Welcome to my blog! I'm Rahul, your guide on an exciting journey through the worlds of Python, deep learning, and cybersecurity. Whether you're here to learn, explore, or deepen your understanding, you're in the right place. Together, we'll navigate complex concepts and make them accessible — no prior expertise required! 🌟🤗
Latest Posts
Projects
Neural Nets
Architected and implemented a robust blog infrastructure on Google Cloud Platform (GCP), leveraging Cloud Run, Cloud Storage, and Cloud CDN to ensure scalable and secure content delivery. Integrated BigQuery for in-depth analytics, Cloud Logging for real-time monitoring, and Cloud Storage as a DataSink for optimized performance tracking. This cloud-native solution guarantees high availability and enables data-driven insights.
Compliance Guide
Created a detailed compliance guide for a fictional digital business, focusing on essential regulatory frameworks and cybersecurity standards. The guide provides actionable recommendations for areas like data protection, PCI compliance, risk management, and employee training, ensuring businesses align their operations with industry regulations to maintain a strong security posture.
Project Cipher
Developed and deployed a Retrieval-Augmented Generation (RAG) web app on Compute Engine, efficiently delivering contextually relevant information about the Mission Impossible film series. The app integrates document retrieval, semantic embeddings, and generative AI to match queries with accurate content using cosine similarity. Optimized backend performance with Gunicorn, configured as a WSGI server, and served through Nginx acting as a reverse proxy. Communication between Nginx and Gunicorn is handled via a Unix socket, ensuring a high-performance, secure connection for real-time queries. Necessary ports have been opened for ingress traffic to facilitate smooth communication and access.
Network Guardian Nexus
Built Network Guardian Nexus, a real-time network monitoring tool that offers in-depth insights into network traffic. Features include automated anomaly detection, customizable alerts, and intuitive data visualization. The system can process large amounts of data and seamlessly integrates with other tools for proactive issue resolution and optimization.
Project Graphil
Designed an interactive platform to simplify technical concepts through dynamic visualizations. It offers interactive graphs and diagrams on topics like Python, Linux, Networking, Google Cloud, and AI. Built with React, Graphil serves as a powerful tool for learners and educators to understand complex topics through visual learning.
CloudNet Analytics
Built a high-performance, security-hardened distributed log aggregation and analytics system on Google Cloud. A custom Virtual Private Cloud (VPC) with meticulously segmented web (x.y.1.0/24), app (x.y.2.0/24), and processor (x.y.3.0/24) subnets, each hosting a dedicated virtual machine (VM) and defined by specific CIDR blocks, ensures robust network isolation and adherence to zero-trust security principles. Firewall rules enforce strict access control, allowing only preconfigured IPs. A streamlined log ingestion pipeline securely transfers logs over SSH, processes data using Python, and integrates with Cloud Storage and Pub/Sub. Cloud Functions (1st gen.), triggered by Pub/Sub events, automate structured data ingestion into BigQuery. A Flask-based API provides controlled external access to processed logs and analytics