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AI · head to head

Arize AI vs Kubeflow

Arize AI logo

Arize AI

AI

AI engineering platform for observability and evaluation of agents and LLM apps

From
Free
Free plan
Yes
Full reviewWebsite
Kubeflow logo

Kubeflow

Machine Learning

Machine learning toolkit for Kubernetes

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Arize AI the free plan caps trace spans at 25,000 per month with only 15 days of retention.; Kubeflow complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
  • They diverge on capability: Arize AI covers End-to-end tracing, Kubeflow covers ML pipelines.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Arize AI and Kubeflow actually diverge.

Attributes where Arize AI and Kubeflow differ
AttributeArize AIKubeflow
Pricing modelfreemiumUnknown
Platformsweb, apiKubernetes
CategoryAIMachine Learning
FoundedUnknown2017

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Arize AI

  • End-to-end tracing
  • Evaluation framework
  • Prompt testing and improvement
  • Alyx AI engineering agent
  • Custom dashboards
  • Data warehouse integrations

Only in Kubeflow

  • ML pipelines
  • Training operators
  • Model serving
  • Jupyter notebooks
  • Hyperparameter tuning
  • Kubernetes
  • TensorFlow
  • PyTorch

What people use each for

The jobs each tool is most often brought in to do.

Arize AI

  • Tracing and debugging production AI agentsnot Kubeflow
  • Running large-scale evaluations across traces and sessionsnot Kubeflow
  • Improving prompts before production rolloutnot Kubeflow
  • Storing and querying GenAI traces alongside a data warehousenot Kubeflow

Kubeflow

  • Machine learningnot Arize AI
  • Data analysisnot Arize AI
  • Model trainingnot Arize AI
  • Predictive analyticsnot Arize AI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Arize AI

  • The free plan caps trace spans at 25,000 per month with only 15 days of retention.
  • Self-hosted deployment and Data Fabric integration are restricted to the custom-priced Enterprise tier.
  • Pricing beyond the $50/month Pro plan requires a custom quote, making cost planning less transparent at scale.
  • Advanced compliance features like HIPAA are only available on Enterprise.

Kubeflow

  • Complex installation and configuration requiring Kubernetes expertise, upgrade paths between versions need manual CRD migrations
  • Resource-intensive infrastructure with minimal installs consuming significant CPU and memory
  • Limited multi-tenancy support and multi-cloud setup leaves users largely on their own
  • No native CI/CD integration, requiring custom glue code for versioning and automated deployments
  • Debugging jobs and monitoring workloads often requires dropping down into raw Kubernetes commands

Pricing, plan by plan

Arize AI

Free
  • AX FreeFree
    • 25k trace spans/month
    • 1 GB storage/month
    • 15-day retention
  • AX Pro$50/month
    • 50k trace spans/month
    • 10 GB storage/month
    • 30-day retention
  • AX Enterprise$undefined/mo
    • Custom trace spans, storage, and retention
    • SaaS or self-hosted deployment
    • Managed agents and Data Fabric

Kubeflow

Free

No published plan breakdown. See the Kubeflow review.

Which should you pick?

Choose Arize AI if

  • You need end-to-end tracing.
  • You want to start without paying.
  • You work on web, api.
  • You also want evaluation framework.
Arize AI review

Choose Kubeflow if

  • You need ml pipelines.
  • You want to start without paying.
  • You work on Kubernetes.
  • You also want training operators.
Kubeflow review

Questions people ask

Is Arize AI or Kubeflow better?
Neither clearly leads. Arize AI starts at Free and Kubeflow at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Arize AI or Kubeflow?
Arize AI starts at Free and Kubeflow at Free.
Does Arize AI or Kubeflow run on more platforms?
Arize AI runs on web, api. Kubeflow runs on Kubernetes.
Can I use Arize AI for free?
Both have a free tier, so you can try either at no cost before committing.
What is Arize AI best used for?
Arize AI is most often used for tracing and debugging production ai agents, running large-scale evaluations across traces and sessions, improving prompts before production rollout, storing and querying genai traces alongside a data warehouse. Of those, tracing and debugging production ai agents and running large-scale evaluations across traces and sessions are not what Kubeflow is typically brought in for.
What can Arize AI do that Kubeflow cannot?
Arize AI covers End-to-end tracing, Evaluation framework, Prompt testing and improvement, Alyx AI engineering agent. Kubeflow covers ML pipelines, Training operators, Model serving, Jupyter notebooks.

Answered from the vendors’ own pages

Arize AI: What does Arize AX cost?

Arize AX offers a free plan, a Pro plan at $50/month, and a custom-priced Enterprise plan, with pricing based on trace spans, storage, and retention needs.

Source
Kubeflow: Is Kubeflow free to use?

Yes, Kubeflow is free and open-source under Apache License 2.0. However, you pay for the underlying Kubernetes infrastructure, which typically costs $500 to $5,000 per month depending on scale and cloud provider.

Source
Arize AI: Is there a free plan, and what are its limits?

The AX Free plan includes 25,000 trace spans and 1 GB of storage per month with 15-day retention, plus unlimited users, evaluations, and experiments.

Source
Kubeflow: Do I need Kubernetes expertise to use Kubeflow?

Kubeflow requires significant Kubernetes and DevOps expertise. The installation deploys dozens of services and CRDs, often requiring manual configuration and troubleshooting. Data scientists typically need to convert scripts to containerized components.

Source
Arize AI: What deployment options are available?

Free and Pro plans are SaaS-only, while Enterprise customers can choose SaaS or self-hosted deployment with custom SLAs.

Source
Kubeflow: What platforms can Kubeflow run on?

Kubeflow runs on any Kubernetes-compliant cluster, including on-premise, AWS, Azure, Google Cloud, and hybrid environments. This multi-cloud portability is one of its key advantages over managed alternatives.

Source
Kubeflow: How does Kubeflow compare to managed services like SageMaker?

Kubeflow offers multi-cloud portability and lower long-term costs but requires more operational overhead. SageMaker provides a fully managed experience with better UI and less infrastructure work, but creates vendor lock-in to AWS.

Source
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