What is MLOps?
Machine learning operations (MLOps) is like DevOps for machine learning. It is a set of practices that automates machine learning workflows, ensuring scalability, portability and reproducibility.
- 10 years of security maintenance
- Easy to deploy and integrate different tools
- Hybrid, multi-cloud experience
- Simple per node subscription
- Automated lifecycle management
with Charmed Kubeflow
Charmed Kubeflow is the foundation of Canonical MLOps. It integrates with various tools including Charmed MLFlow, Canonical Observability Stack and Charmed Spark covering all the stages of the machine learning lifecycle.
Full support for your ML stack
Canonical offers a fully supported machine learning operations solution, with guaranteed SLAs. Get the same level of support across public or private clouds.
We run the platform. Your team can focus on developing and deploying models. Streamline operational service delivery and offload the design, implementation and management of your MLOps environment.
Open source MLOps in the public cloud
Get started with machine learning in the public cloud. Use the Charmed Kubeflow appliance on AWS to experiment with MLOps quickly and scale up with Canonical's support.
Get your team up-to-date
with an MLOps workshop
Canonical offers a 5-day, on-site workshop for up to 10 participants. It includes architecture building based on your specific use case with a full MLOps architecture proposal at the end of the workshop.
Learn to take models to production using open source MLOps platforms.
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