Architecting scalable agentic biotech workloads
🔬 This Google Cloud blog describes a three-layer reference architecture for building enterprise-grade, high-compute AI agents for drug discovery. It separates cognitive orchestration from GPU-bound execution and anchors both inside an enterprise governance plane. The post details execution choices (on-prem vs managed), containerized NVIDIA Inference Microservices on GKE, warm pools and preload strategies to avoid cold starts, and patterns for passing heavy payloads by reference. It also outlines Gemini platform governance features—agent identity, gateway, registry, and Model Armor—plus recommended asymmetric gating for reversible and irreversible actions.
