LLM Production Ops

Practical guides for engineers shipping LLMs to production — inference engines, cost optimization, observability, and deployment. No fluff, just what works.

Inference Optimization Deep Dives

Battle-tested techniques for faster, cheaper LLM serving

Speculative Decoding

How draft-verify decoding delivers 2-3x throughput with zero quality loss. The math, the variants (Medusa, EAGLE), and production deployment.

Inference

Multi-Head Latent Attention (MLA)

DeepSeek's KV cache compression breakthrough — how MLA cuts memory 93% vs standard MHA while keeping quality.

Attention

Ring Attention

Scaling context to millions of tokens across GPUs. Sequence parallelism, the ring topology, and when it beats naive sharding.

Long Context

KV Cache Quantization (FP8/INT4)

How FP8 and INT4 KV cache quantization slash memory 2-8x with <1% quality drop. Implementation in vLLM and SGLang.

Memory
Calculators & Tools

KV Cache Calculator

Compute the exact KV cache memory footprint for any model — layers, heads, sequence length, batch size. Plan your GPU memory budget.

Tool

Quantization Calculator

Compare model size and memory across FP16, BF16, INT8, and INT4. See exactly how much you save before deploying.

Tool
Inference Engines

LLM Inference Engines Hub

Production guide to vLLM, SGLang, TGI, and TensorRT-LLM. Start here for engine selection and deployment.

Hub

vLLM vs SGLang vs TGI: 2026 Benchmark

Head-to-head comparison on H100 — throughput, latency, VRAM, and when to pick each engine for production serving.

Comparison

How to Deploy vLLM in Production

Docker setup, tensor parallelism, GPU memory tuning, and the OpenAI-compatible API.

Tutorial

SGLang RadixAttention Explained

The radix-tree prefix cache behind SGLang's 29% throughput edge on agents and RAG.

Deep Dive
Gateways & Cost Optimization

LLM Gateways & Cost Hub

Route requests across providers, cache redundant calls, and cut API spend 70-85%. Start here for gateway selection.

Hub

LiteLLM vs Portkey vs OpenRouter

Three-way comparison — routing, fallbacks, cost control, observability, self-hosting, and pricing for 2026.

Comparison

LLM Cost Optimization Playbook

The 5 levers that cut API spend 70-85%: routing, semantic caching, context compaction, compression, budget governance.

Playbook

How to Self-Host LiteLLM

Production Docker Compose setup with PostgreSQL, team keys, budgets, cost tracking, and rate limits.

Tutorial
Observability & Evals

LLM Observability & Evals Hub

Trace every call, evaluate quality at scale, catch hallucinations. LangSmith, Langfuse, Phoenix — start here.

Hub

LangSmith vs Langfuse vs Phoenix

Tracing, evals, pricing, open-source status — which LLM observability platform to pick for 2026.

Comparison

How to Self-Host Langfuse

Production Docker Compose setup for open-source LLM observability — tracing, evaluation, dashboards.

Tutorial

LLM-as-a-Judge Methodology

Using a strong model to score outputs — biases, human correlation, and trustworthy scoring practices.

Deep Dive

LiteLLM vs Portkey vs OpenRouter

LLM gateway comparison — routing, fallbacks, cost control, and self-hosting trade-offs.

In queue

LLM Cost Optimization Playbook

The 5 levers that cut API spend 70-85% — routing, semantic caching, prompt compression, and budget governance.

In queue

LangSmith vs Langfuse vs Phoenix

LLM observability platform comparison — tracing, evals, pricing, and self-host options for production agents.

In queue