![]() Often the resources are managed with in-place data and control plane updates, assuming they support zero-downtime update operations.īecause these resources exist for at least the lifetime of the system, this layer is often responsible for storing global, geo-replicated state. Their lifetime spans the life of the system or longer. ![]() These resources are expected to be long living (non-ephemeral). Common examples are resources that are used to distribute traffic across multiple regions, store permanent state for the whole application, and monitor resources for them. If you aren't familiar with this series, we recommend you start with what is a mission-critical workload? Core architecture patternĬertain resources are globally shared by resources deployed within each region. ![]() This article is part of the Azure Well-Architected mission-critical workload series. What is the impact on availability from a disaster at this layer? Would it cause a systemic outage or only a localized capacity or availability issue? What is the expected throughput for that resource? How much scale is provided by the resource to fit that demand? What are the dependencies on other resources? Is the resource required to be globally distributed? Can the resource communicate with other resources, located globally or within that region? What impact will the persisted state at this layer have on reliability or manageability? ![]() What's the expected lifetime of the resource, relative to other resources in the solution? Should the resource outlive or share the lifetime with the entire system or region, or should it be temporary? We recommend that you evaluate the key design areas, define the critical user and system flows that use the underlying components, and develop a matrix of Azure resources and their configuration while keeping in mind the following characteristics. The article recommends a north star design approach and includes other examples with common technology components. Apply this pattern when you start your design process, and then select components that are best suited for your business requirements. This article presents a key pattern for mission-critical architectures on Azure. ![]()
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