BuildIntelligent Future’s digital enterprise base
Relying on the Microsoft Azure global infrastructure, enterprises can efficiently build, run and manage applications, data and Azure AI core capabilities on a unified platform. Azure Arc enables consistent management of hybrid/multi-cloud and deeply integrates Azure OpenAI Service and Zero Trust security architecture to provide secure, compliant, and scalable standardized underlying support for enterprise digital transformation and intelligent innovation.
Global scale and high availability
Relying on Azure's global infrastructure and multi-region capabilities, it provides high availability and business continuity design space for key businesses.
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Global region coverage: Azure offers 70+ declared regions, supporting nearby deployment and compliant location selection.
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Region/AZ Architecture Strategy: Microsoft Well-Architected Framework provides reliability trade-offs and best practices for cross-AZ/cross-region deployments.
Zero Trust Security System
With Microsoft Entra as the core, implement the dynamic identity security boundary of "never trust, always verify".
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Conditional Access: Zero trust policy engine that implements dynamic admission and enforcement controls (e.g. MFA/blocking) based on user/location/IP, device status, application and real-time risk signals.
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Unified Security:Microsoft Defender for Cloud provides unified security management and threat protection across hybrid clouds (CNAPP: CSPM + CWPP + DevSecOps).
Seamless hybrid cloud governance (Azure Arc)
Bring on-premises, edge, and multi-cloud resources into the Azure control plane for a consistent governance, compliance, and operations experience.
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Cross-cloud governance: Azure Arc projects non-Azure resources to Azure Resource Manager to achieve unified resource orchestration and centralized management.
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Edge management: Combine Azure Policy and Defender for Cloud to extend automated guardrails, auditing, and remediation capabilities to Arc Connected resources.
Ultimate R&D efficiency (DevSecOps)
Integrating GitHub and Azure DevOps shifts security and compliance to the left of the R&D process, accelerating the process from "idea" to "online value".
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GitHub Copilot: Controlled experiments show that developers using Copilot complete specific tasks 55.8% faster on average.
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Azure Pipelines: Provides end-to-end CI/CD, automated build, testing and deployment, supports YAML pipelines and multi-platform agents (Windows/Linux/macOS), and can be deployed to Azure or any target environment.
AI native and intelligent computing platform
Relying on Azure AI capabilities, generative AI is implemented with production-level security and governance to quickly build enterprise-level applications.
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RAG best practices: Combine Retrieval Enhanced Generation (RAG) with content security capabilities to improve the reliability and controllability of enterprise knowledge Q&A.
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Responsible AI: Azure AI Content Safety supports harmful content detection, prompt shields, protection and policy configuration to meet compliance and security requirements.
Cost Management and FinOps Governance
With Microsoft Cost Management as the core, it provides a closed-loop native FinOps capability with cost visibility, controllability, and optimization.
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Cost Insights and Allocation: Supports multi-dimensional analysis, cost export, tag inheritance and cost allocation rules, improving organizational level transparency and accountability.
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Budget and exception alarms: Support budget, exception detection, reservation/saving plan utilization alarms, and promote proactive cost control and continuous optimization.
Pillars of architectural excellence
Follow the five dimensions of Microsoft Well-Architected Framework (WAF) to ensure that every cloud solution has production-grade resilience.
Quickly browse Azure core services by capability domain
Service product details
Please select the dimensions above to obtain core components and architectural suggestions in each field.
Enterprise-level architecture practice scenarios
Based on Microsoft Cloud Adoption Framework (CAF)'s standardized scenario recommendations cover the security, reliability, and performance requirements required for production environments.
Generative AI and RAG intelligent retrieval
Architectural Challenge: How to use the GPT-4 model to process petabyte-scale enterprise knowledge bases without leaking private data?
Recommended component stack
- Azure OpenAI (GPT-4o)
- Azure AI Search (Hybrid)
- Cosmos DB (Vector Store)
Architect Notes
Be sure to enable Private Link Ensure that inference traffic does not leave the public network. It is recommended to use Semantic Ranker to improve search accuracy.
Cloud migration of mission-critical systems
Architectural Challenge:How can a traditional SQL Server or VMware environment achieve 99.99% high availability without changing the core code?
Recommended component stack
- SQL Managed Instance
- Azure VMware Solution
- Azure Backup & Site Recovery
Architect Notes
Utilize Azure Hybrid Benefit Save up to 40% on licensing fees. Make sure to use Availability Zones distributed nodes.
Modern microservices and global acceleration
Architectural Challenge: How to manage massive containerized microservices and ensure global user access latency is less than 100ms?
Recommended component stack
- AKS (Azure Kubernetes Service)
- Azure Front Door (CDN + WAF)
- Azure Container Registry
Architect Notes
Combined with Azure CNI Get native VNet performance. The Anycast network provided by Front Door is the key to DDoS-resistant and low-latency access.
Fully managed data lake warehouse and BI
Architectural Challenge: How to connect engineering, analysis and display links to achieve real-time insights into petabyte-level data?
Recommended component stack
- Microsoft Fabric (OneLake)
- Power BI (DirectLake)
- Azure Data Factory
Architect Notes
Fabric is that it reduces data replication (OneLake). It is recommended to use Delta Parquet format for best compatibility.
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