Books

Your agent passed every load test and timed out in production anyway. This free practitioner's guide shows why the traditional performance playbook breaks for agentic AI, and what replaces it: latency budgets, bounded autonomy, token SLOs, and production-grade observability, from a performance engineering and observability architect with two decades in production.

This book is all about testing and closing the gap between infrastructure health and output quality, and how easily that gap can be filled for weeks by a failure that's gone unnoticed.This book looks at the less obvious side of the problem. In the next few chapters, we're going to run 41 experiments on one application. About half of them will give you a result that the system doesn't report. It's not a dig at anyone's engineering, since the systems in question are competently built and mostly behave well.

Break things on purpose, before production does it for you. Load tests that mirror reality and chaos experiments you can defend to management.

Slow SQL queries waste time, increase costs, and limit scalability. Mastering SQL Performance Optimization teaches you how to analyze execution plans, optimize queries and indexes, and solve real-world performance bottlenecks across today's leading database platforms.

Find out in minutes what obligations you face under the EU AI Act - before it becomes a problem.

Learn software testing the way it’s actually done: by doing it. The Test Analyst Field Workbook guides you step-by-step through every part of a test analyst’s job — from reading requirements and designing test cases, to logging defects, running regression cycles, and helping decide when software is ready to release. With real examples, reusable templates, and dozens of practice exercises, this book turns theory into practical skill you can use from day one.

Master the engineering principles behind Unsloth to fine-tune Large Language Models on limited hardware. Discover technical workflows for 4-bit quantization, custom Triton kernels, and Direct Preference Optimization. This guide covers the full lifecycle, including context expansion and production deployment via GGUF and vLLM. A rigorous reference for developers seeking to maximize LLM performance on consumer-grade GPUs.

A builder's guide to AI-powered performance testing, from a multi-agent platform that turns 25 minutes of manual correlation into 75 seconds, written by the engineer who built it.