Software Development News

Learn the critical failure points when running LLM inference on Kubernetes, including resource constraints, operator compatibility, security, scalability, and monitoring best practices for production workloads. Running LLM Inference on Kubernetes: What Breaks First

LLM Performance and PCIe Lanes: Key Considerations LLM Performance and PCIe Lanes: Key Considerations

Search vs Deepsearch vs Deep Research Search vs Deepsearch vs Deep Research

Complete guide to Markdown code blocks: fenced blocks, inline code, syntax highlighting, diff formatting, language identifiers, filename display, and Hugo-specific features. Markdown Code Blocks: Complete Guide with Syntax, Languages & Examples

Quick reference to Markdown syntax: headings, bold, italic, lists, links, images, tables, code blocks, blockquotes, task lists, math, and more — with examples for every element. Markdown Cheatsheet: Syntax, Formatting & Structure Quick Reference

Trying to choose between Docker Model Runner and Ollama? We compare performance, GPU support, API compatibility, Docker integration and production readiness to help you decide fast. Docker Model Runner vs Ollama (2026): Which Is Better for Local LLMs?

Choosing the best way to run LLMs locally? Compare Ollama, vLLM, LM Studio, LocalAI and 8+ tools by API support, hardware compatibility, tool calling, and production readiness. Ollama vs vLLM vs LM Studio: Best Way to Run LLMs Locally in 2026?

Learn how to monitor LLM inference in production using Prometheus and Grafana. Track p95 latency, tokens/sec, queue duration, and KV cache usage across vLLM, TGI, and llama.cpp. Includes PromQL examples, dashboards, alerts, Docker & Kubernetes setups. Monitor LLM Inference in Production (2026): Prometheus & Grafana for vLLM, TGI, llama.cpp