// Generated by orrery. Edit the diagram spec and re-render instead of editing this file. import { type SVGProps, useId } from "react"; export default function MLOpsOnGoogleCloudWithAgentPlatform(props: SVGProps) { const uid = useId().replace(/[^A-Za-z0-9_-]/g, ""); return ( MLOps on Google Cloud with Agent Platform MLOps on Google Cloud with Agent Platform. 18 components in 5 groups. Connections: Data scientists to Source repository (push); Source repository to Cloud Build (build trigger); Cloud Build to Artifact Registry (push); Artifact Registry to Cloud Run functions (pipeline template); Cloud Scheduler to Pub/Sub (publish); Cloud Logging to Pub/Sub (publish); Pub/Sub to Cloud Run functions (subscribe); Cloud Run functions to Agent Platform Pipelines (run); BigQuery to Validate and transform (query); Feature Store to Validate and transform (fetch features); Validate and transform to Managed Training; Managed Training to Evaluate and validate; Evaluate and validate to Model Registry (register); Model Registry to Endpoint (deploy); Endpoint to Model Monitoring (request logs); Cloud Logging to Model Monitoring (drift alerts); Agent Platform Pipelines to Cloud Storage; Agent Platform Pipelines to Vertex ML Metadata. MLOPS ON GOOGLE CLOUD WITH AGENT PLATFORM Cloud Build ships the pipeline; Gemini Enterprise Agent Platform (formerly Vertex AI) trains, registers and serves the model, and drift alerts retrain it PUSH BUILD TRIGGER PUSH PIPELINE TEMPLATE PUBLISH PUBLISH PUBLISH SUBSCRIBE SUBSCRIBE RUN RUN QUERY QUERY FETCH FEATURES REGISTER REGISTER DEPLOY DEPLOY REQUEST LOGS REQUEST LOGS DRIFT ALERTS DRIFT ALERTS GITHUB GOOGLE CLOUD PROJECT ML-PROD AGENT PLATFORM PIPELINES SERVING DATA SCIENTISTS SOURCE REPOSITORY Pipeline and component code CLOUD BUILD Test and compile ARTIFACT REGISTRY Images and pipeline template CLOUD SCHEDULER CLOUD LOGGING Alert log filter PUB/SUB Trigger topic CLOUD RUN FUNCTIONS Submits PipelineJob BIGQUERY Training data FEATURE STORE VALIDATE AND TRANSFORM Dataflow MANAGED TRAINING Train and tune EVALUATE AND VALIDATE Dataflow CLOUD STORAGE Pipeline artifacts VERTEX ML METADATA Lineage MODEL REGISTRY ENDPOINT Online inference MODEL MONITORING Skew and drift DELIVERY, TRAINING AND INFERENCE PIPELINE TRIGGERS ARTIFACTS AND LINEAGE ); }