verified details (they weren't reachable via search), so I've written domain-level descriptions from the names/domains you gave rather than inventing tech-stack specifics. Please review and tighten those sections before publishing. I also left the coding-profile badges (LeetCode/GFG/HackerRank/CodeChef) unlinked since I couldn't verify handles.


πŸš€ About Me

name: Anand Bora
role: Software Engineer (Backend & Cloud, AI-Integrated Systems)
education: B.E. Computer Engineering, Savitribai Phule Pune University
based_in: Pune, Maharashtra, India
focus:
  - Multi-service backends with FastAPI
  - Containerized deployments (Docker, Kubernetes)
  - Observability stacks (Prometheus, Grafana, Alertmanager)
  - Practical AI/ML integrations wired into real product flows
  - Cybersecurity-adjacent systems (honeypots, threat classification, SOC tooling)
currently: Python Developer Intern @ AI Adventures LLP
open_to: ["SDE / Backend / Platform internships & grad roles", "Open source", "Hackathons"]

I'm an early-career engineer who ships complete, working systems and documents them properly β€” clean service boundaries, dependency injection over tight coupling, JWT/RBAC done right, and systems that fail loudly instead of silently. I'm not presenting myself as a finished senior engineer β€” I'm a fast-improving builder with nine shipped projects spanning cybersecurity, MLOps, data engineering, and enterprise workflow platforms.



πŸ› οΈ Tech Stack

Languages

Python Java TypeScript JavaScript HTML CSS

Frontend

React Vite Tailwind

Backend & Databases

FastAPI Flask PostgreSQL MySQL MongoDB Redis SQLite

Cloud, DevOps & Tooling

Docker Kubernetes AWS GithubActions Git GitHub Linux VSCode Postman



πŸ—οΈ Architecture & Systems Expertise

graph LR
    A[Client / React + TS] -->|REST / JWT| B(FastAPI Gateway)
    B --> C[Service Layer]
    C --> D[(PostgreSQL)]
    C --> E[(Redis Cache)]
    C --> F[Celery Workers]
    F --> G[LLM / ML Inference]
    B --> H[Prometheus]
    H --> I[Grafana Dashboards]
    H --> J[Alertmanager]
    style A fill:#8B5CF6,color:#fff
    style B fill:#6D28D9,color:#fff
    style C fill:#4C1D95,color:#fff
    style G fill:#A78BFA,color:#000
    style I fill:#2EC866,color:#000
Loading
Area Applied In
Clean Architecture (routers β†’ services β†’ data access) Enterprise DTP, Enterprise Data Platform
Repository Pattern & Service Layer Enterprise Data Platform, Enterprise MLOps Platform
Dependency Injection (FastAPI Depends()) Enterprise DTP, Observability Platform
JWT Authentication & RBAC All featured projects
Microservices decomposition Enterprise Data Platform (catalog / metadata / quality / reporting), SentinelGrid AI
Event-driven / async background processing Enterprise DTP (Celery), HoneyCloud-X (async ML retraining), Real-Time Data Engineering Platform (streaming)
Containerization & orchestration Docker across all projects; Kubernetes manifests in Observability Platform, DTP & MLOps Platform
Observability (metrics, dashboards, alerting) Observability Platform (Prometheus/Grafana/Alertmanager), Cloud Monitoring Dashboard


🧠 AI / ML Expertise

Domain Proficiency Where It's Used
Classical ML (Random Forest, Isolation Forest) β­β­β­β­β˜† HoneyCloud-X threat classification & anomaly detection
Deep Learning (LSTM, 1D-CNN, Autoencoders) β­β­β­β˜†β˜† HoneyCloud-X optional deep-learning threat engine
NLP / Feature Engineering on text payloads β­β­β­β˜†β˜† HoneyCloud-X payload tokenization & entropy scoring
LLM-assisted application features β­β­β­β˜†β˜† Enterprise DTP document summarization, Enterprise Data Platform NL data assistant
MLOps (model lifecycle, retraining pipelines) β­β­β­β˜†β˜† HoneyCloud-X automated 24h retraining, Enterprise MLOps Platform
Data Processing (Pandas, NumPy) β­β­β­β­β˜† Across ML pipelines and data profiling services


πŸ“Œ Featured Projects

πŸ›‘οΈ SentinelGrid AI β€” AI-Powered Cyber Resilience Platform
Aspect Detail
Domain Cybersecurity β€’ AI β€’ Full Stack
Repository Anand-Bora-0001/SentinelGrid-AI

Add your own architecture/stack/security highlights here β€” I couldn't independently verify implementation details for this repo, so keep this section in your own words.

🍯 HoneyCloud-X β€” AI-Powered Honeypot & SOC Intelligence Platform

Co-built with Ganesh Kambli. A honeypot orchestration and SOC intelligence platform that deploys decoy services, captures attacker behavior, and classifies it in real time using classical ML and an optional deep-learning engine.

Aspect Detail
Stack FastAPI, SQLAlchemy, JWT auth, Scikit-Learn, Pandas, NumPy, optional TensorFlow, React + Vite, Recharts
Deception layer Emulated SSH, HTTP, and MySQL decoy services ("shadow nodes") that log intrusion attempts without touching production infrastructure
ML pipeline Random Forest + Isolation Forest for threat scoring (0–100) and zero-day anomaly detection; optional LSTM/1D-CNN/autoencoder deep-learning engine
Automation Background job retrains models every 24 hours (or after 50+ new events) on freshly labeled attack data
Alerting Telegram bot and Resend-based email dispatch for HIGH/CRITICAL events; MITRE ATT&CK technique mapping on alerts
Reporting PDF (ReportLab), Excel/CSV export for SOC-style incident reports
Live Demo honeycloud-frontend.onrender.com
Repository Anand-Bora-0001/HoneyCloud-X

The interesting engineering decision here is honest, not glamorous: heavy libraries like TensorFlow/PyTorch are deliberately excluded from the production requirements.txt because Render's free tier OOMs under their weight β€” so the system falls back cleanly to the Scikit-Learn pipeline in constrained environments instead of crashing.

βš™οΈ Enterprise MLOps Platform
Aspect Detail
Domain AI β€’ MLOps β€’ ML Engineering
Repository Anand-Bora-0001/Enterprise-MLOps-Platform

Add your own model-lifecycle/pipeline/deployment details here β€” same note as above, keep this section in your own words.

🌊 Real-Time Data Engineering Platform
Aspect Detail
Domain Data Engineering β€’ Big Data β€’ Streaming
Repository Anand-Bora-0001/Real-Time-Data-Engineering-Platform

Add your own streaming architecture/pipeline details here.

πŸ›°οΈ Cloud Infrastructure Observability & Monitoring Platform (observability-platform)

A real-time infrastructure observability and incident-response platform built to act as a unified command center for SRE/NOC-style workflows β€” automated alert triage, incident tracking, ticketing, and maintenance-window scheduling.

Aspect Detail
Stack FastAPI, React + TypeScript + Vite, PostgreSQL, Redis, Prometheus, Grafana, Alertmanager, Node Exporter, cAdvisor, Blackbox Exporter
Architecture Split between metric ingestion (Prometheus), visualization (Grafana), and incident routing (Alertmanager β†’ FastAPI webhooks)
Scale Multi-host monitoring with 15s scrape intervals; SLA/MTTR/MTBF tracking at daily/weekly/monthly granularity
Security JWT-based stateless authentication
Deployment Docker Compose for local dev, Kubernetes manifests for HA production
Repository Anand-Bora-0001/cloud-monitoring-dashboard

Built around a genuinely useful ops problem: turning raw metrics into actioned incidents instead of just dashboards nobody watches. The webhook engine checks active maintenance windows before generating incidents, so scheduled downtime doesn't create alert noise.

🏒 Enterprise Digital Transformation Platform

A microservices-based operating system for enterprise workflows β€” combining BPMN 2.0 workflow automation, a configurable no-code business rules engine, agile/Scrum project management, and practical AI document summarization.

Aspect Detail
Stack FastAPI (Python 3.12), React 18 + TypeScript + Vite, PostgreSQL 15 (JSONB), Redis, Celery, MinIO/AWS S3
Architecture Clean Architecture with strict router β†’ service β†’ repository separation; dependency injection via FastAPI Depends()
Scale SLA escalation engine with time-boxed workflow steps; multi-channel dispatch (Email, Teams, Slack, Twilio SMS)
Security Stateless JWT auth, bcrypt password hashing, granular RBAC (Users β†’ Roles β†’ Permissions)
AI Celery background workers call an LLM to summarize stored documents and help optimize workflow execution
DevOps Docker Compose, Kubernetes (Helm charts), GitHub Actions CI/CD, Prometheus/Grafana monitoring
Repository Anand-Bora-0001/Enterprise-Digital-Transformation-Platform

The business rules engine is the centerpiece β€” rules like IF Budget > 1Cr AND Department == 'Finance' β†’ escalate to CFO are configured by end users, not developers. Kafka-based event sourcing and ElasticSearch are on the documented roadmap but not yet built.

πŸ—‚οΈ Enterprise Data Governance & Analytics Platform

A microservices platform for enterprise metadata management, data quality monitoring, and business glossaries β€” modeled on the workflows of tools like Purview and Collibra.

Aspect Detail
Stack FastAPI microservices (catalog, metadata, quality, reporting, analytics services), React + TypeScript, PostgreSQL, Redis
Architecture Repository Pattern, Service Layer, Dependency Injection, event-driven metadata scanning
Scale Automated metadata discovery across PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, S3, CSV/Excel/Parquet
Security JWT + granular RBAC, immutable audit logs, GDPR-oriented PII detection and data classification tagging
Data Quality Deep profiling (null %, duplicate %, distinct %, statistical summaries), configurable validation rules
AI Natural-language data assistant that answers questions like "what datasets contain Customer ID?" by querying catalog metadata
Repository Anand-Bora-0001/Enterprise-Data-Platform

The steward workflow (Data Owner β†’ Data Steward β†’ Approver β†’ Published) is deliberately modeled on real enterprise data-governance processes β€” the part of the system that would actually matter to a Chief Data Officer.

πŸ“„ Bulk Certificate Generator
Aspect Detail
Domain Flask β€’ Automation β€’ PDF Generation
Stack Flask, ReportLab, CSV bulk processing, Google Sheets API
What it does Generates certificates in bulk from customizable templates, driven by CSV input β€” the same automation later extended during the AI Adventures LLP internship
Repository Anand-Bora-0001/Bulk-Certificate-Generator
πŸ’Ό Portfolio Website
Aspect Detail
Domain React β€’ Portfolio
Live Site anand-bora.vercel.app
Repository Anand-Bora-0001/Anand-Bora


πŸ’Ό Internship Experience

Python Developer Intern β€” AI Adventures LLP

  • Developed and maintained backend applications using Python and Flask
  • Built an automated Bulk Certificate Generator with PDF generation and CSV-based bulk processing
  • Automated workflows using the Google Sheets API to reduce manual effort and improve operational efficiency
  • Enhanced and maintained the Moodle LMS, implementing new features and fixing bugs
  • Developed and integrated REST APIs for seamless frontend–backend communication
  • Optimized application performance, debugged issues, and improved code quality
  • Implemented GitHub Actions workflows for automated build and deployment
  • Collaborated with the dev team using Git, participating in code reviews and feature development

Tech Stack: Python Β· Flask Β· FastAPI Β· REST APIs Β· Google Sheets API Β· Git Β· GitHub Actions Β· HTML Β· CSS Β· JavaScript Β· SQLite/PostgreSQL Β· Pandas Β· ReportLab Β· CSV Processing Β· JWT Authentication



πŸŽ“ Earlier Projects

Project Description
Railway Management System MySQL + Flask project for railway operations management
Cloud-SaaS-System Python-based SaaS system project
Contact-Management-App Python contact management application
Ecommerce-App Java e-commerce application


πŸ† Achievements

Recognition Details
Nine-project builder Shipped nine independent platforms spanning cybersecurity, MLOps, data engineering, observability, and enterprise workflow automation
Collaborative engineering Co-built HoneyCloud-X with a fellow developer, including a live production deployment
Industry experience Python Developer Intern at AI Adventures LLP β€” shipped automation tooling and LMS features used in production
Consistent GitHub activity Active public repository history spanning backend, full-stack, and applied-ML projects


πŸ“Š GitHub Analytics




πŸ“ˆ Contribution Activity



🐍 Contribution Snake

To make the snake animation actually render, add a GitHub Actions workflow (Platane/snk) to your profile repo β€” see github-contribution-grid-snake for the one-file setup.



🎯 Current Focus

learning:
  - Kubernetes in production (HA, autoscaling)
  - Event-driven architecture with Kafka
  - System design fundamentals

building:
  - Deeper AI integrations across existing platforms
  - MLOps pipelines for model deployment at scale
  - Real-time streaming data pipelines

exploring:
  - Multi-tenant SaaS architecture
  - Cybersecurity automation & SOC tooling

open_to:
  - Software Engineering roles
  - Backend / Platform Engineering roles
  - Graduate programs
  - Hackathons and open-source collaboration


πŸ“« Connect

Portfolio Gmail LinkedIn GitHub Phone



"Building today, evolving for tomorrow."

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