Tag: gcp

A production-oriented Cloud Run and vLLM design that keeps GPT-OSS private, separates routing from inference, and makes model loading, readiness, concurrency, and rollback explicit.

When a SaaS product should graduate from a flexible Python-first backend into Go, gRPC, Cloud Run, and Google Cloud service boundaries.

A Dataform and BigQuery case study for turning data contracts, release lanes, validation gates, rollback behavior, and cost checks into one governed promotion path.

A sanitized GCP platform case study where compliance, analytics delivery, and ML feature access had to be designed as one release path instead of three disconnected workstreams.

A production-focused Vertex AI post on turning raw data, BigQuery features, online feature serving, model endpoints, monitoring, and retraining into one governed ML loop instead of another platform checklist.

A Vertex AI architecture map for teams that need to decide which Google Cloud AI services belong in the ML lifecycle, where ownership changes hands, and which older assumptions are now unsafe.

A practical deployment guide for running Ollama behind Open WebUI on Cloud Run GPUs without mixing service specs, model storage modes, sidecar startup order, or auth assumptions.

A practical view of data strategy as the operating discipline that connects business goals, governance, KPIs, platforms, analytics, ML, and AI delivery.