Python

This project is Phase 2 of the Cloud Costs Monitor platform. Where Phase 1 focused on automated data collection, anomaly detection, and scheduled reporting, Phase 2 adds a real-time conversational interface: users open a browser, type a question like “What did the team X spend on cloud Y last quarter?”, and the system autonomously writes and executes the SQL, verifies the numbers, and returns a grounded answer — all within seconds. ...

This project is a self-hosted, multi-cloud cost management system for AWS, Azure, GCP, and Kubernetes (via a third-party cost attribution platform) that I designed and built from scratch. It runs daily to collect granular cost line items at the service × region × account level, detects spend anomalies, sends configurable alerts, and produces a rich suite of reports in HTML, Excel, and PDF — from executive summaries and rolling-window trend views to per-owner and per-department drilldowns and an annual budget tracker. All data is stored locally in a local database, keeping the system lightweight and self-contained with no external SaaS dependencies. ...

Introduction DNS leaks are commonly discussed as a privacy concern when using VPNs or other privacy tools. However, the real danger lies in data exfiltration from protected environments, even those with external access locked down in and out. The critical vulnerability is this: even if your DNS query goes to your private DNS resolver first, it eventually reaches the public internet to resolve unknown domains. If an attacker crafts a domain with a specifically configured DNS server, they can log these queries and extract sensitive data that was embedded in the subdomain. ...

This guide covers setting up Ollama (Open Large Language Model) in a Proxmox LXC container with GPU passthrough and creating a simple web interface for easy interaction. Overview We’ll deploy Ollama in a resource-constrained LXC environment with: Intel UHD Graphics GPU acceleration llama3.2:1b model (~1.3GB) Lightweight Python web interface Auto-starting services Prerequisites Proxmox VE host Intel integrated graphics (UHD Graphics) At least 4GB RAM allocated to LXC 40GB+ storage for container Step 1: Container Setup Check Available GPU Resources First, verify GPU availability on the Proxmox host: ...