Mohlo by se vám také líbit

Více informací o knize Production Data Engineering for AI

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 66 bodů

Anotace knihy

Production Data Engineering for AI: Master Layout-Aware Parsing, Semantic Chunking, and Sub-10ms Database Retrieval

Why do AI applications that perform flawlessly in isolated development sandboxes collapse under real-world enterprise traffic? When software prototypes meet production networks, the illusion of simplicity disappears. Data engineering teams routinely face fragmented context windows, race conditions from concurrent agents, and skyrocketing cloud bills caused by unoptimized vector stores. If your AI platform suffers from lagging response times or broken API payloads, the issue is not your prompt engineering-it is your underlying data infrastructure.

Production Data Engineering for AI provides the rugged, architectural blueprint required to build resilient, high-throughput data engines. This practical guide bypasses superficial wrappers to address the physical realities of scaling AI infrastructure. By aligning software logic with raw silicon constraints, you will learn how to design deterministic pipelines that remain stable, secure, and cost-effective under heavy enterprise workloads.

How do you maintain absolute system integrity when millions of parallel queries hit your cluster? This book delivers actionable strategies and production-grade architectures to optimize your AI platform from the ground up.

What you will master inside:

• Layout-Aware Parsing & Semantic Chunking: Isolate and extract clean metadata from complex documents to eliminate fragmented context data.

• Sub-10ms Database Retrieval: Configure HNSW indexes and pgvector parameters to maintain lightning-fast query velocities under load.

• Distributed State Locks: Deploy high-throughput concurrency guardrails to prevent parallel agent updates from corrupting shared databases.

• Tiered Storage Architectures: Design cost-effective hot-and-cold storage configurations using Apache Iceberg and LanceDB.

• Granular Cost Allocation: Track multi-tenant resource consumption and token footprints to eliminate runaway cloud expenses.

Stop troubleshooting fragile wrappers and start engineering for scale. Secure your copy of Production Data Engineering for AI today and build a bulletproof data infrastructure.

Parametry knihy

• Plný název: Production Data Engineering for AI
• Podnázev: Master Layout-Aware Parsing, Semantic Chunking, and Sub-10ms Database Retrieval
• Autor: Landen Howe
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 332
• EAN: 9798198012608
• ID: 52513115
• Nakladatelství: Independently published
• Hmotnost: 579 g
• Rozměry: 254 × 178 × 18 mm
• Datum vydání: 21. May 2026

---

---

---