Multi-Cloud Architecture
You do not have to run everything with one provider. We design across platforms where it improves resilience or fit, and say so when a single cloud is the better answer.
The case for spreading across providers
Committing everything to a single cloud is a reasonable default. It is simpler to operate, easier to hire for, and volume discounts are real. For most companies it is the right choice.
There are situations where it is not. A regulator may require that certain data stays within a jurisdiction where your primary provider has no region. An uptime commitment may exceed what one provider's SLA will support. A specific capability (a particular managed database, an edge network, a machine learning service) may be substantially better in one place while the rest of your system sits comfortably in another. And a company spending heavily with one vendor is in a materially different negotiating position when a credible alternative exists.
Each of these is a concrete reason. When one of them applies, a multi-cloud design is worth its cost. When none of them do, it usually is not.
What it actually costs to run
The infrastructure bill is the smaller part. The larger cost is operational, and it is easy to underestimate at the design stage.
Two platforms mean two identity and permission models, two sets of networking concepts, two billing structures, two security review processes, and two sets of quirks that only reveal themselves at three in the morning. Your engineers need working competence in both, which affects hiring and means on-call becomes harder to staff. Tooling that works cleanly on one provider often needs a layer of abstraction to work on both, and that abstraction is code someone has to maintain.
None of this is an argument against multi-cloud. It is an argument for having a clear reason before choosing it, because the overhead is permanent while the benefit may be occasional.
There is also a lighter version worth considering first. Putting your DNS, edge caching or object storage with a provider separate from your main compute gives you a degree of independence at a fraction of the operational cost, because those services are broadly interchangeable and rarely deeply coupled to the rest of the system. For a number of companies that is as far as the argument needs to go.
Redundancy only counts if it has been tested
The most common mistake we see is treating a second provider as a backup plan without ever exercising it.
An environment that has been provisioned in another cloud but never taken production traffic is not a failover target. Configuration drifts. Data replication falls behind or silently stops. Certificates expire. DNS records point to something that has changed. When the primary provider has an outage, that is a bad moment to discover any of it.
If resilience is the reason for the architecture, then the failover has to be rehearsed on a schedule, with the recovery time and any data loss measured and written down. That number is the actual resilience of the system. Everything else is intention.
A more honest way to think about lock-in
Complete portability is a goal that sounds prudent and works badly in practice. Achieving it means refusing every managed service and building on the lowest common denominator, which throws away most of the reason to use a cloud provider at all.
The useful version is narrower. For each significant dependency, know what replacing it would involve and roughly what it would take. Some answers are comfortable. Object storage and container runtimes are broadly similar everywhere. Some are not, and a proprietary managed service deeply woven through your application is expensive to leave.
Knowing which is which lets you make the trade deliberately. You can accept a deep dependency where the service is genuinely worth it, and keep an escape route where it is not. That is a far more practical position than either ignoring lock-in or trying to engineer it away entirely.
What you get
An assessment of whether you need it
Multi-cloud adds real operational cost. We start by establishing whether your resilience or independence requirement actually justifies it, because often it does not.
Workload placement plan
A decision for each component about where it should run and why, based on what each platform is genuinely good at rather than on splitting things evenly.
Portable infrastructure definitions
Infrastructure described as code, with platform-specific parts isolated, so moving a workload later is a scoped piece of work instead of a rebuild.
Failover design and runbooks
If redundancy is the goal, the failover path is documented, automated where practical, and tested. An untested failover is a theory.
Unified monitoring across providers
One place to see the state of the whole system. Separate dashboards per provider is how outages get noticed late.
Exit strategy for each dependency
For every managed service you rely on, a written answer to what replacing it would take. That answer is what turns lock-in from a worry into a known cost.
How we work
- 01
Establish the actual requirement
Regulatory constraints, uptime commitments, negotiating position, or a specific capability only one provider offers. The requirement determines the design, and sometimes it rules multi-cloud out.
- 02
Map workloads to platforms
We match each component to a platform based on its needs: data residency, latency to users, available managed services, and cost at your volume.
- 03
Design the connective layer
Networking, identity, secrets and deployment pipelines have to work consistently across providers. This layer is where most of the added complexity lives.
- 04
Implement with isolation in mind
Business logic stays independent of platform APIs, with provider-specific code kept at the edges where it can be swapped.
- 05
Test the failure scenarios
We run the failover, measure how long it takes and what is lost, and fix what does not work. This is repeated on a schedule rather than done once.
Tools and technology
Where a solid open-source tool exists, we choose it over a closed one. No lock-in to a single vendor, and costs you can actually predict.
- OpenTofu
- Terraform
- Kubernetes
- Docker
- PostgreSQL
- OpenTelemetry
- Grafana
- Prometheus
- AWS
- Google Cloud
- Microsoft Azure
- Cloudflare
Frequently asked questions
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Worried about depending on a single cloud provider?
Message usTell us what you run and what resilience you need, and we will give you an honest assessment of whether multi-cloud is worth it in your case.
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