Bare Metal Cyber

The board slide looks reassuring. It shows three cloud provider logos, arrows between regions, and a title that promises there is no single point of failure. The story is simple and comforting: if one provider has an outage or a security event, your critical services will fail over to another and keep running. You can take that message to the board, to regulators, and to customers as proof that you are serious about resilience. This audio is part of the Wednesday “Headline” feature from Bare Metal Cyber Magazine, developed by Bare Metal Cyber, and it is about what really sits behind that slide.

The uncomfortable truth is that for many organizations, multi-cloud changes the logos but not the backbone. You do not build three independent stacks. You build one fragile spine of identity, connectivity, automation, and operations, then stretch it across two or three providers. The identity provider (I D P) is still singular. The private network fabric is still central. The deployment pipeline is still one set of templates and one team pushing changes. When that spine fails or is compromised, every “independent” cloud fails together. Over the next few years, the important question will not be whether you are multi-cloud. It will be whether you actually have independent failure domains, or whether you have just created a more expensive way to fail all at once.

On paper, the resilience case for multi-cloud is irresistible. You tell the board that instead of betting everything on a single hyperscaler, you will spread critical workloads across multiple providers and reduce concentration risk. It sounds like portfolio theory applied to infrastructure: do not put all your eggs in one basket, diversify your positions, and reduce exposure to any single bad event. Regulators and insurers are receptive to that framing because it mirrors how they already think about risk. It gives leaders a clean narrative that justifies very large spend on cloud transformation.

Inside the organization, that narrative quickly turns into commitments. Architecture decks show active active services across clouds, seamless failover, and containerized workloads that can be redeployed anywhere on short notice. Platform teams promise that infrastructure as code will abstract away provider differences. Commercial teams talk about stronger negotiating positions with providers because you are not locked in. Security leaders echo the talking points, framing multi-cloud as a way to reduce dependency on any single control plane or trust model. The shared assumption is that more providers automatically mean more resilience, and that becomes the baseline expectation in risk conversations.

Reality is usually far messier than those early conversations admit. Budget limits, skill shortages, and legacy systems mean you rarely get the clean architecture from the slide deck. One cloud inevitably becomes the primary environment, often because it has the best commercial deal or the most existing workloads. Other providers become homes for a handful of opportunistic projects, acquisitions, or executive experiments. Operational teams quietly standardize on a single identity tenant, a single I D P configuration, a single deployment pipeline, and a single observability stack. Instead of three independent environments, you end up with one intertwined ecosystem stretched across multiple providers. The resilience story starts to drift away from the backbone you are actually building.

When leaders talk about multi-cloud, they tend to picture separate stacks with different regions, consoles, and services. What gets far less airtime is the small set of shared systems those stacks quietly depend on. In most enterprises, there is one I D P, one internal Domain Name System (D N S) path, one software defined wide area network (S D W A N) overlay, and one set of device and endpoint controls. Whether a workload lands in one hyperscaler or another, the people who access it, the pipelines that deploy it, and the tools that observe it all ride on the same narrow spine. If that spine is fragile, it does not matter how many clouds are attached to it.

Identity is the clearest example. Most organizations centralize authentication and authorization through a single I D P tenant with one set of conditional access policies and device checks. That tenant becomes the root of trust for consoles, A P I access, and runbooks in every cloud. Networking tells a similar story. Your multi-cloud setup is often an overlay on a single S D W A N mesh, one private connectivity broker, and one set of firewall and routing policies. A D N S misconfiguration, a broken secure web gateway rule, or a flawed S D W A N software push can make all of your clouds equally unreachable at the same moment, regardless of how many regions or providers you have on the diagram.

Tooling completes the picture of shared backbones. Continuous integration and continuous delivery (C I C D) pipelines, secrets managers, configuration systems, observability platforms, ticketing tools, and incident response consoles are almost always centralized, even when workloads are not. A mis-pushed template, a compromised runner, or a broken agent rollout can ripple quietly until it creates identical conditions in multiple clouds. The more providers you add, the more traffic and trust you channel through those shared backbones, concentrating risk instead of dispersing it. From a leadership perspective, the first hard question is whether you can point to independent backbones, or whether you simply stretched one fragile one across multiple providers and declared victory.

When you peel back the architecture diagrams, the core problem is that most multi-cloud environments do not create independent failure domains. They create separate compute islands that depend on the same handful of control points. An I D P outage, a bad conditional access rollout, or an admin lockout does not just affect one console. It affects all of them because every administrator path and every automation token depends on that same gatekeeper. In a serious security incident, the team discovers that the backup cloud is gated by the same login page that just failed or was intentionally shut down to contain an attack. The illusion of independence disappears exactly when you need it most.

Operational failures behave in the same way. A single mis-pushed infrastructure as code change can stretch across every provider if your templates and pipelines are centralized. One flawed Terraform module, a risky Kubernetes admission policy, or an over-broad network rule pattern can propagate into multiple clouds before anyone notices. From a risk perspective, that is not diversification. It is a mechanism for synchronizing failures you have not discovered yet. Even routine changes, such as rotating keys, updating agents, or modifying logging sinks, can simultaneously damage visibility or access across all environments if they share the same automation backbone.

The data plane adds another layer of coupling. Many multi-cloud designs converge critical traffic through shared data stores, event streams, or integration layers that sit in a primary cloud or in a core data center. Business applications may technically run in different providers, but they still depend on a single database cluster, a single message bus, or a single application programming interface (A P I) gateway to do anything useful. When that shared dependency falters, it takes down multiple clouds in one move. Leaders who assume that spreading workloads equals spreading risk often first see these dependencies drawn as a single red box in the center of an incident review diagram.

If the data plane shows where the traffic flows, the control plane shows who is really in charge. In most multi-cloud environments, control planes are where centralization quietly creeps back in. One I D P governs access to all consoles and APIs. One configuration management platform and one C I C D stack push changes everywhere. One set of policy engines and security tools define what is allowed, alert worthy, or blocked. On a slide, you may list three or four cloud providers. In reality, you have one or two systems through which every meaningful decision flows. That is not automatically wrong, but it is very different from the independence story many leaders think they are buying.

Centralized control planes can be powerful when used deliberately. They give you consistent policy enforcement, shared visibility, and global levers for controlled change. They make it easier to prove to auditors that policies apply everywhere and to demonstrate a unified view of risk. But they also concentrate blast radius. If a threat actor compromises your C I C D platform, they now have a staging ground that touches multiple clouds at once. If your policy engine is misconfigured, you can unintentionally weaken controls across your entire estate in a single deployment. When regulators ask how you prevent a single control failure from affecting everything, pointing to more cloud logos is not an answer. You have to show that your control planes themselves are designed with isolation and recovery in mind.

Vendor preferences complicate this picture further. Security and platform teams often standardize on a single cloud native security suite, a unified observability platform, or a preferred Kubernetes control plane. Those decisions are usually pragmatic. You do not want four dashboards, four agent types, and four policy languages. But they also mean that a single vendor outage, an integration bug, or even a commercial dispute can simultaneously erode your defenses across every provider. The illusion of choice is that you have multiple clouds. The reality is that you have one control stack holding all of them together. The key question is whether that stack is architected as a robust backbone or as an elegant single point of failure.

If you genuinely want multi-cloud to improve resilience, the goal shifts from running in more places to failing in smaller, more contained ways. That means designing for isolation first and distribution second. Instead of asking whether a workload can technically run in two providers, the better starting point is to ask what would have to go wrong for both to fail at once. For a small set of truly critical services, that might mean independent identity paths, separate administration groups, different operational workflows, and distinct data paths, even if that costs more and is less convenient. For many other systems, you may decide that single cloud with strong recovery is a better trade.

Real isolation usually requires breaking some of the elegant centralization you have spent years building. You may need separate identity tenants for break glass access, using different factors and devices than your daily login. Network paths between environments may need to be segmented rather than running entirely over one pristine but brittle private backbone. Automation that touches multiple providers might need guardrails such as per cloud approval steps, narrower scopes, or even completely separate pipelines for your most sensitive stacks. None of this looks as clean as a single unified architecture diagram, but it matters more than drawing an extra logo in the corner of the slide.

Data and operations complete the picture of genuine separation. For the systems where you truly cannot tolerate correlated failure, leaders may need to fund independent data replication paths with different schedules, different mechanisms, and different teams owning the runbooks. Incident response exercises should assume that your central control planes are unavailable or compromised and test whether the supposed secondary environment can really stand on its own. The right outcome is not universal perfection. It is a clear, deliberate map of where you accept shared backbones and where you pay for genuine separation. That map is what lets you talk about multi-cloud resilience without crossing your fingers under the table.

At some point, all of this comes back to a room where you are explaining risk and spend to non technical leaders. The temptation is to keep the story simple and say that more clouds equal more safety. That story is easy to sell but hard to defend once people start asking about real failure modes. A better posture is to be explicit that multi-cloud is not a magic shield. It is one of several tools you can use to shape failure domains and buy time and options when things go wrong. That framing lets you talk about the backbone instead of brand names and sets more realistic expectations for how much resilience a given design actually delivers.

Owning the trade offs also means putting clear boundaries around ambition. You can acknowledge that truly independent stacks are expensive, complex, and appropriate only for a small subset of services where correlated failure is unacceptable. For the rest, you might position multi-cloud as a way to reduce vendor lock in or to access differentiated services, while openly admitting that it does not eliminate shared dependencies on identity, networking, and automation. Boards and regulators are usually more comfortable with a well explained, partially mitigated risk than with a glossy promise of seamless failover. The important part is to show your reasoning, not just your diagrams.

Internally, you need to align incentives with the story you tell externally. If architects and operators are rewarded purely for efficiency and standardization, they will naturally centralize control planes and tooling, even as leadership talks about independent failure domains. If procurement optimizes only for volume discounts with a primary provider, multi-cloud will quietly degrade into multi-logo. As a leader, you can reset metrics around blast radius, recovery paths, and control plane resilience, and ask teams to demonstrate how those goals appear in design reviews and incident simulations. That is how multi-cloud stops being a mirage and becomes an honest, bounded part of your resilience strategy.

At its heart, this topic is about the difference between where your workloads run and where your dependencies live. Multi-cloud can spread compute across providers, but resilience only improves when failure domains, control planes, and operational paths are deliberately separated instead of quietly shared. The mirage appears when boards see multiple logos and assume independent safety nets, while the real backbone of identity, connectivity, automation, and data remains centralized and fragile. Closing that gap is not about buying more platforms. It is about redesigning how your organization couples trust, access, and change.

When you internalize that lens, multi-cloud stops being a checkbox and becomes a way of seeing your architecture. You start asking which systems truly need independent failure domains, which control planes must be able to fail safely, and where centralized convenience is an acceptable trade off. As you prepare for your next architecture review or board update, the most useful questions may be simple ones. What has to break for multiple clouds to fail together, who owns the backbone that answer depends on, and where will you consciously accept the mirage versus paying for real separation.