“Canonical at Cloud Expo 2024” was a pre-event announcement, not a post-event report. Published on October 3, 2024, Canonical said it planned to attend Cloud Expo Madrid at IFEMA on October 16–17, with representatives at booth K87 in Hall 9. Its stated agenda covered private-cloud infrastructure, hybrid- and multi-cloud orchestration, enterprise AI and MLOps. The announcement does not verify which demonstrations ran, who spoke, whether a product launched or what happened after the event.
Canonical’s original announcement is available at Canonical at Cloud Expo 2024.
Event details Canonical published
| Item | Verified detail |
|---|---|
| Event | Cloud Expo Madrid 2024 |
| Dates | October 16–17, 2024 |
| Venue | IFEMA Madrid, Avenida del Parténon 5, Hall 9 |
| Canonical location | Booth K87 |
| Hours listed by Canonical | 9:30 a.m.–7:00 p.m. |
| Announcement | Published October 3, 2024 by Anastasia Kritskaya |
The name “Cloud Expo 2024” is ambiguous without the city. This article concerns the Madrid event, not Cloud Expo Europe in London, Cloud Expo North America or another regional show.
What Canonical said it wanted to discuss
Private-cloud implementation and management
Canonical presented itself as a provider of open-source infrastructure, enterprise support and services for building and operating private clouds. The announcement stayed at a high level: it did not identify a specific bill of materials or say that OpenStack, MicroCloud, Charmed Kubernetes, MAAS, Ceph or another named product would be demonstrated at booth K87.
#1 Best Overall
For a buyer, “private cloud” means taking responsibility for some combination of servers, virtualization or container control planes, networking, storage, identity, upgrades, security and resilience. Canonical’s broader commercial portfolio includes subscriptions, consulting, deployment and managed infrastructure, but those are different operating and cost models. Its current service categories are described at ubuntu.com/pricing.
Hybrid- and multi-cloud workload orchestration
Canonical said its team would discuss orchestrating workloads across hybrid and multi-cloud environments. The practical objective is a more consistent operating model across on-premises infrastructure and public clouds, while reducing dependence on a single provider.
- Workloads may need to move between private and public infrastructure.
- Teams may want common security, patching and support processes.
- Capacity, data-residency or regulatory requirements can require more than one location.
- Standard tooling can simplify operations, but it does not make clouds identical.
Portability still has limits. Storage formats, networking, identity, observability, GPU availability, managed databases and provider-specific services can create operational differences and lock-in. Canonical’s announcement did not promise universal application portability or eliminate those trade-offs.
Rank #2
Enterprise AI
Canonical said its experts would discuss enterprise AI projects and the difficulty of making them production-ready “in any environment.” That phrase is positioning, not a guarantee of equal features, performance or hardware support on every cloud, private platform, accelerator or compliance regime.
In practice, enterprise AI architecture may involve:
- Provisioning GPUs or other accelerators.
- Reproducible development environments and dependency management.
- Data access controls, governance and residency.
- Training and inference orchestration.
- Model and artifact management.
- Monitoring, security and ongoing maintenance.
The Cloud Expo announcement did not name a model framework, GPU vendor, benchmark, architecture diagram or event-specific AI product.
Rank #3
MLOps architecture
The announcement explicitly invited visitors with MLOps questions or a need to define an MLOps architecture. MLOps is the operational layer linking data preparation, experimentation, training, artifact management, deployment, monitoring and retraining.
- Prepare and govern data.
- Run repeatable experiments and training jobs.
- Track models, code and other artifacts.
- Deploy models for batch or online inference.
- Monitor quality, drift, cost, availability and security.
- Retrain and retire models under documented controls.
Canonical’s current commercial materials describe AI and MLOps support across the lifecycle from concept to production, with enterprise support available as an add-on to Ubuntu Pro at ubuntu.com/pricing/pro. That does not mean one turnkey Canonical product automatically solves every data-platform, model-serving or governance requirement.
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Canonical specifically invited people with AI or MLOps questions, infrastructure requirements, a need to define an MLOps architecture or an interest in its solutions. The implied buying audience included:
- Organizations evaluating private-cloud platforms.
- Teams operating hybrid or multi-cloud estates.
- Companies moving AI prototypes toward production.
- Infrastructure leaders seeking commercial support for open-source systems.
- MLOps teams that need architecture, deployment or lifecycle guidance.
What the announcement confirms—and what it does not
| Confirmed by Canonical’s announcement | Not confirmed by the announcement |
|---|---|
| Canonical planned to attend Cloud Expo Madrid 2024 | Actual attendance or visitor numbers |
| Booth K87 in Hall 9 | Specific demonstrations or technical configurations |
| Private-cloud and hybrid/multi-cloud discussions | Named speakers or a session schedule |
| AI, enterprise AI and MLOps topics | A product launch, partnership or benchmark |
| October 16–17, 2024 event dates | Post-event outcomes or customer deployments |
No post-event recap or independent event report was identified that verifies what happened at the booth. It is therefore inaccurate to write that Canonical “launched” a product or “demonstrated” a named stack at Cloud Expo based on this announcement alone.
Current commercial context (checked August 18, 2026)
These figures describe current pages, not what a 2024 attendee paid. Canonical can change prices, inclusions, support tiers, taxes and marketplace rates.
| Offering or plan | Current information | Typical responsibility model |
|---|---|---|
| Ubuntu Pro workstation, self-support | $25 per machine per year | Customer operates the system; subscription adds security and management features |
| Ubuntu Pro server, self-support | $500 per machine per year, with unlimited VMs on the listed plan | Customer operates the infrastructure |
| Personal Ubuntu Pro | Free for up to five machines; official Ubuntu Community members may receive coverage for up to 50 machines | Personal or community use under Canonical’s stated limits |
| Ubuntu Pro on public clouds | Metered hourly; Canonical says it typically represents about 3–4.5% of list compute cost, varying by provider | Cloud provider supplies compute; Canonical subscription is an additional metered charge |
| Managed infrastructure | Managed OpenStack and Kubernetes are listed; enterprise pricing is generally sales-led | Canonical takes on more operational work for recurring spend |
| Consulting and deployment | Architecture, deployment, integration and training services are listed | Project or service engagement rather than only software licensing |
See Canonical’s Ubuntu Pro plans, Ubuntu Pro overview and 30-day trial details. Canonical says support and Knowledge Base access are excluded from the trial.
Best Value
What these costs leave out
- Servers, storage, networking and backup.
- GPU or accelerator capacity for AI workloads.
- Cloud consumption and data-transfer charges.
- Internal platform-engineering and security labor.
- Monitoring, disaster recovery, training and integration.
Open-source software can reduce licensing barriers without making a production platform free. Buyers should separate subscription costs from infrastructure and staffing costs before comparing options.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How Canonical compares with other operating models
| Option | Operating model | Questions to ask |
|---|---|---|
| Canonical | Ubuntu-centered open infrastructure with subscriptions, support, consulting and optional managed services | Do we want Ubuntu standardization and control over private or hybrid infrastructure? |
| Public-cloud managed Kubernetes | Provider operates much of the control plane; customer pays cloud consumption and service charges | Is lower infrastructure ownership worth provider dependence and service-specific integration? |
| Red Hat OpenShift | Commercial enterprise Kubernetes platform with a different ecosystem and support model | Do existing Red Hat skills, tooling or contracts outweigh migration costs? |
| SUSE Rancher | Kubernetes and multi-cluster management alternative | Does its management approach fit our existing distributions and clusters? |
| Cloud-native AI platforms | Managed model, data or inference services with less infrastructure ownership | Do convenience and speed matter more than infrastructure control and portability? |
Potential comparison starting points are Amazon EKS, Azure Kubernetes Service, Google Kubernetes Engine, Red Hat OpenShift and SUSE Rancher. Their current prices were not established here, so consult each provider before making a financial comparison.
When Canonical is likely to fit
- Your estate is substantially Ubuntu-based.
- You need long-term security maintenance, fleet management or compliance tooling.
- You are prepared to operate open-source private-cloud or Kubernetes infrastructure, or to pay for managed services.
- You want one support relationship spanning bare metal, virtual machines, private cloud and public cloud.
- You are moving AI workloads from experimentation toward production and need architecture help.
When another approach may be better
- You want a fully managed public-cloud experience with minimal infrastructure ownership.
- Your team lacks Linux, Kubernetes, OpenStack or automation skills and cannot fund professional services.
- Your workloads depend heavily on provider-specific databases, AI APIs or networking.
- You need a narrowly specialized hosted AI platform rather than a broad infrastructure portfolio.
- You already have a mature, well-supported platform and little reason to change distributions or tooling.
- The deployment is small enough that a managed service costs less operationally than building a private platform.
Questions to ask before buying
- Which layer are we buying: Ubuntu Pro, consulting, deployment, managed infrastructure or all of them?
- Who will own patching, upgrades, incident response, backups and disaster recovery?
- What hardware, GPU capacity, storage performance and network topology does the workload require?
- How will identity, policy, logging, monitoring and data residency work across environments?
- Which applications rely on cloud-specific databases, APIs or storage?
- What is the three-year total cost after subscriptions, cloud usage, hardware and staff time?
- What support response times and contract terms are required for production?
The Bottom Line
Canonical’s Cloud Expo Madrid 2024 announcement was primarily an invitation to discuss open-source cloud infrastructure, hybrid and multi-cloud operations, enterprise AI and MLOps. It establishes the event logistics and Canonical’s intended agenda, but not a documented product launch or verified booth demonstration. Treat current Ubuntu Pro and service prices as separate, dated commercial context when evaluating whether Canonical fits your infrastructure and budget.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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