Canonical MLOps vs Flyte
Canonical MLOps
canonical.com
Flyte
flyte.orgSide by side
| Figure | Canonical MLOps | Flyte |
|---|---|---|
| Price from | — | $950/mo |
| Free plan | — | Yes |
| Free trial | — | Yes |
| Open source | — | Yes |
| Web | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 5 |
| Spec score · MLOps Platforms | 7.6 (#11) | 9.1 (#1) |
| Deployment | Charmed MLflow can run on a workstation, CNCF-conformant Kubernetes, or a public cloud. | Flyte 2 can run locally with a devbox or on a user's cluster; the site provides `pip install flyte` and `flyte start devbox` setup commands. |
| Integrations | Canonical lists Jupyter, Grafana, and Prometheus as tools to use with Charmed MLflow. | The Flyte site lists integrations including Apache Spark, Ray, PyTorch Elastic, BigQuery, Snowflake, Weights & Biases, OpenAI Agents SDK, LangGraph, CrewAI, Pydantic AI, MLflow, Dask, and Databricks. |
| Purpose | Canonical MLOps is an open source platform for moving machine learning models from experimentation to production across the ML lifecycle. | Flyte 2 is a durable AI runtime for workloads involving training, serving, and agents. |
| Security | Canonical says its MLOps components receive up to 15 years of security maintenance, regular updates, and CVE fixes. | Union.ai states that its data plane runs inside the customer's cloud and that workflow inputs, outputs, logs, code, and reports do not pass through its control plane. |
| Support | Optional 24/7 support with SLAs is available for Canonical’s MLOps stack. | The Team plan lists one business day Sev 1 support, while Enterprise lists custom white-glove support. |
Plans
Flyte
- Flyte OSSFree
- Flyte OSSFree
- Team$950 a month
- Union.ai Team (enterprise Flyte platform)$950 a month
- EnterprisePriced on request
In their own words
Canonical MLOps
Canonical MLOps has no write-up on Specifiction yet; its figures are above.
Flyte
Flyte 2 is a durable runtime for AI workloads involving training, serving and agents. Users write workflows as plain Python async functions and use a TaskEnvironment to declare images, resources, secrets and retry policies. Flyte resumes from failed tasks and can recover from out-of-memory kills, preempted nodes and disappearing GPUs. Branches, loops and runtime decisions support dynamic workflows and agents. Native serving integrations include Streamlit, FastAPI, vLLM, SGLang and Ollama, with replicas able to scale to zero when idle. Listed integrations also cover Apache Spark, Ray, PyTorch Elastic, BigQuery, Snowflake, Weights & Biases, OpenAI Agents SDK, LangGraph, CrewAI, Pydantic AI, MLflow, Dask and Databricks. It runs locally with a devbox or on a customer cluster. Union.ai says customer-cloud data planes keep workflow inputs, outputs, logs, code and reports outside its control plane. Flyte is available as free Apache 2.0 open-source software.