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.

What is Well-Architected 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 showing the an example architecture pattern for AI workloads.

Explore the all new AI Workload:

  • Understand how to address architectural challenges for designing AI workloads, including data and application design, nondeterministic functionality, and operational challenges.
  • Get design recommendations when incorporating generative and discriminative AI models.
  • Address cross-cutting challenges such as security requirements, large data volumes, model decay, skill gaps, rapid AI innovation, and maintaining ethical standards.
  • Learn about the recommended practices for managing the lifecycle of models, covering both MLOps and GenAIOps.
AI Workload Documentation

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.

  • Oracle on IaaS

    Host Oracle workloads on Azure, which includes not only Oracle Databases, but also applications such as Siebel, Peoplesoft, JD Edwards.

  • SAP

    Evaluate, design, and optimize an SAP workload from premigration to operations.

  • Mission-critical

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

  • Sustainability

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

  • Azure VMware Solution

    Relocate legacy application virtual machines to Azure VMware Solution as a staging area for the first phase of your migration and modernization strategy.

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

Azure service guides

Browse the service guides

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