Originally reported by Container Journal.
What Canonical Is Offering
Canonical has made ten complementary databases and tools available as fully managed services for organizations running Kubernetes clusters. The goal is to let engineering teams focus on application development rather than infrastructure operations, while Canonical handles ongoing management, patching, and updates on their behalf.
Managed Databases
- MySQL – widely used relational database
- PostgreSQL – open-source relational database known for standards compliance
- MongoDB – document-oriented NoSQL database
- InfluxDB – time-series database popular in metrics pipelines
- Elasticsearch – distributed search and analytics engine
Managed Middleware and Monitoring Tools
- Apache Kafka – open-source event streaming platform
- Open Source Mano (OSM) – ETSI-backed platform for managing Network Functions Virtualization (NFV) software
- Prometheus – metrics collection and alerting toolkit
- Grafana – visualization and dashboarding layer for metrics
- Graylog – centralized log management platform
Deployment Flexibility
According to Nilay Patel, a product manager at Canonical, each managed service can be deployed on a public cloud, a private cloud, virtual machines, or bare-metal servers. This mirrors the deployment flexibility already offered by Canonical’s managed Kubernetes service. Every service is covered by defined Service Level Agreements (SLAs), and customers can monitor compliance through Canonical-provided dashboards.
Why This Matters for DevOps Teams
Modern microservices architectures running on Kubernetes often require a broad stack of supporting services—message queues, databases, observability tools—each with its own upgrade cadence and operational requirements. Managing that full stack internally demands deep specialization across multiple technologies simultaneously.
By bundling these components as integrated managed services, Canonical is addressing a real operational pain point: the rate of change in cloud-native tooling outpaces the capacity of many internal teams to keep up. Offloading routine operations—upgrades, security patches, availability monitoring—allows engineering organizations to allocate more time to building features and delivering business value.
The Broader Context: Managed Services and Kubernetes Skills Scarcity
Kubernetes expertise remains scarce in the job market. Even as IT workforce dynamics shift, engineers with the skills needed to operate, secure, and troubleshoot a production Kubernetes environment are in high demand. This skills gap is one of the primary drivers behind increased adoption of managed Kubernetes offerings from cloud providers and independent vendors alike.
Historically, managed services have represented a minority share of overall IT infrastructure consumption. However, as infrastructure complexity grows—particularly with the rise of edge computing scenarios where Kubernetes clusters may be deployed across many distributed locations—the operational burden on internal teams increases proportionally. Canonical’s pitch is that its managed services extend beyond any single public cloud platform, offering a consistent operational model across hybrid and multi-cloud environments.
Considerations Before Adopting Managed Services
Before migrating critical databases or observability pipelines to a managed service, engineering teams should evaluate the following:
- SLA terms and remediation windows – Understand exactly what uptime guarantees cover and what happens during an incident.
- Data residency and compliance – Confirm that managed service deployments meet your regulatory requirements (GDPR, HIPAA, etc.).
- Version control and upgrade scheduling – Clarify how much control you retain over when major version upgrades occur.
- Egress and lock-in risk – Assess the cost and complexity of migrating away from the managed service if requirements change.
- Integration with existing CI/CD pipelines – Verify that managed databases and tools can be provisioned and configured through infrastructure-as-code tooling your team already uses.
Summary
Canonical’s expanded managed services portfolio targets the operational complexity that accompanies mature Kubernetes deployments. By taking responsibility for ten commonly used databases and tools, Canonical aims to give organizations a practical path to reducing internal operational burden without sacrificing the flexibility to run workloads on the infrastructure of their choice. Whether this model fits a given organization depends on its appetite for outsourcing operational control and its ability to meet compliance and integration requirements through a third-party managed offering.