Last reviewed 2026-10-29 UTC
Dokumen dalam Google Cloud Well-Architected Framework ini menjelaskan prinsip dan rekomendasi untuk membantu Anda mendesain, membangun, dan mengelola workload AI dan ML di Google Cloud yang memenuhi sasaran operasional, keamanan, keandalan, biaya, dan performa Anda.
Target audiens untuk dokumen ini mencakup pengambil keputusan, arsitek, administrator, developer, dan operator yang mendesain, membangun, men-deploy, dan memelihara workload AI dan ML di Google Cloud.
Halaman berikut menjelaskan prinsip dan rekomendasi yang khusus untuk AI dan ML, untuk setiap pilar Well-Architected Framework:
- Perspektif AI dan ML: Keunggulan operasional
- Perspektif AI dan ML: Keamanan
- Perspektif AI dan ML: Keandalan
- Perspektif AI dan ML: Pengoptimalan biaya
- Perspektif AI dan ML: Pengoptimalan performa
Kontributor
Penulis:
- Benjamin Sadik | AI and ML Specialist Customer Engineer
- Charlotte Gistelinck, PhD | Partner Engineer
- Filipe Gracio, PhD | Customer Engineer, Spesialis AI/ML
- Isaac Lo | AI Business Development Manager
- Kamilla Kurta | GenAI/ML Specialist Customer Engineer
- Mohamed Fawzi | Benelux Security and Compliance Lead
- Rick (Rugui) Chen | AI Infrastructure Field Solutions Architect
- Sannya Dang | AI Solution Architect
Kontributor lainnya:
- Daniel Lees | Cloud Security Architect
- Gary Harmson | Principal Architect
- Jose Andrade | Customer Engineer, SRE Specialist
- Kumar Dhanagopal | Developer Solusi Lintas Produk
- Marwan Al Shawi | Partner Customer Engineer
- Nicolas Pintaux | Customer Engineer, Application Modernization Specialist
- Radhika Kanakam | Program Lead, Google Cloud Well-Architected Framework
- Ryan Cox | Principal Architect
- Samantha He | Technical Writer
- Stef Ruinard | Field Solutions Architect AI Generatif
- Wade Holmes | Global Solutions Director
- Zach Seils | Networking Specialist