The Tool Desk
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What “reliable compute” should mean for this decision
Cloud reliability is not a single provider score. It is the result of several controls that address different failure modes:
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- Failure-domain design: Can an application run across independent zones or regions, or is it tied to one facility?
- SLA and remedy: What availability target is written into the contract, how is it measured, and is the remedy a service credit rather than cash compensation?
- Capacity assurance: Are servers merely available on demand, or can you reserve capacity in a named zone or data center?
- Economics: Can you right-size instances, and will outbound data transfer make a distributed design unexpectedly expensive?
- Geography and sovereignty: Where is the workload physically hosted, and does that location satisfy latency, residency, or regulatory requirements?
- Operations: How much of the database, Kubernetes, networking, backup, monitoring, and failover stack must your own team operate?
A provider’s headline SLA does not make a single-zone application resilient. A multi-zone design with tested failover can survive a facility problem even when the provider’s contractual target is lower than a rival’s. Conversely, a high SLA is of limited value if you cannot obtain capacity, restore data, or move traffic during an incident.
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The global infrastructure market is concentrated among a few hyperscalers. The UK Competition and Markets Authority estimated that, in 2024, AWS held 30–40% of global data-center capacity, Microsoft held 30–40%, Google held 10–20%, Oracle held 5–10%, and CoreWeave and IBM each held 0–5%. The CMA’s 2025–2026 entries are forecasts rather than measured historical shares, and it notes that provider-submitted capacity data may slightly overstate individual shares.
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| Provider or group | Estimated global data-center capacity, 2024 | Qualification |
|---|---|---|
| AWS | 30–40% | Estimate from the UK Competition and Markets Authority, 2025 |
| Microsoft | 30–40% | Estimate from the UK Competition and Markets Authority, 2025 |
| 10–20% | Estimate from the UK Competition and Markets Authority, 2025 | |
| Oracle | 5–10% | Estimate from the UK Competition and Markets Authority, 2025 |
| CoreWeave | 0–5% | Estimate from the UK Competition and Markets Authority, 2025 |
| IBM | 0–5% | Estimate from the UK Competition and Markets Authority, 2025 |
That concentration creates several practical reasons to evaluate smaller or differently structured providers: a shortage of a particular instance family, exposure to one control plane, a regional outage, changing transfer charges, or a requirement for physical servers. An alternative does not need to match hyperscaler scale to be useful; it needs to provide the capacity, location, controls, and operating model your workload actually requires.
The OECD’s 2025 methodology illustrates the same point from a market-measurement perspective. It examines AWS, Azure, Google Cloud, Alibaba Cloud, Tencent Cloud, Huawei Cloud, Hetzner, OVHcloud, and Exoscale, estimating that the nine-provider set covers more than 70% of global cloud-infrastructure spending. Its indicative estimates put AWS at 31% of the global public-cloud market, Azure at 24%, Google Cloud at 11.5%, Alibaba Cloud at 4%, Tencent Cloud at 2%, and each of the listed European providers below 1%. OECD cautions that these are general public-cloud estimates, sometimes using company revenue as a proxy, and are not AI-only or reliability rankings.
Shortlist at a glance
The table separates commitments stated by each provider from capabilities that still require architectural validation. “Not stated” means the cited provider material did not establish a comparable value; it is not evidence that the capability is absent.
| Provider | Failure-domain design | SLA and remedy | Capacity assurance | Economics | Geography and sovereignty | Operations |
|---|---|---|---|---|---|---|
| Oracle Cloud Infrastructure | The cited pricing page does not set one universal zone or region design target; validate the chosen service and region. | The cited pricing material does not state a compute availability percentage or credit remedy. | On-demand compute with fine-grained resizing; reservation terms require a separate regional check. | Scale by one CPU core and 1 GB of memory; 10 TB monthly free egress; Oracle says egress can be up to 10 times lower than other providers. Pricing comparisons are labeled December 5, 2024. | Pricing is described as consistent across public and government regions; actual service and residency availability varies by region. | Broader platform services are available, but the cited material does not establish parity with a hyperscaler’s managed-service catalog. |
| OVHcloud | Paris deployment spans three independent availability zones. | 99.99% availability is listed for compatible compute, networking, storage, Kubernetes, and database services; remedy terms must be read in the applicable SLA. | Multi-zone deployment provides architectural redundancy; a reservation guarantee is not stated in the cited page. | Compatible multi-zone services cost approximately 10% more than single-zone services; no inter-zone traffic charges are stated for that design. | Paris is the documented example; select another region if latency or residency requires it. | Terraform and OpenTofu support is stated, alongside managed Kubernetes and managed databases for listed services. |
| Hetzner | The cited SLA applies to each Cloud Server or vServer; a multi-zone architecture must be designed and tested by the customer. | 99.9% monthly availability target with Cloud Credit compensation when the threshold is exceeded. | On-demand virtual servers; guaranteed zone or data-center reservation is not stated. | Included outbound traffic varies from 0.5 TB to 5 TB per month; monthly billing and cancellation at any time are stated. | Choose from the locations offered for the required product; the cited material does not define a sovereignty guarantee. | Best suited to straightforward VM hosting; the cited material does not demonstrate hyperscaler-level managed-service breadth. |
| IBM Cloud bare metal | Reservations target a selected availability zone and data center, reducing dependence on an on-demand supply pool. | The cited bare-metal pricing page does not state one comparable availability percentage or credit schedule. | Reserved capacity is guaranteed in the chosen zone and data center for the committed term. | Up to 35% discount for one-year reservations and up to 55% for three-year reservations; more than 11 million configuration combinations and 20 TB of cost-free bandwidth are stated. | Selection is made at zone and data-center level; verify the location against residency and latency requirements. | Physical-server operations suit isolated, steady workloads; the cited material does not establish serverless or managed-service breadth. |
Oracle Cloud Infrastructure: flexible sizing and transfer economics
Where OCI is strongest
OCI is the most compelling option in this shortlist when utilization is uneven or data movement is a major part of the bill. Its compute pricing model allows a running shape to be resized in one-CPU-core and 1-GB increments across AMD, Arm, and Intel processors. That granularity can reduce the waste created by choosing the next large fixed instance size simply to obtain a little more memory or CPU.
OCI also publishes a monthly free egress allowance and says its outbound rates can be substantially lower than those of other providers. For applications that serve large files, replicate data between clouds, or send results to customers outside the provider network, transfer economics can matter as much as hourly compute. Treat the published comparison as a dated reference: Oracle labels the cited prices as those published on December 5, 2024, so obtain a current regional price sheet before signing a commitment.
How to evaluate OCI for a real workload
- Measure the workload’s shape: record CPU, memory, storage, network throughput, and burst behavior over at least a representative billing period.
- Model transfer separately: classify traffic as internet egress, cross-zone traffic, cross-region replication, or traffic to another cloud. Apply current regional rates to each class rather than using one blended estimate.
- Check the exact region: confirm that the required processor family, storage type, managed database, Kubernetes service, and compliance controls exist together in the target region.
- Test resizing and recovery: verify that the selected image, boot volume, licensing, autoscaling policy, and orchestration tooling handle the smaller increments you intend to use.
Trade-offs
OCI’s pricing advantages do not remove the need for platform engineering. A workload that depends on proprietary APIs, specialized identity integrations, or region-specific managed services may require redesign. The pricing page also does not establish a single availability target applicable to every compute shape, so evaluate the specific service SLA and build redundancy above it.
OVHcloud: a documented three-zone pattern
What the Paris 3-AZ design provides
OVHcloud’s Paris example places compatible services in three independent availability zones. The provider lists a 99.99% availability SLA for compute instances, floating IP, load balancing, gateway, block and object storage, managed Kubernetes, and managed databases. The design is therefore more than a virtual-machine placement option: it covers the principal layers needed to keep an application serving when one zone fails.
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OVHcloud states that compatible multi-zone services cost approximately 10% more than their single-zone counterparts and that traffic between the zones carries no inter-zone charge. That combination makes the economics easier to model than a design in which every replication packet is metered, although the additional replicas, storage, and database capacity still increase total spend.
How to build around zone failure
- Make the application stateless where possible: place sessions in a replicated data store and keep durable files in replicated object storage.
- Spread compute deliberately: schedule instances, containers, and worker pools across all three zones rather than allowing an autoscaler to concentrate them.
- Put traffic management above the zones: use the documented load-balancing and floating-IP services to steer traffic away from an unhealthy zone.
- Replicate state: select a database topology that can promote a healthy member without manual access to the failed zone.
- Exercise the failure: block one zone in a staging or controlled production test and measure recovery time, data loss, queue behavior, and operator actions.
When OVHcloud is the better fit
Choose this path when a published multi-zone pattern is central to the design and the team is prepared to deploy across zones from the beginning. Terraform and OpenTofu support can make the topology repeatable. It is less suitable when the application is a single large server, depends on a service unavailable in the selected region, or cannot tolerate the operational complexity of distributed state.
Hetzner: simple virtual machines with a clear monthly target
What the SLA does and does not promise
Hetzner’s cloud SLA, created and changed March 16, 2026, says the company will make commercially reasonable efforts to provide 99.9% monthly availability for every Cloud Server and vServer. When downtime exceeds the threshold, compensation is issued as Cloud Credit. That is a defined remedy, but it is not the same as guaranteed application uptime, and credits do not restore lost data or compensate for business interruption.
The customer remains responsible for redundancy. A single virtual server can still fail because of an operating-system error, a bad deployment, a full disk, or a regional incident. Put the service behind health-checked traffic routing, keep backups outside the failure domain, and maintain an image or infrastructure definition that can recreate the server elsewhere.
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Cost and capacity characteristics
Hetzner’s cloud page states that included outbound traffic ranges from 0.5 TB to 5 TB per month, depending on the product. Billing is monthly, with cancellation at any time. Those terms are attractive for predictable VM workloads, development environments, web applications, and worker fleets whose transfer volume fits the allowance.
For a design with heavy cross-region replication, large public downloads, or a managed database requirement, calculate the complete operating cost and service gap. The cited material does not demonstrate the managed-service breadth available from the largest providers, so your team may need to run backups, patching, orchestration, monitoring, and failover components itself.
IBM Cloud bare metal: reserve the physical capacity you need
Why bare metal changes the capacity question
IBM’s reservation model guarantees capacity in the availability zone and data center selected by the customer for the committed term. That directly addresses a common failure mode of on-demand infrastructure: the desired machine type exists in the catalog but cannot be allocated during a regional capacity squeeze.
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IBM offers hourly and monthly pay-as-you-use bare-metal billing without an upfront payment. Reservations can provide discounts of up to 35% for one-year terms and up to 55% for three-year terms. The commitment trades flexibility for supply certainty and a lower unit price, so reserve only the baseline capacity you can forecast with confidence.
Workloads that benefit
- Databases or analytics systems that need dedicated physical resources and stable performance.
- Licensed software tied to a server configuration or physical-core count.
- Security-sensitive workloads that require isolation from multi-tenant virtual machines.
- Steady production capacity where replacing a failed server is more disruptive than operating a cluster of reserved machines.
IBM states that its classic bare-metal infrastructure supports more than 11 million configuration combinations and includes 20 TB of cost-free bandwidth. Those figures indicate breadth and a substantial transfer allowance, but they do not replace a workload-specific benchmark. Confirm processor generation, storage layout, network interface, provisioning time, spare capacity, and the process for replacing a failed host.
Operational trade-off
Bare metal gives you control and isolation, not automatic resilience. Build a cluster, replicate data, automate reprovisioning, and document how traffic moves when a physical host or data center is unavailable. If the workload requires serverless functions, deeply integrated managed queues, or a large catalog of hosted databases, a bare-metal-first design may require more engineering than a virtual-machine approach.
Choose by the failure you are trying to prevent
“We cannot get the instance type we need.”
Prioritize capacity assurance rather than a lower list price. IBM’s zone-and-data-center reservation model is the clearest fit in this shortlist. For other providers, ask for written confirmation of capacity, lead times, quota processes, and the behavior of autoscaling during a regional shortage. Keep an alternate instance family or provider tested if the workload can tolerate it.
“A single facility outage would stop us.”
Use a multi-zone architecture, not merely a provider with a high SLA. OVHcloud’s three-zone pattern is the most explicit documented example here. Replicate compute and state, place traffic management outside the failed component, and test the actual promotion and routing sequence.
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“Outbound transfer is unpredictable.”
Start with OCI’s granular compute and published egress allowance, or Hetzner if your VM’s traffic fits its included monthly range. In either case, build a traffic ledger that distinguishes internet delivery, replication, backups, and cross-provider traffic. A cheap VM can become expensive when every read or backup crosses a metered boundary.
“We need physical isolation.”
IBM bare metal is the direct candidate. Compare the operational cost of dedicated hardware with the cost of implementing clustering, patching, monitoring, spare capacity, and recovery yourself. Isolation is valuable only when the surrounding design can still tolerate a host failure.
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“We need a small operational footprint.”
Favor the provider whose managed database, Kubernetes, load-balancing, identity, backup, and observability services match your team’s skills. The cited material confirms selected managed services for OVHcloud but does not establish equivalent breadth for every provider. Obtain a service-by-service inventory before migrating a platform that currently relies on hosted control planes.
“We need a second provider to reduce lock-in.”
Separate portability from duplication. Keep infrastructure in Terraform or OpenTofu where supported, package applications in portable containers, use open protocols for queues and databases, and export backups in formats you can restore elsewhere. A dormant account is not a failover plan; regularly provision a small environment, restore data, and send test traffic through it.
A practical migration and resilience plan
1. Define the service objective
Write the required recovery-time objective, recovery-point objective, latency range, throughput, data residency, and maximum acceptable monthly spend. Identify whether the business needs continuous service, a warm standby, or simply a rebuildable environment. This prevents a provider SLA from becoming a substitute for a business requirement.
2. Inventory hidden dependencies
List identity providers, DNS, certificates, container registries, package mirrors, monitoring, logging, backups, queues, object storage, license servers, and external APIs. Mark every dependency that would fail if the primary cloud’s control plane or network became unreachable.
3. Select the failure domains
Decide whether the minimum design is two zones, three zones, two regions, or a primary and an independently operated standby. Place quorum-based systems according to their election rules; spreading nodes without understanding quorum can reduce availability instead of improving it.
4. Establish capacity before cutover
Request quotas, verify instance availability, and reserve the baseline where the provider offers a reservation mechanism. For burst capacity, pre-approve alternate instance families and document what the autoscaler should do when the preferred type is unavailable.
5. Model the full bill
Include compute, storage, snapshots, public IPs, load balancing, managed control planes, backups, support, inter-zone or inter-region transfer, internet egress, and the engineering time required to operate missing services. Recheck all prices immediately before commitment because the cited OCI comparison is dated and other prices can change by region or product.
6. Automate an equivalent environment
Keep network, identity roles, firewall rules, instances, disks, databases, DNS records, and monitoring definitions in version-controlled infrastructure code. Make secrets external to the code and test a clean deployment from an empty account or project.
7. Prove backup restoration
Set a restoration schedule, record the time and operator steps, and verify application-level consistency rather than merely checking that a snapshot exists. Store at least one copy outside the primary failure domain and confirm that credentials and encryption keys are also recoverable.
8. Run controlled failure tests
Test loss of an instance, a zone, a database primary, a load balancer, a DNS provider, and the provider API access path. Measure detection, promotion, routing convergence, data loss, customer-visible errors, and the point at which a human must intervene.
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Read the exact SLA for each service, including exclusions, measurement windows, maintenance treatment, credit limits, and claim procedures. Document how to export data, release reserved capacity, cancel commitments, and operate the standby if the primary provider becomes uneconomic or unavailable.
Common mistakes that make an alternative less reliable
- Choosing on hourly price alone: a lower VM rate can be outweighed by transfer, backup, support, and engineering costs.
- Confusing an SLA with an architecture: a credit after downtime does not keep a single-instance application online.
- Ignoring control-plane dependencies: a healthy workload may still be hard to repair if deployment, identity, DNS, or secrets services are unavailable.
- Reserving too much: long commitments lower unit cost but can strand money when demand, processor needs, or geography changes.
- Failing over only compute: moving application servers without databases, queues, certificates, and observability produces a nominal standby that cannot serve users.
- Assuming a second region is independent: verify power, networking, identity, DNS, and support dependencies rather than relying on labels alone.
- Skipping restoration drills: an untested backup is an assumption, not a recovery capability.
How to make the final choice
Select OCI when right-sizing and outbound-data economics dominate, provided the required services and regional controls are available. Select OVHcloud when a documented three-zone topology and published service targets justify the additional multi-zone cost and operational complexity. Select Hetzner when you need uncomplicated virtual machines, transparent monthly transfer allowances, and a flexible billing relationship, while accepting that more of the platform may be yours to operate. Select IBM Cloud bare metal when dedicated physical capacity, isolation, and a predictable baseline matter more than a broad serverless ecosystem.
For many organizations, the most reliable answer is not one replacement provider but a layered design: a primary environment chosen for the workload’s economics and managed services, plus an independently deployable recovery environment that is exercised on a schedule. Keep the application, data formats, infrastructure code, and operational runbooks portable enough that a capacity shortage or prolonged outage becomes a controlled procedure rather than an improvised migration.
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