Azure Well-Architected Framework

The Azure Well-Architected Framework is a set of quality-driven tenets, architectural decision points, and review tools intended to help solution architects build a technical foundation for their workloads.

Explore the Framework

Azure Well-Architected Framework

Design workloads that achieve business value over time.

As solution architects, you want to build reliable, secure, and performant workloads that maximize the value of investment in Azure infrastructure. Start with the Pillars, and align your design choices with the principles. Then, build a strong foundation for your workload based on technical design areas. Finally, use review tools to assess your readiness in deploying to production.

Diagram of AI workload design with labeled components for AI practices and process, data processing and analytics, model training and fine-tuning, intelligent AI applications, and platform services and tools.

Apply AI architecture patterns to design Well-Architected intelligent applications and custom AI models with greater confidence. Establish baseline knowledge of core components, their interactions, and key design characteristics (such as lifetime, scalability, security, and Responsible AI) to make informed design decisions. Evaluate and tailor these characteristics for your specific workload to build reliable, secure, and scalable AI solutions.

Azure architecture pattern for AI workloads

Pillars

  • Reliability

    Ensures that the workload meets the uptime and recovery targets by building redundancy and resiliency at scale.

  • Security

    Protect the workload from attacks by maintaining confidentiality and data integrity.

  • Cost Optimization

    Adopt an optimization mindset by at organizational, architectural, and tactical levels to keep your spending within budget.

  • Operational Excellence

    Reduce issues in production by building holistic observability and automated systems.

  • Performance Efficiency

    Adjust to changes in demands placed on the workload by through horizontal scaling and testing changes before deploying to production.

Workloads

  • Artificial Intelligence (AI)

    Incorporate discriminative or generative AI models in your workload for predictive analysis, generating content, and other AI use cases.

  • Software as a service (SaaS)

    Key insights for Startups and mature independent software vendors (ISVs) to build scalable, performant, reliable, and secure SaaS solutions.

  • Mission-critical

    Design and operationalize workloads that are expected to be always available and resilient to failures.

  • HPC

    Design strategies for all the characteristics of HPC workloads.

  • Sustainability

    Plan your path forward, improve your sustainability posture, and create new business value while reducing your operational footprint.

See example workloads that apply Well-Architected tenets in the Azure Architecture Center

Service guides

Browse the service guides

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