Announcing Azure Infrastructure Resiliency Manager Public Preview
At Microsoft Build 2026, we are thrilled to announce that Azure Infrastructure Resiliency Manager is now available in public preview, open to all Azure customers. Azure Infrastructure Resiliency Manager is not a replacement for individual Azure resiliency features; it is the unifying layer that connects them into a coherent, goal-driven workflow. It leverages and complements Availability Zones, Azure Advisor, Azure Chaos Studio, Azure Monitor, and Azure Copilot, adding purposeful orchestration that turns isolated capabilities into a complete resiliency strategy. The preview already covers a broad range of Azure resource types and zone-redundant configurations, from virtual machines and databases to AKS clusters and networking with continued expansion planned. The new platform is built on a foundational belief: achieving application resilience is a continuous journey, not a one-time configuration task. That journey is organized into three actionable phases: Start Resilient, Get Resilient, and Stay Resilient. Each phase delivers measurable customer value such as reduced downtime risk, faster recovery, and greater operational confidence. Start resilient: Embedding resiliency from day one Starting resilient means treating resiliency as a fundamental architectural requirement, not an afterthought. Azure Infrastructure Resiliency Manager makes it straightforward to design zone-resilient applications from the outset, eliminating costly retrofits and reducing risk before your first deployment. Resiliency Agent: Your AI-powered architecture advisor The standout capability in this preview is the Resiliency Agent, a conversational, AI-powered assistant embedded directly in the Azure Portal. Designed for architects and developers, the Resiliency Agent allows teams to validate and refine resiliency strategies using plain language. For example, you might enter a prompt such as "I'm designing a three-tier web app with VMs, a Flexible PostgreSQL database, and a Standard Load Balancer" and ask the agent what zone-resiliency requirements apply. The Resiliency Agent analyzes your plan, identifies single points of failure, and recommends specific changes: enabling zone redundancy for the database, deploying VMs across zones, or upgrading to zone-redundant load balancers. It delivers a structured, per-resource summary that makes the path to resiliency explicit and actionable. Infrastructure-as-Code generation and validation Beyond design guidance, Infrastructure Resiliency Manager accelerates implementation. You can ask the Resiliency Agent to generate Infrastructure-as-Code (IaC) templates (ARM, Bicep, or Terraform) with all resiliency configurations pre-built and ready to deploy. A generated Bicep template, for example, automatically includes zone-redundant settings for databases, VMs, and load balancers aligned to your stated goals. The agent also validates existing IaC templates: upload a template and receive a natural language assessment of resiliency gaps, complete with targeted suggestions and code snippets to close them. This eliminates manual review overhead and ensures every new deployment starts with a resilient foundation by embedding resiliency into the design and deployment lifecycle from day one, organizations avoid expensive redesigns, accelerate time-to-market, and bring new services to production already meeting high-availability standards. Get resilient: Closing gaps in existing applications Most Azure customers have workloads built over months or years that may not fully meet today's resiliency requirements. Infrastructure Resiliency Manager delivers a centralized, goal-driven view of your current environment's resilience posture, along with prioritized, actionable recommendations to close every gap. Goal-driven resiliency posture Define what constitutes your application by grouping resources across regions, subscriptions, or resource groups, including tag-based grouping, using Service Groups. Once your application boundary is established, assign a resiliency goal: for example, zone-failure tolerance for all components, or specific data replication requirements for critical services. The platform assesses every resource against that goal and presents a clear, single-pane-of-glass resiliency posture showing which resources meet the goal, which are non-resilient, and which remain unevaluated. This goal-driven model ensures that all subsequent guidance is precisely calibrated to your target state, not generic best practices. Actionable, prioritized recommendations For every resource that falls short of the defined goal, Infrastructure Resiliency Manager generates targeted remediation recommendations powered by Azure Advisor. If a virtual machine lacks zone redundancy, the platform recommends converting it to an availability zone deployment. If a database is not zone-redundant, the recommendation specifies exactly how to enable it. Critically, every recommendation includes contextual decision-making information: impacted resources, implementation steps, and qualitative cost indicators (High, Medium, Low) that flag whether a fix requires additional service spend, downtime, or redeployment. This allows engineering teams to plan remediation in a business-informed, prioritized manner. Looking ahead, the platform will also integrate application health with infrastructure health, correlating Azure Monitor SLIs and Azure Health Model insights to surface resiliency gaps with even greater precision. Guided remediation with the resiliency agent Azure Advisor identifies resiliency gaps and surfaces prioritized recommendations. Infrastructure Resiliency Manager builds on this by making those recommendations actionable. Instead of stopping at insights, the platform provides guided execution. Each recommendation includes step-by-step portal flows, dependencies, and readiness checks required for remediation. The Resiliency Agent acts as the interactive layer on top, helping you interpret and act on these recommendations in context. For example, you can ask whether an App Service can be moved to zone-redundant storage, what downtime to expect, or what prerequisites are required and receive clear, workload-aware answers tailored to their environment. On request, the agent can generate remediation scripts or IaC snippets to implement specific changes, such as validating an existing Terraform template against Azure resiliency best practices. Importantly, the agent never makes changes autonomously: it provides information and code, while you retain full control over execution. This human-in-the-loop model accelerates remediation without sacrificing governance. The result: a curated, goal-oriented to-do list that replaces generic advice with targeted action, weighted by cost and feasibility - giving engineering leaders clear visibility into which investments will yield the greatest resilience gains. Stay resilient: Continuous validation and recovery Readiness Resilience is not just a configuration milestone; it is an ongoing operational discipline. The "Stay Resilient" phase ensures the resilience you've built performs under pressure and that your teams are prepared to respond when real incidents occur. Azure Infrastructure Resiliency Manager delivers resiliency drills and recovery orchestration to support continuous readiness. Resiliency drills enabled by Azure Chaos Studio A highlight of this public preview is the introduction of availability zone failure drills, enabled by Azure Chaos Studio. These drills simulate zone outages for your application in a controlled, safe environment: shutting down VMs in a target availability zone, forcing failover for zone-redundant databases, or stopping AKS node pools. Every fault action is based on Azure-recommended patterns for each supported resource type, providing a realistic approximation of an actual zone failure. Because Infrastructure Resiliency Manager understands which resources are intended to be zone-resilient, it automatically determines which fault actions to apply, eliminating manual configuration. For scenarios not covered out of the box, custom fault logic via Azure Automation runbooks is supported, providing the flexibility required for complex environments. Recovery orchestration Resiliency drills in the platform go beyond fault injection. It integrates with recovery plan to orchestrate the complete recovery sequence automatically after injecting faults: fault injection → failover → reprotection → failback. This full-cycle simulation measures the maximum potential downtime your application could experience during a zone outage and surfaces any recovery steps that did not execute as expected. Real-time health monitoring and drill insights Throughout each drill, the Infrastructure Resiliency Manager provides live health monitoring powered by Azure Monitor. A built-in metrics dashboard tracks each resource's health in real time revealing whether your application remains available and how performance holds under simulated stress. This immediate feedback surfaces resilience gaps that may not have been visible through static analysis. After each drill, the platform logs the results along with team notes and attestations, building a historical record of all resilience tests. Over time, this record demonstrates measurable improvement and supports compliance with organizational and regulatory resiliency requirements. "Stay Resilient" converts assumptions into evidence. When an actual zone outage occurs, your teams will not be executing a failover for the first time; they would have rehearsed it. The result is a culture of proactive resilience, and the organizational confidence that your systems will deliver on their availability commitments. Get started with the public preview Starting today, the public preview of Azure Infrastructure Resiliency Manager is open to all Azure customers. Access the new platform through the Azure Portal by searching for "Resiliency". We encourage you to evaluate it against a test application or a production workload to gain immediate visibility into your current resiliency posture. To get the most from Infrastructure Resiliency Manager, we recommend these three starting actions: Define a resiliency goal for a critical application and review the posture insights the platform surfaces; you may uncover gaps that were previously invisible. Engage the Resiliency Agent to tackle a few recommendations and experience firsthand how AI-guided remediation accelerates your team's workflow. Run a zone-down drill in a non-production environment to validate your failover and recovery processes under realistic conditions. We believe this holistic approach will help organizations achieve a new level of operational excellence, making resiliency actionable, measurable, and deeply embedded in cloud practices. As Infrastructure Resiliency Manager moves toward general availability, we will continue incorporating your feedback and expanding capabilities to meet the demands of real-world cloud architectures. Azure Infrastructure Resiliency Manager gives you the tools to reduce downtime risk, gain clarity over your resiliency posture, and build genuine readiness for the unexpected. Join the public preview today and take the next step toward applications that don't just survive disruptions; they thrive through them. Resources Azure Infrastructure Resiliency Manager — Overview Get Started with Service Groups — Microsoft Learn Introduction to Azure Advisor — Microsoft Learn What is Azure Chaos Studio? — Microsoft Learn What's New in Azure Monitor — Microsoft Learn Modern Azure Resilience with Mark Russinovich — Tech CommunityIntroducing Layered Ingress Sharding: Achieving Single-Tenant Isolation in Multi-Tenant Services
Abhishek Tiwari, Vice President of Engineering, Azure Networking Amit Srivastava, Partner Director of PM, Azure Networking Varun Chawla, Partner Director of Engineering, Azure Networking Links to the three-part AFD blog series: Part 1 Part 2 Part 3 Why Multi‑Tenant Isolation Is Still Hard at Hyperscale Modern cloud platforms thrive on multitenancy. By sharing infrastructure across tenants, services like Azure Front Door (AFD) can deliver massive scale, global reach, and cost efficiency. At hyperscale, however, this efficiency comes with a hard truth: rare failures are inevitable, and their blast radius matters more than their frequency. When hundreds of thousands of tenants share a global data plane, a single misbehaving tenant, configuration regression, or zero-day exploit can turn a low probability event into a high impact outage. Over the years, the industry has developed many protections — rate limiting, circuit breakers, fair share scheduling, crash protection, and various sharding strategies. These techniques dramatically reduce average case risk, but they still struggle to bound worst case impact. In particular, they fall short of delivering what customers intuitively expect: single tenant isolation semantics (the guarantee that one tenant’s failure does not affect another) without requiring dedicated per-tenant infrastructure. At Azure Front Door, we’ve been working on a new architectural approach that directly targets worst case blast radius. Today, I’m excited to introduce Layered Ingress Sharding, a sharding strategy designed to enable single tenant fault isolation for largescale multitenant services. From Traditional Sharding to Ingress Sharding Traditional partitioning assigns each tenant to a fixed shard. This limits blast radius, but tenants in the same shard can still experience complete outages when that shard fails. Shuffle sharding improves on this by assigning each tenant to a subset of instances, where subsets partially overlap, dramatically reducing the probability of widespread impact. However, shuffle sharding still allows 100% availability loss for tenants in the affected shard, relies heavily on client retries, and introduces nontrivial capacity loss in overlapping shards. To address these limitations, we introduced Ingress Sharding. With ingress sharding, an ingress controller, which we call IRIS (Intelligent Routing with Ingress Sharding), sits directly on the data path. Ingress sharding uses shuffle sharding to construct shards from service instances; IRIS operates on top of these shards to perform tenant-aware, capacity-aware routing rather than introducing a new shard construction algorithm. IRIS identifies the tenant for each incoming connection and deterministically maps that tenant to a shard. Instead of relying on clients to retry when a shard is unhealthy, IRIS actively: Monitors the health of service instances Tracks available capacity in real time Retries and reroutes traffic internally Steers traffic away from unhealthy or overloaded instances Dynamically expands the set of service instances used for oversized tenants when sustained load exceeds a single shard’s capacity In effect, IRIS turns shard selection into a real-time, capacity-aware decision that is reevaluated for every new connection. This moves fault resilience and load balancing inside the platform, rather than pushing that burden onto clients. Ingress sharding significantly improves isolation and resilience, but on its own, a tenant can still experience a complete loss of availability if all instances in its shard are affected. Introducing Layers: Isolation Through Independence Layered Sharding adds a new dimension to multitenant isolation. In Layered Sharding, the service is divided into multiple independent layers. A layer represents an independent serving dimension of the system capable of handling tenant traffic independently. This technique was developed to reduce blast radius by changing how tenants are assigned across shards, rather than changing the underlying shard construction within a single layer. A key design goal is that layered sharding is orthogonal to the underlying sharding strategy. It works with existing approaches, whether that is standard partitioning-based sharding, shuffle sharding, or other shard assignment schemes used within a layer. Within each layer: Service instances are grouped into shards using an existing sharding technique (for example, traditional partitioning or shuffle sharding) Each tenant is assigned to a shard independently in that layer Crucially, tenant-to-shard assignments are randomized and independent across layers. This independence is what gives layered sharding its isolation properties, regardless of the specific sharding algorithm used within a single layer. The definition of a layer itself is intentionally flexible and service dependent. In Azure Front Door, each server naturally acts as one layer. In other services, a layer might correspond to a cluster, a scale unit, a fault domain, or even a regional partition — any unit capable of serving tenant traffic independently while preserving uniform load distribution. The result is powerful: even if a tenant’s traffic causes failures in one shard in one layer, it is statistically unlikely that the same tenant will collide with the same peers across many layers. Instead of experiencing a full outage, other tenants see at most a small, transient reduction in capacity, often invisible with standard retry behavior. Layered sharding alone already reduces availability impact across tenants. But when combined with ingress sharding, it enables something fundamentally stronger. Layered Ingress Sharding Layered Ingress Sharding integrates two complementary ideas: Layered Sharding spreads tenants across many independent layers with randomized shard assignments. Ingress Sharding dynamically routes traffic to healthy service instances across layers using real‑time health and capacity signals. The key blast radius reduction that enables single tenant isolation comes from the combination of independent shard randomization across layers with active, intelligent traffic steering. When a tenant misbehaves due to harmful traffic, a bad configuration, or an unknown vulnerability, IRIS detects unhealthy service instances and automatically routes traffic to healthy shards in other layers. Because shard assignments are independent, IRIS can always find unaffected capacity for well-behaved tenants. The resulting behavior is a fundamental shift in multitenant failure dynamics: Outages remain localized to the misbehaving tenant Healthy tenants continue to serve traffic Blast radius shrinks from fleetwide to tenant-local In effect, a shared multi‑tenant system begins to behave like it has single tenant‑ isolation semantics, without abandoning multitenancy. Why the Math Works The guarantees behind layered ingress sharding are not heuristic, they’re statistical. Because tenant-to-shard assignments are randomized independently across layers, the probability that two tenants repeatedly collide in the same shard follows a binomial distribution. With production representative configurations, tens of layers and shuffle-sharded service instances, the probability that an arbitrary tenant experiences a user-visible failure due to another tenant drops below what standard client retries already mask. Instead of asking “Can a noisy neighbor impact me?”, the system answers “What is the probability that a single connection attempt is unlucky across all layers?” and that probability decreases exponentially as the number of layers increases. This allows us to trade catastrophic outages for rare, isolated, and standard retry-mitigated events. A Hidden Benefit: Identifying Bad Tenants Layered ingress sharding provides an additional, powerful side benefit: automated identification of misbehaving tenants. Because shard assignments are computed independently across layers, a tenant that is consistently responsible for failures appears as a common factor across impacted shards and service instances. By correlating signals across layers, the platform can accurately identify the offending tenant and apply targeted mitigations such as isolation, throttling, or traffic steering without relying on coarse-grained circuit breakers that penalize everyone. This dramatically improves response time under high load or adversarial conditions while preserving availability for unaffected tenants. Beyond Azure Front Door While Layered Ingress Sharding was developed in the context of Azure Front Door, the underlying principle is broadly applicable. Any large‑scale multi‑tenant system that: Serves many tenants from shared infrastructure Can distribute traffic uniformly across independent layers Can enforce shard-level isolation within each layer can benefit from this approach. Layers don’t have to be servers they could be clusters, scale units, or regional partitions. The key is independent assignment across layers combined with intelligent ingress routing. We believe this pattern represents a reusable architectural strategy for building resilient, hyperscale, multi‑tenant services. Closing Thoughts Multi‑tenancy doesn’t have to mean shared fate. Layered Ingress Sharding shows that by combining probabilistic isolation with intelligent ingress routing, we can build systems where failures are expected, bounded, and automatically contained, even at hyperscale. Rather than eliminating failure, this approach mathematically constrains its impact. And in large‑scale multi‑tenant platforms, that distinction makes all the difference.Modern Azure Resilience with Mark Russinovich
Resiliency in the cloud reflects different priorities from consistent performance, to withstanding failures, to predictable recovery. These map to reliability, resiliency, and recoverability, which together guide how workloads should be designed on Azure. This post extends foundational guidance with practical multi‑region design decisions, including when to use availability zones, paired regions, and non‑paired regions to meet business continuity goals. Reliability in Azure isn’t defined by a single recommendation, but by a set of architectural patterns designed to balance cost, complexity, recovery speed, and operational effort—because no single approach fits every workload. While disaster recovery is a common driver for multi‑region designs, long‑term scale planning also matters. Azure regions operate within defined physical and latency boundaries, and large-scale workloads may eventually approach the practical capacity limits of a single region. This post introduces four resilience patterns, outlining when and why to use each so you can assess options based on your non‑functional requirements. It also explains how availability zone–based designs can often provide an alternative to paired regions as a default choice. Here are a few common reliability and availability architecture patterns: In-region High Availability (HA) with Availability Zones (AZ): Maximize availability within a single Azure region by deploying across multiple availability zones. Regional Business Continuity and Disaster Recovery (BCDR): A primary/secondary region strategy implemented across separate Azure regions, selected based on geographic risk boundaries, regulatory requirements, and service availability. Recovery sequencing and failover behaviors are defined by workload dependencies and organizational requirements. Non-paired region BCDR: A primary/secondary region strategy where the secondary region is chosen based on requirements such as capacity, service availability, data residency, and network latency. This approach also supports long‑term scale planning, since Azure regions operate within physical datacenter footprints and latency boundaries and can reach practical capacity limits as workloads grow. See multi‑region solutions in non‑paired regions. Multi-region active/active: Deploy workloads across multiple regions simultaneously so that each region can serve production traffic. This approach can provide both high availability and disaster resilience while improving global performance, but it introduces additional architectural complexity and operational overhead. The rest of this post helps you understand the tradeoffs across these patterns, enabling you to select the right approach per workload while avoiding unnecessary cost and operational complexity. First post in this series: Achieve agility and scale in a dynamic cloud world Why did Azure launch with paired regions? Launched in 2010, but rebranded to Microsoft Azure in 2014, the regions were introduced in pairs (West US & East US, West Europe & North Europe, Southeast Asia & East Asia) to align with common enterprise business continuity practices at the time. Many organizations operated multiple datacenters within the same geographic boundary, separated by sufficient distance to reduce shared risk while maintaining regulatory and operational alignment. This design mirrored familiar enterprise BCDR practices at the time and offered: A familiar primary/secondary failover pattern consistent with enterprise BCDR strategies Support for regulatory or data residency requirements that required disaster recovery within a defined geographic boundary Turnkey replication capabilities for services such as Geo-Redundant Storage (GRS) Platform-level sequencing of updates to reduce the likelihood of simultaneous regional impact A defined regional recovery prioritization model for rare geography-wide incidents This model provided assurance that Azure could meet or exceed the resilience of legacy enterprise environments while simplifying early cloud adoption through predefined recovery patterns. However, Azure’s engineering strategy has evolved. Many services now support replication to a region of choice rather than being limited to predefined pairs. This provides architects with greater flexibility to select regions based on workload requirements, risk boundaries, compliance constraints, capacity considerations, and cost models. It’s important to recognize that regional parity is never guaranteed even between paired regions. Differences in service availability, supported SKUs, scale limits, capacity, cost and operational maturity must be explicitly accounted for in the workload design. How has cloud resilience evolved since launch? The introduction of Availability Zones in 2018 provides a significant advancement in Azure resilience. Availability Zones are physically isolated groups of data centers within a region; each zone has independent power, cooling and networking. Many Azure services (App Service, Storage, Azure SQL etc.) use zones to provide platform-managed resilience. In addition, customers can deploy zonal resources, such as virtual machines, into specific zones or distribute them across zones to design for higher availability. Where previously Azure regions were launched in pairs, since 2020, regions have been typically designed with multiple availability zones, without a paired region. This design enables: High availability within a single region Platform-managed resilience for most failure scenarios Reduced need for multi-region deployments for standard high-availability requirements How should customers design for resilience when using both paired and non-paired regions? To decide which resiliency model makes sense, customers should start by defining clear expectations including uptime targets, recovery time objectives (RTO), recovery point objectives (RPO), latency tolerance, and data residency. These non-functional requirements should directly influence architectural decisions. In practice, High Availability (HA) and Disaster Recovery (DR) are differentiated by recovery objectives rather than geography. HA architectures target near-zero downtime and minimal data loss, while DR solutions allow for defined recovery time and acceptable data loss. While HA is commonly established within a region using availability zones, it can also be achieved across regions through active-active designs. Similarly, DR is typically implemented across regions using replication and failover strategies. HA: Availability Zones When designing high availability within a region, Azure builds on AZs with 2 models: Zone-redundant resources are replicated across multiple availability zones to ensure data remains accessible even if one zone fails. Some services provide built-in zone redundancy, while others require manual configuration. Typically, Microsoft chooses the zones used for your resources, though some services allow you to select them. Zonal resources are deployed in a single availability zone and do not provide automatic resiliency against zone outages. While faults in other zones do not affect them, ensuring resiliency requires deploying separate resources across multiple zones. Microsoft does not handle this process; you are responsible for managing failover if an outage occurs. The decision to design a zone-resilient architecture is critical for balancing availability requirements with cost and regional capacity constraints. Designing workloads to be resilient across availability zones is generally the preferred approach for improving availability and protecting against zone-level failures. Deploying workloads across availability zones can enhance fault tolerance and reduce downtime when supported by the Azure service being used. However, architects should still consider workload characteristics, cost implications, and potential latency impacts, which may vary depending on the services and architecture patterns involved. Ultimately, zone resiliency is an architectural decision that should be strategically aligned with business priorities and risk tolerance, not simply treated as a checkbox to be ticked during deployment. DR: Paired and Non-Paired Regions Region pairs should be viewed as an architectural choice rather than a rule. Historically, paired regions played a key role in minimizing correlated failures and streamlining platform updates and recovery processes. However, as the Azure Safe Deployment Practices (SDP) have matured, the advantages of region pairs have become more nuanced. Over time, SDP has evolved to support safer and more flexible change management through longer and more adaptable bake times, richer operational signal integration, and an expanded understanding of regional deployment boundaries. These improvements enable Azure to release changes more safely across a growing and increasingly diverse regional footprint, while still balancing reliability with time‑to‑market. As a result, regional pairs are no longer the sole mechanism for managing correlated change risk, but one of several architectural tools customers can apply based on their resiliency and compliance needs. Using non-paired regions or a mix of paired and non-paired regions allows customers to design high availability and disaster recovery architectures that are driven by business, compliance, and application requirements rather than fixed regional relationships. This enables customers to optimize data residency, regulatory boundaries, latency to specific user populations, and provide differentiated recovery objectives across their workloads. This approach can also reduce exposure to rare but high-impact platform-level events by avoiding tightly coupled regional behaviors. While some Azure services natively simplify replication and recovery within paired regions, and others support replication across arbitrary regions (such as Azure SQL, Cosmos DB, and Azure Blob Storage with object replication), non-paired designs encourage explicit, workload-aware resiliency strategies such as application-level replication, asynchronous data sync, and failover orchestration. Although this introduces more architectural responsibility and may require compensating for paired region features, it delivers greater transparency, predictable recovery behavior, and alignment with business-driven RTO/RPO requirements rather than platform defaults. Regional failover is a customer‑orchestrated decision; customers should design, test, and operate their own failover and failback processes rather than assuming platform‑initiated regional failover. Designing for regional resilience requires distinguishing between workload mobility and data protection. Azure provides two complementary capabilities that address these needs differently: Azure Site Recovery (ASR) and Azure Backup. Azure Site Recovery (ASR) enables near‑continuous replication and orchestrated failover of virtual machine–based workloads to a region of choice, not limited to paired regions. ASR is the primary mechanism for customers who need low RPO, controlled failover, and workload restart in a secondary region. This is especially relevant for regions without a paired region or where the paired region does not meet capacity, service availability, or compliance needs. Azure Backup provides durable, policy‑based data protection, independent of compute availability. While Azure Backup is not a high‑availability or infrastructure failover solution, it plays a critical role when services do not support region‑of‑choice replication natively. In these scenarios, backup and restore become the recovery mechanism. These two services are often used together: ASR for VM‑level workload continuity, and Azure Backup for protecting and restoring data across regions, including to non‑paired regions. I am using paired regions today – does this mean I need to change my architecture? If your current architecture is built around paired regions for compliance, data residency, or strict disaster recovery objectives, that model stays valid and supported. Azure continues to support paired regions providing prioritized recovery sequencing, staggered platform updates, and geo-aligned data residency, all backed by Microsoft’s global infrastructure strategy. What has changed is that paired regions are no longer the only way to achieve enterprise-grade resilience. For many workloads that adopted a paired region (1+1) model primarily to protect against local datacenter failure, Availability Zones combined with geo-redundant services now provide equivalent or better protection with far less architectural complexity and cost. The shift to nonpaired regions is therefore not a forced migration, but an opportunity to simplify. Customers can continue using paired regions where business requirements demand it, while selectively modernizing other workloads to take advantage of platform-managed zone resilience. What’s coming up next for resilience in Azure? Resilience is evolving from static guidance to continuous, workload-aware execution. A multi-region strategy isn’t only about recovery; it’s also a practical hedge against regional capacity constraints (regions have physical limits within a latency boundary, so growth can eventually hit caps). Resiliency agent in Azure Copilot (preview) helps you spot missing resiliency coverage—such as zone alignment gaps or missing backup/DR—and provides automated guidance (including scripts) to remediate issues, configure Azure Backup and Azure Site Recovery, and define recovery drills. Resiliency in Azure brings zone resiliency, high availability, backup, DR, and ransomware protection together into a unified experience within Azure Copilot, enabling teams to set resiliency goals, receive proactive recommendations, and view service‑group insights via Azure portal. If you’re looking for service-specific BCDR and replication guidance, use these authoritative starting points: Cloud Adoption Framework (CAF) – Landing zone design area (BCDR): guidance to define platform DR requirements (RTO/RPO), data residency considerations, and operational readiness as part of landing zone design. Azure Well-Architected Framework (WAF) – Disaster recovery strategies: guidance for structuring, testing, and operating DR plans aligned to recovery targets, with links to companion DR planning resources. WAF design guide – Regions & Availability Zones: how to choose between zone- vs region-based approaches and understand reliability/cost/performance tradeoffs. Azure service reliability guides: service-by-service reliability/replication behavior and customer responsibilities. Non‑paired multi‑region configurations: examples of supported multi-region approaches when regions aren’t paired. Validate feasibility before you design: confirm service/SKU/zone availability in both regions. Next step: Explore Azure Essentials for guidance and tools to build secure, resilient, cost-efficient Azure projects. To see how shared responsibility and Azure Essentials come together in practice, read Resiliency in the cloud—empowered by shared responsibility and Azure Essentials and How to design reliable, resilient, and recoverable workloads on Azure on the Microsoft Azure Blog. For expert-led, outcome-based engagements to strengthen resiliency and operational readiness, Microsoft Unified provides end-to-end support across the Microsoft cloud. To move from guidance to execution, start your project with experts and investments through Azure Accelerate. Related Resources Architecture strategies for using Availability Zones and Region High Availability Architecture strategies for highly available multi-region design Disaster Recovery Architecture strategies for designing a Disaster Recovery strategy Multi-Region solutions in nonpaired Regions Develop a disaster recovery plan for multi-region deployments Azure Regions and Services Azure region pairs and nonpaired regions Reliability guides for Azure servicesChoosing two-zone and three-zone patterns for zone-resilient Azure workloads
This article complements our Advancing Reliability series post, Two zones or three? A design framework for zone-resilient Azure workloads. Together, they provide guidance on both the considerations and deployment patterns for zone-resilient Azure workloads. Purpose This article helps customers evaluate Azure workload components and choose zone-resilient patterns that meet their requirements during a single-zone failure. The goal is to identify where two zones can meet workload requirements, where three zones are required, and where service-managed zone redundancy is the right approach. Important: This guidance is a decision framework, not a service support matrix. Availability zone behavior varies by Azure service, SKU, tier, region, and configuration. Always validate the selected design against the relevant Azure reliability guidance and test the workload's actual failure behavior before finalizing the architecture. Zone resiliency helps protect against the loss of a single availability zone. It does not protect against a full-region outage. For mission-critical workloads or workloads with strict disaster recovery requirements, evaluate whether the workload also requires a multi-region design. Availability zones are separate groups of datacenters within an Azure region. Each availability zone has independent power, cooling, and networking infrastructure. Azure services that support availability zones generally expose support through zone-redundant or zonal deployment models. Key takeaways Evaluate zone patterns at the workload component level, not only at the whole-workload level. Many workloads can meet single-zone failure objectives by using two zones for some components and three zones only where component requirements demand them. For the single-zone failure mode, two-zone and three-zone patterns can both meet resource availability objectives when remaining capacity and failover behavior are validated. Use service-managed zone redundancy when it meets workload requirements. Use two zones when the component can meet its availability, durability, capacity, performance, and operational requirements across two zones. Use three zones when a component requires the additional zone for post-failure capacity, data durability, replication topology, quorum, leader election, or operational margin. Balance cost and operational complexity after defining the workload's resiliency objective. Do not assume that two zones are always cheaper or that three zones are always required. Zone-redundant and zonal deployment models Zone-resilient designs depend on the deployment model used by each Azure service. Zone-redundant resources are distributed or replicated across multiple availability zones. Azure manages replication, request distribution, and failover behavior for the service. Where available and aligned to workload requirements, zone-redundant resources should be preferred, especially for production deployments. Zonal resources are pinned to a specific availability zone. A zonal resource is isolated from failures in other zones, but it is not automatically resilient to a failure in its own zone. To make a zonal service resilient, customers need to deploy separate instances across multiple zones and design the workload to route traffic, replicate data, detect failures, and recover. Some Azure services offer both zonal and zone-redundant deployment options, while others may be zone-resilient by default. In some cases, availability zone support requires additional configuration, service modification, or redeployment. Support can also vary by region, SKU, tier, or service configuration. Before choosing a deployment model, review the service-specific reliability guidance and availability zone support matrix to understand the options and requirements for your scenario. Primary decision dimensions Current Azure Well-Architected guidance emphasizes deploying production workloads across two or more failure domains to improve resiliency to failures within a single failure domain. In Azure regions that support availability zones, those failure domains are exposed as availability zone boundaries. When deciding whether a component should use two zones, three zones, or service-managed zone redundancy, evaluate three dimensions: Resource availability: For the single-zone failure mode, two-zone and three-zone patterns can both meet resource availability objectives when the remaining zone or zones can support the required operating state and failover behavior. The additional zone in a three-zone design does not by itself make the component resilient to more than one zone failure within the same region. Data consistency and durability: Stateful components might require three zones when data durability, replication topology, quorum, consensus, leader election, or split-brain prevention depends on a third failure domain or third replica placement. Cost and capacity: For the same post-failure performance target, a two-zone design can require more recovery capacity than a three-zone design. Cost optimization should be evaluated after the resiliency objective is defined. If more than one availability zone is unavailable in the same region, the concern can become regional rather than only workload-specific because foundational regional services require at least two surviving availability zones for continued regional availability. Workloads with requirements beyond a single-zone failure should evaluate disaster recovery or multi-region design separately. Common workload components can be grouped as follows: Component category Typical zone decision Stateless resources that support networking or application code and do not store persistent data Two-zone or three-zone flexibility, based on remaining capacity, routing, latency, and operational requirements. Stateful resources that use node-based quorum, consensus, or leader election Three zones, a third failure domain, or a product-specific witness pattern is commonly required to avoid split-brain or quorum-loss scenarios. Critical data stores that require three replicas for the highest durability targets Three-zone replication might be required to support the intended durability level, such as eleven-nines-style durability targets. Validate service-specific claims. Other stateful resources Two-zone, three-zone, or service-managed patterns can be valid depending on service behavior, recovery time objective (RTO), recovery point objective (RPO), durability, failover, and recovery requirements. Component-level decision framework Walk through the workload by critical flow and component. For each component, determine whether service-managed zone redundancy applies, whether a two-zone pattern can meet the component's single-zone failure objective, or whether three zones are required. Component question What to evaluate Decision guidance Is zone resiliency managed by the Azure service? Confirm whether the service provides zone-redundant or zone-resilient behavior through a supported configuration, SKU, tier, or replication mode. Use service-managed zone redundancy when it meets workload requirements. Do not force a two-zone or three-zone customer-managed design onto services where Azure manages placement and failover internally. Is the component stateless or easily replaceable? Evaluate routing, health probes, scale-out behavior, post-failure capacity, deployment automation, monitoring, and recovery steps. Two zones can often meet requirements for stateless or easily replaceable components when the remaining zone can support the required degraded or full operating state. Use three zones when capacity distribution or operational requirements justify the added design and testing scope. Does the component store durable state? Evaluate replication mode, data durability, consistency, RTO, RPO, failover behavior, recovery behavior, and service-specific support. Use the pattern that satisfies the data protection and recovery requirements. Three zones might be required when the storage or data service requires an additional zone for durability, triple-replica placement, replication topology, or recovery behavior. Does the component use quorum, consensus, or leader election? Validate replica placement, majority behavior, witness or tie-breaker design, leader election, split-brain prevention, recovery, and failback. Do not assume that three replicas across two zones are sufficient. Three zones, a third failure domain, or a product-specific witness pattern might be required to tolerate a zone loss safely. Is the component latency-sensitive? Define latency and throughput thresholds, test candidate zone pairs with realistic protocols and configuration, and identify which paths are actually latency-sensitive. Two zones can be appropriate for latency-sensitive synchronous paths that use tested placement. Logical zone numbers can map to different physical zones across subscriptions, so validate zone mapping when selected zone pairs matter. What capacity must remain after one zone fails? Define the required post-failure operating state for the component: degraded but acceptable, full baseline, or standby recovery. Choose the zone pattern that can satisfy the required post-failure operating state. Two zones can meet requirements when each remaining zone has enough capacity for the target state. Three zones can reduce the capacity each zone must carry for the same post-failure target. How will the design be operated and reviewed? Assign owners for monitoring, testing, incident response, failover, failback, and periodic reassessment. Confirm that identity, network security, encryption, secrets management, policy, monitoring, and data protection requirements are preserved. Document why each component uses service-managed zone redundancy, two zones, or three zones. If three zones are required for a component, state the requirement that drives that decision. Where two zones can meet requirements A two-zone pattern can be a practical way to meet single-zone failure objectives when the component's requirements are satisfied across two zones. Common examples include: Stateless compute, application, or network components where traffic can be routed to the remaining zone. Pairwise active-passive or active-active designs that are simpler to deploy, test, and operate across two zones. Latency-sensitive synchronous paths where a tested zone pair meets performance requirements. Customer-managed zonal resources where the remaining capacity, failover process, monitoring, recovery, and failback behavior are validated. Components whose acceptable degraded operating state can be supported after one zone is unavailable. The design should define what happens after one zone is unavailable, including remaining capacity, acceptable degradation, data consistency, failover behavior, recovery steps, observability, and operational ownership. Where three zones are required Three zones are required when two zones cannot meet the component's requirements during or after a single-zone failure. Examples include: A required post-failure operating state that cannot be supported by the remaining zone in a two-zone design. Data durability or replication requirements that depend on placement across three zones, such as triple-replica placement for the highest durability targets. Quorum, consensus, or leader-election designs that require a third failure domain or witness placement to avoid losing quorum or creating split-brain risk. Three zones still primarily help a workload tolerate a single availability-zone failure within a region. When this guidance refers to an additional failure domain, it means an additional Azure availability-zone placement option or an application-level failure domain needed by a specific component design, such as quorum, witness, or leader-election behavior. Where three zones may add value Some components do not strictly require three zones but can benefit from the additional placement option. In these cases, the value is usually related to capacity distribution, maintenance flexibility, or operational margin, not a different single-zone availability failure mode. Use three zones when the additional zone helps the component meet the required post-failure operating state, reduces how much capacity each zone must carry, or improves the ability to maintain and recover the component without violating workload requirements. Data consistency and durability considerations Stateful components should be evaluated based on consistency, replication, quorum, durability, RTO, and RPO requirements. Some distributed systems use quorum, leader election, or consensus-based coordination to maintain consistent state. Three zones are not universally required for every quorum-based architecture, but quorum-based systems require careful validation. Replica count alone is not enough. Replica placement, majority behavior, witness or tie-breaker placement, leader election, write consistency, split-brain prevention, recovery behavior, and failure-domain assumptions all affect whether a two-zone or three-zone deployment is appropriate. Some systems can place three or more replicas across two zones, and some managed services provide zone-resilient behavior without exposing direct customer control over zone placement. These patterns should not be generalized. In customer-managed majority-quorum systems, placing replicas across only two failure domains can still lose quorum if the majority-holding zone is unavailable. A third failure domain, witness, or tie-breaker might be required to tolerate a zone loss safely, depending on the product architecture. For customer-managed stateful systems, validate replica count and placement, quorum behavior, leader election behavior, synchronous and asynchronous replication, split-brain prevention, failure recovery behavior, data durability requirements, and RTO and RPO objectives. For managed data services, understand how the service implements zone resiliency, which configuration choices are available, and how the service behaves during zone-down scenarios. Capacity planning for a single-zone failure Capacity planning should start with the component's required operating state after the loss of one availability zone. Determine the capacity required to support the component in an approved degraded resiliency state, then use that post-failure target to compare zone patterns. For active-active deployments, use: Total Capacity = Target Remaining Capacity x Z / (Z - 1) In this formula: Target Remaining Capacity is the capacity the component must have after one zone is unavailable. Z is the number of zones used by the component. For example, if a component requires 100 units of baseline capacity and can operate at an approved degraded level of at least 80 units after losing one zone, the model estimates: Deployment model Formula Total provisioned capacity Capacity per zone Remaining after one zone loss Two availability zones 80 x 2 / (2 - 1) 160 units 80 units 80 units Three availability zones 80 x 3 / (3 - 1) 120 units 40 units 80 units This example compares designs against the same post-failure operating objective. The acceptable degraded state should be explicitly defined, tested, and approved. It should include the minimum remaining capacity, expected throttling or prioritization behavior, scale-out assumptions, and how long the component can remain in the degraded state. If the component must maintain full baseline capacity after one zone is unavailable, use the full baseline capacity as the target remaining capacity. Capacity requirements depend on workload architecture, scaling behavior, service limits, failover behavior, and acceptable degradation. Cost and operational considerations Cost and operational complexity should be evaluated after the resiliency objective is defined. They should not be used to dismiss two-zone designs that can meet component requirements, and they should not be used to justify two-zone designs that do not meet requirements. For the same post-failure capacity target, a three-zone design can require less total provisioned capacity than a two-zone design because the recovery capacity is distributed across more zones. Use the capacity model to understand that tradeoff before optimizing costs. For workloads with predictable usage, evaluate commitment-based discounts such as Azure savings plans or Azure reservations where they apply to the selected services. Operationally, consider whether the selected pattern can be deployed, monitored, tested, failed over, recovered, and reviewed consistently. A two-zone pattern can be simpler for pairwise designs. A three-zone pattern can provide more operational margin for components that benefit from additional placement options. Component classification workflow Before finalizing the zone pattern, confirm that: Each critical flow is decomposed into the components that support it. Each component is evaluated across resource availability, data consistency and durability, and cost or capacity impact. Each component is classified as service-managed zone-redundant, two-zone customer-managed, or three-zone required. The reason for requiring three zones is documented when two zones do not meet the component objective. Each Azure service's zone support, SKU, tier, region, and configuration requirements are validated. Customer-managed zonal resources have validated routing, load balancing, replication, failover, monitoring, recovery, and failback. Remaining capacity and acceptable degradation after one zone loss are documented. Stateful or quorum-based components have validated replica placement, witness or tie-breaker behavior, leader election, and split-brain prevention. Latency-sensitive paths have been tested across the selected zone placement. Security, identity, monitoring, and data protection requirements are preserved. Ownership for testing, incident response, failover, failback, and periodic reassessment is assigned. Related public guidance Azure services that support availability zones Enable zone resiliency for Azure workloads Zonal resources and zone resiliency What are Azure availability zones Architecture strategies for availability zones and regionsAnnouncing the resiliency agent in Azure Copilot, now in public preview
The distance between knowing and doing Most teams already know that zonal resiliency matters. What slows them down is everything in between: assessing posture across subscriptions and regions, deciding which gaps should be prioritized, writing the templates, and confirming the change actually rolled out. That is four separate workstreams, in four separate places, usually picked up long after the application is shipped. The resiliency agent closes that distance. We’re excited to announce that it is now available in public preview as part of the agents in Azure Copilot. The agent brings resiliency assessment, prioritized recommendations, and deployment-ready code into a single conversation, so resiliency becomes something your team does continuously rather than something you audit once a year. Learn more about Azure Copilot agents here. What the resiliency agent does The Resiliency agent is the conversational, action-oriented layer of Azure Infrastructure Resiliency Manager. The platform gives you a goal-driven view of your resiliency posture, and the agent lets you act on that posture in plain language. It brings together the signals you would otherwise chase manually across availability zones, Azure Backup, Azure Site Recovery, service level indicators, and Azure health models, then turns them into workload-aware guidance you can execute. Starting with zonal resiliency, it is designed to complement the resiliency capabilities you already rely on rather than replace them. The agent is built on the same foundational belief as Azure Infrastructure Resiliency Manager: application resiliency is a continuous journey, not a one-time task. That journey runs in three phases: Start Resilient Get Resilient Stay Resilient. This public preview addresses the activities associated with first two phases, frontloading the capabilities customers asked for most: direct remediation, Infrastructure as Code integration, and cost visibility. Stay Resilient comes next. What you can do in public preview Generate deployment-ready Bicep and Terraform with zone-redundant settings already enabled, before your first deployment Find the service groups and resources that are not zone resilient across your subscriptions and regions Prioritize remediation with cost-aware indicators that flag whether a fix needs extra spend, downtime, or redeployment Generate ready-to-deploy scripts to configure zone resiliency for supported resource types Create and update service groups so your applications are modeled correctly from the start Start resilient: build it in from the first line of code The most durable resiliency is the kind you never have to retrofit. Starting resilient means treating zone resiliency as an architectural requirement on day one, and the Resiliency Agent makes that the path of least resistance. Describe the application you are building, and the agent helps you generate deployment-ready Infrastructure as Code with the recommended resiliency configurations already enabled at creation time. Ask for a Bicep or Terraform template for a new workload and the agent returns one with zone-redundant settings pre-built for your databases, VMs, and load balancers, aligned to the goals you set. For example, try prompts like: “Generate a Bicep template for a zonally resilient VM setup.” “Create Terraform templates for a resilient architecture with VMs, AKS, and Storage.” The payoff: new services reach production already meeting your high availability standards, and the expensive redesign never has to happen. Get resilient: close the gaps in what you already run Applications change. The configuration that was right at first deployment is often not the one a business-critical workload needs two years later. This is where the resiliency agent turns posture insight into prioritized, executable action. Ask the agent to assess your environment, and it surfaces the resources and service groups that are not zone resilient, that are exposed to a datacenter outage, or that have key alerts waiting on attention. Every recommendation carries cost-aware decision support, qualitative indicators that flag whether a fix requires additional spend, downtime, or redeployment, so your team can sequence remediation against business value instead of guesswork. When you are ready to act, the agent generates ready-to-deploy scripts to configure zone resiliency for supported resource types, or targeted IaC snippets to close one specific gap. Try prompts like: “Assign resiliency goals for my application.” “Give me the posture of my service group: Contoso Payments.” “Enable zonal resiliency for my PostgreSQL server.” “Generate scripts to create a zonally resilient storage account.” This is a human-in-the-loop model by design. The agent brings the analysis, the recommendations, and the code. You keep full control over execution. Remediation gets faster without giving up governance. Stay resilient: what comes next Resiliency is not only about withstanding a zone outage. It is about protecting your data and knowing you can recover when something does go wrong. Recovery orchestration plans and zone drills are available today in Azure Infrastructure Resiliency Manager, and we are bringing both into the agent experience next. That closes the loop: assess, remediate, and validate recovery readiness in the same conversation. Get started with the public preview Open Azure Copilot and select the Resiliency Agent from the dropdown or the side panel. Three actions will get you value in the first session. Model your application. The agent works from your application, not a flat list of resources, so make sure it is represented as a service group that reflects your latest resource discovery. You can create service groups natively through the agent. Try: “Create a service group for my application.” Find your gaps. Ask which of your service groups and resources are not zone resilient. Most teams uncover exposure that was previously invisible. See Set resiliency goals and track compliance. Design it in. Ask for a Bicep template with zone-redundant defaults for a workload you plan to deploy and see how much retrofit effort disappears. See Generate resilient Bicep templates. What to expect in the preview Ready-to-deploy zone resiliency scripts are supported for Azure services that have zonal resiliency support in Infrastructure Resiliency Manager. See the support matrix for current coverage. Some advanced configurations, including multi-user authorization and Azure Site Recovery, may require manual steps, and the agent provides guidance to help you complete them. Where we are going This public preview is a starting line, not a finish. We are building toward end-to-end, agent-led journeys across Start, Get, and Stay Resilient, with cross-agent orchestration that reaches into migration, deployment, and observability, and multi-surface delivery so resiliency validation shows up in your IDEs, APIs, and CI/CD pipelines, not only in Azure Copilot. Service coverage will keep expanding, and the guidance will keep getting richer. The goal is simple and ambitious: make resilient-by-design the path of least resistance for every application on Azure. Preview is where that gets shaped, so tell us what is working and what you need next at azureresiliency@microsoft.com. Start here: open Azure Copilot, select the resiliency agent, and ask which of your applications are not zone resilient yet. Resources Announcing Azure Infrastructure Resiliency Manager public preview Agents in Azure Copilot public preview Resiliency capabilities in Agents (preview) in Azure Copilot, Azure Infrastructure Resiliency Manager overview Get started with service groups Microsoft Learn Questions or feedback: azureresiliency@microsoft.com
Protect Azure Cosmos DB with vaulted backups using Azure Backup (public preview)
As organizations increasingly rely on Azure Cosmos DB to power mission‑critical, globally distributed applications, protecting this data from accidental deletion, malicious activity, and ransomware has become more important than ever. At MS Build 2026, we’re excited to announce the preview of Azure Backup for Cosmos DB, which introduces vaulted backups—a secure, isolated, and fully managed backup solution designed to strengthen cyber‑resilience and support compliance requirements. Why vaulted backups for Azure Cosmos DB? Azure Cosmos DB already provides built‑in data protection capabilities such as replication and availability features to help ensure application uptime. However, these capabilities alone may not be sufficient to protect against scenarios such as: Accidental or malicious deletion of data or accounts Compromised credentials or insider threats Ransomware attacks targeting production environments Compliance requirements that mandate off‑site, immutable backups Vaulted backups add an independent protection layer by storing backup copies in an Azure Backup vault, isolated from the source Cosmos DB account and managed through Azure Backup. How vaulted backups protect your Cosmos DB data With this preview, Azure Backup enables you to protect Azure Cosmos DB using a policy‑driven, automated backup experience. Once configured, Azure Backup manages backup scheduling, retention, and lifecycle without manual intervention. Key protection capabilities include: Isolation from production data: Vaulted backups are stored in a separate, Microsoft‑managed backup vault, ensuring that backup data remains protected even if the source Cosmos DB account is deleted or compromised. Resilience against ransomware and malicious attacks: Because backups are isolated and protected by Azure Backup security controls, attackers cannot directly access or tamper with recovery points, helping ensure reliable recovery when it matters most. Policy‑based backups with long‑term retention: Define backup schedules and retention periods using Azure Backup policies to support long‑term compliance and audit requirements. Security‑first design: Azure Backup safeguards vaulted backups using encryption, soft delete, immutability, and role‑based access control, helping protect backup data against unauthorized deletion or modification. Designed for compliance and enterprise resilience Vaulted backups for Azure Cosmos DB help organizations align with industry and regulatory expectations that require: Off‑site and isolated backup copies Strong access controls and separation of duties Protection against premature deletion Long‑term retention of critical data By integrating Cosmos DB protection into Azure Backup, customers can manage backups centrally alongside other Azure workloads using a consistent governance and monitoring experience. Getting started with the preview Please refer to the product documentation for details on supported scenarios, limitations, and onboarding steps. For Cosmos DB vaulted backup (preview), you incur charges from, 1 July 2026. Refer to Azure Backup pricing page and pricing calculator for more details.
Proactive Reliability Series — Article 1: Fault Types in Azure
Welcome to the Proactive Reliability Series — a collection of articles dedicated to raising awareness about the importance of designing, implementing, and operating reliable solutions in Azure. Each article will focus on a specific area of reliability engineering: from identifying critical flows and setting reliability targets, to designing for redundancy, testing strategies, and disaster recovery. This series draws its foundation from the Reliability pillar of the Azure Well-Architected Framework, Microsoft's authoritative guidance for building workloads that are resilient to malfunction and capable of returning to a fully functioning state after a failure occurs. In the cloud, failures are not a matter of if but when. Whether it is a regional outage, an availability zone going dark, a misconfigured resource, or a downstream service experiencing degradation — your workload will eventually face adverse conditions. The difference between a minor blip and a major incident often comes down to how deliberately you have planned for failure. In this first article, we start with one of the most foundational practices: Fault Mode Analysis (FMA) — and the question that underpins it: what kinds of faults can actually happen in Azure? Disclaimer: The views expressed in this article are my own and do not represent the views or positions of Microsoft. This article is written in a personal capacity and has not been reviewed, endorsed, or approved by Microsoft. Why Fault Mode Analysis Matters Fault Mode Analysis is the practice of systematically identifying potential points of failure within your workload and its associated flows, and then planning mitigation actions accordingly. A key tenet of FMA is that in any distributed system, failures can occur regardless of how many layers of resiliency are applied. More complex environments are simply exposed to more types of failures. Given this reality, FMA allows you to design your workload to withstand most types of failures and recover gracefully within defined recovery objectives. If you skip FMA altogether, or perform an incomplete analysis, your workload is at risk of unpredicted behavior and potential outages caused by suboptimal design. But to perform FMA effectively, you first need to understand what kinds of faults can actually occur in Azure infrastructure — and that is where most teams hit a gap. Sample "Azure Fault Type" Taxonomy Azure infrastructure is complex and distributed, and while Microsoft invests heavily in reliability, faults can and do occur. These faults can range from large-scale global service outages to localized issues affecting a single VM. The following is a sample taxonomy of common Azure infrastructure fault types, categorized by their characteristics, likelihood, and mitigation strategies. The taxonomy is organized from a customer impact perspective — focusing on how fault types affect customer workloads and what mitigation options are available — rather than from an internal Azure engineering perspective. Some of these "faults" may not even be caused by an actual failure in Azure infrastructure. They can be caused by a lack of understanding of Azure service designed behaviors (e.g., underestimating the impact of Azure planned maintenance) or by Azure platform design decisions (e.g., capacity constraints). However, from a customer perspective, they all represent potential failure modes that need to be considered and mitigated when designing for reliability. The following table presents infrastructure fault types from a customer impact perspective: Disclaimer: This is an unofficial taxonomy sample of Azure infrastructure fault types. It is not an official Microsoft publication and is not officially supported, endorsed, or maintained by Microsoft. The fault type definitions, likelihood assessments, and mitigation recommendations are based on publicly available Azure documentation and general cloud architecture best practices, but may not reflect the most current Azure platform behavior. Always refer to official Azure documentation and Azure Service Health for authoritative guidance. The "Likelihood" values below are relative planning heuristics intended to help prioritize resilience investments. They are not statistical probabilities, do not represent Azure SLA commitments, and are not derived from official Azure reliability data. Fault Type Blast Radius Likelihood Mitigation Redundancy Level Requirements Service Fault (Global) Worldwide or Multiple Regions Very Low High Service Fault (Region) Single service in region Medium Region Redundancy Region Fault Single region Very Low Region Redundancy Partial Region Fault Multiple services in a single Region Low Region Redundancy Availability Zone Fault Single AZ within region Low Availability Zone Redundancy Single Resource Fault Single VM/instance High Resource Redundancy Platform Maintenance Fault Variable (resource to region) High Resource Redundancy, Maintenance Schedules Region Capacity Constraint Fault Single region Low Region Redundancy, Capacity Reservations Network POP Location Fault Network hardware Colocation site Low Site Redundancy In future articles we will examine each of these fault types in detail. For this first article, let's take a closer look at one that is often underestimated: the Partial Region Fault. Deep Dive: "Partial Region Fault" A Partial Region Fault is a fault affecting multiple Azure services within a single region simultaneously, typically due to shared regional infrastructure dependencies, regional network issues, or regional platform incidents. Sometimes, the number of affected services may be significant enough to resemble a full region outage — but the key distinction is that it is not a complete loss of the region. Some services may continue to operate normally, while others experience degradation or unavailability. Unlike Natural Disaster caused Region outage, in the documented cases referenced later in this article, such "Partial Region Faults" have historically been resolved within hours. Attribute Description Blast Radius Multiple services within a single region Likelihood Low Typical Duration Minutes to hours Fault Tolerance Options Multi-region architecture; cross-region failover Fault Tolerance Cost High Impact Severe Typical Cause Regional networking infrastructure failure affecting multiple services, regional storage subsystem degradation impacting dependent services, regional control plane issues affecting service management These faults are rare, but they can happen — and when they do, they can have a severe impact on customer solutions that are not architected for multi-region resilience. What makes Partial Region Faults particularly dangerous is that they fall into a blind spot in most teams' resilience planning. When organizations think about regional failures, they tend to think in binary terms: either a region is up or it is down. Disaster recovery runbooks are written around the idea of a full region outage — triggered by a natural disaster or a catastrophic infrastructure event — where the response is to fail over everything to a secondary region. But a Partial Region Fault is not a full region outage. It is something more insidious. A subset of services in the region degrades or becomes unavailable while others continue to function normally. Your VMs might still be running, but the networking layer that connects them is broken. Your compute is fine, but Azure Resource Manager — the control plane through which you manage everything — is unreachable. This partial nature creates several problems that teams rarely plan for: Failover logic may not trigger. Most automated failover mechanisms are designed to detect a complete loss of connectivity to a region. When only some services are affected, health probes may still pass, traffic managers may still route requests to the degraded region, and your failover automation may sit idle — while your users are already experiencing errors. Recovery is more complex. With a full region outage, the playbook is straightforward: fail over to the secondary region. With a partial fault, you may need to selectively fail over some services while others remain in the primary region — a scenario that few teams have tested and most architectures do not support gracefully. The real-world examples below illustrate this clearly. In each case, a shared infrastructure dependency — regional networking, Managed Identities, or Azure Resource Manager — experienced an issue that cascaded into a multi-service fault lasting hours. None of these were full region outages, yet the scope and duration of affected services was significant in each case: Switzerland North — Network Connectivity Impact (BT6W-FX0) A platform issue resulted in an impact to customers in Switzerland North who may have experienced service availability issues for resources hosted in the region. Attribute Value Date September 26–27, 2025 Region Switzerland North Time Window 23:54 UTC on 26 Sep – 21:59 UTC on 27 Sep 2025 Total Duration ~22 hours Services Impacted Multiple (network-dependent services in the region) According to the official Post Incident Review (PIR) published by Microsoft on Azure Status History, a platform issue caused network connectivity degradation affecting multiple network-dependent services across the Switzerland North region, with impact lasting approximately 22 hours. The full root cause analysis, timeline, and remediation steps are documented in the linked PIR below. 🔗 View PIR on Azure Status History East US and West US — Managed Identities and Dependent Services (_M5B-9RZ) A platform issue with the Managed Identities for Azure resources service impacted customers trying to create, update, or delete Azure resources, or acquire Managed Identity tokens in East US and West US regions. Attribute Value Date February 3, 2026 Regions East US, West US Time Window 00:10 UTC – 06:05 UTC on 03 February 2026 Total Duration ~6 hours Services Impacted Managed Identities + dependent services (resource create/update/delete, token acquisition) 🔗 View PIR on Azure Status History Azure Government — Azure Resource Manager Failures (ML7_-DWG) Customers using any Azure Government region experienced failures when attempting to perform service management operations through Azure Resource Manager (ARM). This included operations through the Azure Portal, Azure REST APIs, Azure PowerShell, and Azure CLI. Attribute Value Date December 8, 2025 Regions Azure Government (all regions) Time Window 11:04 EST (16:04 UTC) – 14:13 EST (19:13 UTC) Total Duration ~3 hours Services Impacted 20+ services (ARM and all ARM-dependent services) 🔗 View PIR on Azure Status History Wrapping Up Designing resilient Azure solutions requires understanding the full spectrum of potential infrastructure faults. The Partial Region Fault is just one of many fault types you should account for during your Failure Mode Analysis — but it is a powerful reminder that even within a single region, shared infrastructure dependencies can amplify a single failure into a multi-service outage. Use this taxonomy as a starting point for FMA when designing your Azure architecture. The area is continuously evolving as the Azure platform and industry evolve — watch the space and revisit your fault type analysis periodically. In the next article, we will continue exploring additional fault types from the taxonomy. Stay tuned. Authors & Reviewers Authored by Zoran Jovanovic, Cloud Solutions Architect at Microsoft. Peer Review by Catalina Alupoaie, Cloud Solutions Architect at Microsoft. Peer Review by Stefan Johner, Cloud Solutions Architect at Microsoft. References Azure Well-Architected Framework — Reliability Pillar Failure Mode Analysis Shared Responsibility for Reliability Azure Availability Zones Business Continuity and Disaster Recovery Transient Fault Handling Azure Service Level Agreements Azure Reliability Guidance by Service Azure Status History
