EmerAgents on Google Cloud: Vertex AI, BigQuery, and Fact-to-Artifact Pipelines
How EmerSoftware and EmerAgents integrate with Google Cloud: Vertex AI and Gemini under policy, BigQuery/Pub/Sub for ROI and events, Apigee/Cloud Run factory APIs, and Cloud IAM perimeters.
By Emerson Amorim · Founder and Principal Software Engineer
Google Cloud shines when analytics and model serving are already first-class. EmerAgents turns Vertex inferences and BigQuery facts into auditable FactoryRuns — business fact → agent decision → versioned artifact — with IAM-scoped tools.
Google Cloud × EmerAgents control plane
- 01Google Cloudsystems of record / cloud
- 02ContractAPI · events · IAM
- 03EmerAgentsroles · HITL · audit
- 04Factoryspec → release
AI — Vertex AI and Gemini
Primary services: Vertex AI, Gemini.
Inference and grounding use controlled corpora. EmerAgents owns tool orchestration, evaluation, and HITL — Vertex remains the model platform.
- Grounding sources are owned datasets, not the entire lake.
- Model garden swaps do not rewrite integration contracts.
- Safety settings + EmerAgents allowlists = stacked controls.
Data — BigQuery, Pub/Sub, Dataflow
Primary services: BigQuery, Pub/Sub, Dataflow.
Analytics and streaming fuel diagnosis and ROI loops. Agents read contracted marts; mutations go through APIs, not DML from the model.
- Pub/Sub topics mirror EmerAgents handoffs between roles.
- Dataflow prepares features/context without exposing PII to prompts.
- BigQuery metrics close the Operations → Strategy feedback loop.
Integration — Apigee, Cloud Run, Workflows
Primary services: Apigee, Cloud Run, Workflows.
Factory APIs and long-running workflows host connectors and control-plane endpoints with SLAs.
- Apigee enforces quotas and consumer identities per tool.
- Cloud Run scales adapters with traffic.
- Workflows encode compensation for failed FactoryRuns.
Identity — Cloud IAM and Secret Manager
Primary services: Cloud IAM, Secret Manager.
Same perimeter model as AWS/Azure: service accounts per adapter, secrets out of prompts, human approvers separately authenticated.
- Split read/write service accounts.
- Workload Identity for GKE/Cloud Run where applicable.
- No long-lived keys in agent memory.
Commercial fit
Highest fit when BigQuery is the system of insight and Vertex/Gemini is the preferred runtime; EmerAgents supplies the enterprise control plane the raw model stack does not.
What EmerAgents will not do
- No UI bots clicking SAP GUI, Salesforce screens, or Oracle Forms disguised as “agents.”
- No LLM with standing admin credentials or API keys pasted into prompts.
- No rip-and-replace of S/4, Salesforce, or ERP “because AI” — orchestrate the investment already paid.
Ready to accelerate your enterprise software?
Talk with EmerSoft about the software factory, EmerAgents, and SAP, AWS, and Azure integrations — with accelerated delivery at enterprise standard.
LinkedIn · Emerson Amorim
Vertex + BigQuery without a control plane is a science project.
EmerAgents on GCP: • Vertex/Gemini under policy • BigQuery as grounded fact — not prompt stuffing • Apigee contracts + Pub/Sub handoffs • IAM perimeter for every tool https://www.emersoftware.com.br/en/blog/emeragents-google-cloud-integration — Emerson Amorim, EmerSoftware
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