What is Kubeflow?
Kubeflow is an open-source platform that provides composable, Kubernetes-native tools for the entire AI lifecycle, including model training, hyperparameter tuning, pipeline orchestration, model management, and notebook environments. It enables AI teams to build scalable ML systems on any Kubernetes infrastructure.
Kubeflow pricing
We don't have Kubeflow's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What Kubeflow does
The capabilities that matter for mlops & llmops tools, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Tool role
- End-to-end ML platform
- Self-hostable / OSS core
- ✓
- Managed cloud available
- ✗
- On-prem / VPC deployment
- ✓
- LLM tracing / observability
- -
- Evaluation (offline / LLM-judge / human)
- -
- Prompt management + versioning
- -
- Experiment tracking / model registry
- ✓
- Model serving / inference endpoint
- ✓
- OpenTelemetry / OpenLLMetry compatible
- -
- Framework-agnostic
- ✓
- Multi-provider model support
- ✓
- No-train-on-customer-data guarantee
- Yes
Platform & deployment
Independently observed- CLI
- Web
- Cloud / SaaS
- On-premise
- Self-hosted
Integrations (9)
Independently observed- PyTorch
- TensorFlow
- JAX
- XGBoost
- Spark
- HuggingFace
- DeepSpeed
- Megatron
- MLX
Security & compliance
Known vulnerabilities: 0 (0 in the last 12 months) sourcea count reflects scale & disclosure, not quality
Kubeflow FAQ
Common questions about Kubeflow, answered from independent, dated evidence.
What is Kubeflow?
Kubeflow is an open-source platform that provides composable, Kubernetes-native tools for the entire AI lifecycle, including model training, hyperparameter tuning, pipeline orchestration, model management, and notebook environments. It enables AI teams to build scalable ML systems on any Kubernetes infrastructure. It is indexed under MLOps & LLMOps Tools.
Source: https://kubeflow.org
Is Kubeflow free to use?
Kubeflow is open source, so it can be self-hosted and used at no licence cost. It is released under the Apache-2.0 licence. Pricing changes often, so verify at source before relying on it.
Source: https://kubeflow.org
What platforms does Kubeflow support?
Kubeflow supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://kubeflow.org
Can Kubeflow be self-hosted?
Yes. Kubeflow can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://kubeflow.org
What does Kubeflow integrate with?
We have confirmed 9 integrations for Kubeflow, including PyTorch, TensorFlow, JAX, XGBoost, Spark, HuggingFace, DeepSpeed and Megatron, plus 1 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://kubeflow.org
Is Kubeflow open source?
Yes. Kubeflow is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.
Kubeflow alternatives
Other mlops & llmops tools we track, ranked by the same independent score.
- PortkeyAn API gateway for routing requests across thousands of language models with built-in safety guardrailshigh · 76%
- LangChainA platform for building, testing, and operating AI agents at scalemedium · 70%
- BasetenAn inference platform for deploying and running AI models at scalemedium · 73%
- Together AICloud platform for deploying and running open-source AI models with optimized inferencemedium · 61%
- OllamaA platform for running open-source language models locally or in the cloud with cost-effective access.medium · 57%
- RayDistributed computing infrastructure for scaling machine learning applicationsmedium · 65%
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Kubeflow, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 81 | 0.07 | 5.7 | ✓ |
| Release cadence | 86 | 0.05 | 4.5 | ✓ |
| Security score | 55 | 0.04 | 2.3 | ✓ |
| Stars | 79 | 0.03 | 2.1 | ✓ |
| Integrations | 26 | 0.08 | 2.0 | ✓ |
| Dependent projects | 27 | 0.06 | 1.7 | ✓ |
| Development activity | 10 | 0.09 | 0.9 | ✓ |
| Security posture | 0 | 0.06 | 0.0 | - |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 1 | mediumsource · 2026-09-10 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 6 items | mediumsource · 2026-09-10 · 66% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Role: platform · Managed cloud: No · Model serving: Yes · Self hostable: Yes · Multi provider: Yes · Vpc deployment: Yes | mediumsource · 2026-08-14 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 7 | mediumsource · 2026-08-14 · 60% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | Apache-2.0 | highsource · 2026-09-10 · 95% |
Pricing
Release
Security
Is Kubeflow the right choice for you?
Tell us the job, the constraints and what you weigh most, and we will rank Kubeflow against the rest of the mlops & llmops tools we index, using the same dated evidence weighted your way.
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Is this your product?
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