What's new in the Architecture Center

(New guide) Stream logs from Google Cloud to Datadog: Provides an architecture to send log event data from across your Google Cloud ecosystem to Datadog Log Management. The architecture is accompanied by a deployment guide.

(New guide) Infrastructure for a RAG-capable generative AI application using Vertex AI and Vector Search: Describes how to design infrastructure for a generative AI application with retrieval-augmented generation (RAG) by using Vector Search.

(New guide) Cross-Cloud Network inter-VPC connectivity using VPC Network Peering: Describes how to configure hub-and-spoke Cross-Cloud Network using VPC Network Peering.

(New guide) Deploy and operate generative AI applications: Describes how you can adapt DevOps and MLOps processes to develop, deploy, and operate generative AI applications on existing foundation models.

(New guide) Migrate from AWS Lambda to Cloud Run: Describes how to design, implement, and validate a plan to migrate from AWS Lambda to Cloud Run.

(New series) Architecture Framework: AI and ML perspective: Describes principles and recommendations that are specific to AI and ML, for each pillar of the Architecture Framework: operational excellence, security, reliability, cost optimization, and performance optimization.

(New guide) Enterprise application on Compute Engine VMs with Oracle Exadata in Google Cloud: Provides a reference architecture for an application that's hosted on Compute Engine VMs with connectivity to Oracle Cloud Infrastructure (OCI) Exadata databases in Google Cloud.

(New guide) Business continuity with CI/CD on Google Cloud: Learn how to plan and implement business continuity and disaster recovery (DR) for the CI/CD process.

(New guide) Migrate from Amazon RDS and Amazon Aurora for PostgreSQL to Cloud SQL and AlloyDB for PostgreSQL: Describes how to design, implement, and validate a plan to migrate from Amazon Relational Database Service (RDS) or Amazon Aurora for PostgreSQL to Cloud SQL.

(New guide) Scalable BigQuery backup automation: Build a solution to automate recurrent BigQuery backup operations at scale, with two backup methods: BigQuery snapshots and exports to Cloud Storage. This architecture is accompanied by a deployment guide.

(New guide) Enterprise application with Oracle Database on Compute Engine: Provides a reference architecture to host an application that uses an Oracle database, deployed on Compute Engine VMs.

(New guide) Select a managed container runtime environment: Learn about managed runtime environments and assess your requirements to choose between Cloud Run and GKE Autopilot.

(New guide) Use generative AI for utilization management: A reference architecture for health insurance companies to automate prior authorization (PA) request processing and improve their utilization review (UR) processes.

(New guide) Migrate from Amazon RDS and Amazon Aurora for MySQL to Cloud SQL for MySQL: Describes how to design, implement, and validate a plan to migrate from Amazon RDS or Amazon Aurora to Cloud SQL for MySQL.

(New guide) Manage and scale networking for Windows applications that run on managed Kubernetes: Discusses how to manage networking for Windows applications that run on Google Kubernetes Engine using Cloud Service Mesh and Envoy gateways. This reference architecture is accompanied by a deployment guide.

(New guide) Architect your workloads: Design resilient, single-region environments on Google Cloud.

(New guide) From edge to multi-cluster mesh: Globally distributed applications exposed through GKE Gateway and Cloud Service Mesh: Describes exposing applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh.

(New guide) From edge to multi-cluster mesh: Deploy globally distributed applications through GKE Gateway and Cloud Service Mesh: Provides the steps needed to deploy applications externally through Google Kubernetes Engine (GKE) Gateways running on multiple GKE clusters within a service mesh.

(New guide) Migrate from AWS to Google Cloud: Migrate from Amazon RDS for SQL Server to Cloud SQL for SQL Server: Describes how to design, implement, and validate a plan to migrate from Amazon Relational Database Service (RDS) to Cloud SQL for SQL Server.

(New guide: 1 of 4) Cross-Cloud Network for distributed applications: Provides an overview about how you can design Cross-Cloud Network for distributed applications.

(New guide 2 of 4) Network segmentation and connectivity for distributed applications in Cross-Cloud Network: Describes how to design the network segmentation structure and connectivity of Cross-Cloud Network for distributed applications.

(New guide 3 of 4) Service networking for distributed applications in Cross-Cloud Network: Describes how to design Cross-Cloud Network service networking for distributed applications.

(New guide 4 of 4) Network security for distributed applications in Cross-Cloud Network: Describes how to design Cross-Cloud Network security for distributed applications.

(New guide) Build an ML vision analytics solution with Dataflow and Cloud Vision API: Deploy a Dataflow pipeline to process large-scale image files with Cloud Vision. Dataflow stores the results in BigQuery so that you can use them to train BigQuery ML pre-built models. This architecture is accompanied by a reference architecture and a deployment guide.

(New guide) Global deployment with Compute Engine and Spanner: Learn how to architect a multi-tier application that runs on Compute Engine VMs and Spanner in a global topology on Google Cloud.

(New guide) C3 AI architecture on Google Cloud: Develop applications using C3 AI and Google Cloud.

(New guide) Use Google Cloud Armor, load balancing, and Cloud CDN to deploy programmable global front ends: Provides an architecture that uses a global front end incorporating Google Cloud best practices to help scale, secure, and accelerate the delivery of internet-facing applications.

(New guide) Infrastructure for a RAG-capable generative AI application using GKE: Design the infrastructure to run a generative AI application with retrieval-augmented generation (RAG) using GKE, Cloud SQL, and open source tools like Ray, Hugging Face, and LangChain.

(New guide) Model development and data labeling with Google Cloud and Labelbox: Provides guidance for building a standardized pipeline to help accelerate the development of ML models.

(New guide) Jump Start Solution: Generative AI RAG with Cloud SQL: Deploy a retrieval augmented generation (RAG) application with vector embeddings and Cloud SQL.

(New guide) Build and deploy generative AI and machine learning models in an enterprise: Describes the generative AI and machine learning blueprint, which deploys a pipeline for creating AI models.

(New guide) Jump Start Solution: Generative AI Knowledge Base: Demonstrates how to build an extractive question-answering (EQA) pipeline to produce content for an internal knowledge base.

(New guide) Cross-silo and cross-device federated learning on Google Cloud: Provides guidance to help you create a federated learning platform that supports either a cross-silo or cross-device architecture.

(New guide) Design storage for AI and ML workloads in Google Cloud: Select the recommended storage options for your AI and ML workloads.

(New guide) Configure networks for FedRAMP and DoD in Google Cloud: Provides configuration guidance to help you comply with design requirements for FedRAMP High and DoD IL2, IL4, and IL5 when you deploy Google Cloud networking policies.

(New guide) Infrastructure for a RAG-capable generative AI application using Vertex AI: Design infrastructure to run a generative AI application with retrieval-augmented generation (RAG) to help improve the factual accuracy and contextual relevance of LLM-generated content.

(New guide) Single-zone deployment on Compute Engine: Provides a reference architecture for a multi-tier application that runs on Compute Engine VMs in a single Google Cloud zone and describes the design factors to consider when you build a single-zone architecture.

(New guide) Regional deployment on Compute Engine: Architect a multi-tier application that runs on Compute Engine VMs in multiple zones within a Google Cloud region.

(New guide) Use RIOT Live Migration to migrate to Redis Enterprise Cloud: Migrate from Redis compatible sources like Redis Open Source (Redis OSS), AWS ElastiCache, and Azure Cache for Redis to a fully managed Redis Enterprise Cloud instance in Google Cloud using the Redis Input and Output Tool (RIOT) Live Migration service. This architecture is accompanied by a deployment guide and an assessment guide.

(New guide) Import logs from Cloud Storage to Cloud Logging: Import logs that were previously exported to Cloud Storage back to Cloud Logging. This architecture is accompanied by a deployment guide.

(New guide) Okta user provisioning and single sign-on: Set up federated user provisioning and single sign-on using Okta.

(New guide) Multi-regional deployment on Compute Engine: Reference architecture for a multi-region, multi-tier topology on Compute Engine VMs and a third-party database.

(New guide) Deploy an enterprise developer platform on Google Cloud: Provides a blueprint to help enterprises set up a developer platform for building and managing container-based applications in Google Cloud.

(New guide) Jump Start Solution: Stateful app with zero downtime deployment on Compute Engine: Update a live app without a noticeable disruption by using the Stateful app with zero downtime deployment on Compute Engine app.

(New guide) Jump Start Solution: Stateful app with zero downtime deployment on GKE: Update a live app without a noticeable disruption by using the Stateful app with zero downtime deployment on GKE app.

(New Guide: 1 of 3) Build hybrid and multicloud architectures using Google Cloud: Provides practical guidance on planning and architecting your hybrid and multi-cloud environments using Google Cloud.

Adds new content and revises existing content.

(New Guide: 2 of 3) Hybrid and multicloud architecture patterns: Discusses common hybrid and multicloud architecture patterns, and describes the scenarios that these patterns are best suited for.

Adds new content and revises existing content.

(New Guide: 3 of 3) Hybrid and multicloud secure networking architecture patterns: Discusses several common secure network architecture patterns that you can use for hybrid and multicloud architectures.

Adds new content and revises existing content.

(New guide) Data transformation between MongoDB Atlas and Google Cloud: Data transformation between MongoDB Atlas as the operational data store and BigQuery as the analytics data warehouse.

(New series) Migrate across Google Cloud regions: Start preparing your workloads and data for migration across Google Cloud regions.

• (New guide) Design resilient single-region environments on Google Cloud
• (New guide) Prepare data and batch workloads for migration across regions

(New guide) Set up an embedded finance solution using Google Cloud and Cloudentity: Describes architectural options for providing your customers with a seamless and secure embedded finance solution.

(New guide) Migrate to Google Cloud: Minimize costs: Minimize costs of your single- and multi-region Google Cloud environments, and of migrations across Google Cloud regions.

(New guide) FortiGate architecture in Google Cloud: Deploy a FortiGate Next Generation Firewall in Google Cloud, using Compute Engine and Virtual Private Cloud networking.

(New guide) Google Cloud Architecture Framework: Added the deployment archetypes page in the System Design category.

(New guide) Google Cloud deployment archetypes: Overview and comparative analysis of the zonal, regional, multi-regional, global, hybrid, and multicloud deployment archetypes.

(New guide) Migrate from AWS to Google Cloud: Migrate from Amazon EKS to GKE: Design, implement, and validate a plan to migrate from Amazon EKS to Google Kubernetes Engine.

(New guide) Design secure deployment pipelines: Best practices for designing secure deployment pipelines based on your confidentiality, integrity, and availability requirements.

(New guide) Identify and prioritize security risks with Wiz Security Graph and Google Cloud: Describes how to identify and prioritize security risks in your cloud workloads with Wiz Security Graph and Google Cloud.

(New guide) Connect Google Virtual Private Clouds to Oracle Cloud Infrastructure using Equinix: Use Equinix Network Edge and Partner Interconnect to deploy private, multi-cloud connectivity between Google Cloud VPC networks and Oracle® VCNs.

(New guide) Import data from an external network into a secured BigQuery data warehouse: Describes an architecture that you can use to help secure a data warehouse in a production environment, and provides best practices for importing data into BigQuery from an external network, such as an on-premises environment.

(New guide) Use distributed tracing to observe microservice latency: Shows how to capture trace information on microservice applications using OpenTelemetry and Cloud Trace.

(New guide) Deploy a secured serverless architecture using Cloud Functions: Provides guidance on how to help protect serverless applications that use Cloud Functions (2nd gen) by layering additional controls onto your existing foundation.