# Table of Contents
- [Documentation | Kubeflow](#documentation-kubeflow)
- [Kubeflow](#kubeflow)
- [Future Events | Kubeflow](#future-events-kubeflow)
- [Google Summer of Code 2025 | Kubeflow](#google-summer-of-code-2025-kubeflow)
- [Past Events | Kubeflow](#past-events-kubeflow)
- [2023 | Kubeflow](#2023-kubeflow)
- [Kubeflow Summit 2023 | Kubeflow](#kubeflow-summit-2023-kubeflow)
- [2024 | Kubeflow](#2024-kubeflow)
- [Google Summer of Code 2024 | Kubeflow](#google-summer-of-code-2024-kubeflow)
- [2025 | Kubeflow](#2025-kubeflow)
---
# Documentation | Kubeflow
Documentation
=============
All of Kubeflow documentation
* * *
##### [GenAI](https://www.kubeflow.org/docs/genai/)
GenAI with Kubeflow
##### [Getting Started](https://www.kubeflow.org/docs/started/)
How to get started with Kubeflow
##### [Kubeflow Projects](https://www.kubeflow.org/docs/components/)
Logical projects that make up Kubeflow
##### [Kubeflow AI Reference Platform](https://www.kubeflow.org/docs/kubeflow-platform/)
Information about Kubeflow AI reference platform and distributions
##### [Kubeflow Community](https://www.kubeflow.org/docs/about/)
About Kubeflow and its community
##### [External Add-Ons](https://www.kubeflow.org/docs/external-add-ons/)
Externally developed projects that integrate with Kubeflow
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+docs/_index.md)
so we can improve.
Last modified April 21, 2020: [Restructured the website repo to allow for future i18n and content translation (#1909) (d0bd0e0)](https://github.com/kubeflow/website/commit/d0bd0e031453d12e704d0636f9ad192c866a327c)
---
# Kubeflow
Kubeflow
========
The foundation of tools for AI Platforms on Kubernetes.
[Get Started](https://www.kubeflow.org/docs/started/)
[Contribute](https://www.kubeflow.org/docs/about/contributing/)
[GenAI](https://www.kubeflow.org/docs/genai/use-cases/)
[](https://www.kubeflow.org/#overview)
### What is Kubeflow?
Kubeflow is the foundation of tools for AI Platforms on Kubernetes.
AI platform teams can build on top of Kubeflow by using each project independently or deploying the entire AI reference platform to meet their specific needs. The Kubeflow AI reference platform is composable, modular, portable, and scalable, backed by an _ecosystem_ of Kubernetes-native [projects](https://www.kubeflow.org/docs/started/architecture/#kubeflow-ecosystem)
for each stage of [the AI lifecycle](https://www.kubeflow.org/docs/started/architecture/#kubeflow-projects-in-the-ai-lifecycle)
.
[Deploy Kubeflow](https://www.kubeflow.org/docs/started/installing-kubeflow/)
anywhere you run [Kubernetes.](https://kubernetes.io/)
### Trusted by
 
 
 
 
[see more adopters on](https://github.com/kubeflow/community/blob/master/ADOPTERS.md)
### Kubeflow Projects
[](https://www.kubeflow.org/docs/components/spark-operator/overview/)
Kubeflow Spark Operator
[Kubeflow Spark Operator](https://www.kubeflow.org/docs/components/spark-operator/overview/)
aims to make specifying and running Spark applications as easy and idiomatic as running other workloads on Kubernetes.
[](https://www.kubeflow.org/docs/components/notebooks/overview/)
Kubeflow Notebooks
[Kubeflow Notebooks](https://www.kubeflow.org/docs/components/notebooks/overview/)
lets you run web-based development environments on your Kubernetes cluster by running them inside Pods.
[](https://www.kubeflow.org/docs/components/trainer/overview/)
Kubeflow Trainer
[Kubeflow Trainer](https://www.kubeflow.org/docs/components/trainer/overview/)
is a Kubernetes-native project for LLMs fine-tuning and enabling scalable, distributed training across a wide range of AI frameworks, including PyTorch, HuggingFace, DeepSpeed, MLX, JAX, XGBoost, and others.
[](https://www.kubeflow.org/docs/components/katib/overview/)
Kubeflow Katib
[Kubeflow Katib](https://www.kubeflow.org/docs/components/katib/overview/)
is a Kubernetes-native project for automated machine learning (AutoML) with support for hyperparameter tuning, early stopping and neural architecture search.
[](https://kserve.github.io/website/)
Kubeflow KServe
[KServe](https://www.kubeflow.org/docs/components/kserve/introduction/)
is a standardized distributed generative and predictive AI inference platform for scalable, multi-framework deployment on Kubernetes.
[](https://www.kubeflow.org/docs/components/model-registry/overview/)
Kubeflow Model Registry
[Kubeflow Model Registry](https://www.kubeflow.org/docs/components/model-registry/overview/)
is a cloud-native component that provides a single pane of glass for ML model developers to index and manage models, versions, and ML artifacts metadata. It fills a gap between model experimentation and production activities.
[](https://www.kubeflow.org/docs/components/pipelines/overview/)
Kubeflow Pipelines
[Kubeflow Pipelines](https://www.kubeflow.org/docs/components/pipelines/overview/)
(KFP) is a platform for building then deploying portable and scalable machine learning workflows using Kubernetes.
[](https://www.kubeflow.org/docs/components/central-dash/overview/)
Kubeflow Dashboard
[Kubeflow Central Dashboard](https://www.kubeflow.org/docs/components/central-dash/overview/)
is our hub which connects the authenticated web interfaces of Kubeflow and other ecosystem components.
### Join our Community
We are an open and welcoming [community](https://www.kubeflow.org/docs/about/community/)
of software developers, data scientists, and organizations! Check out the [weekly community calls](https://www.kubeflow.org/docs/about/community/#list-of-available-meetings)
, get involved in discussions on the [mailing list](https://www.kubeflow.org/docs/about/community/#kubeflow-mailing-list)
or chat with others on the [Slack Workspace](https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels)
!
 
We are a Cloud Native Computing Foundation project.
---
# Future Events | Kubeflow
Future Events
=============
Future Kubeflow events
* * *
##### [Google Summer of Code 2025](https://www.kubeflow.org/events/gsoc-2025/)
Google Summer of Code 2025
##### [Kubeflow Summit North America (co-located event at KubeCon NA 2025)](https://events.linuxfoundation.org/kubecon-cloudnativecon-north-america/co-located-events/kubeflow-summit/)
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/upcoming-events/_index.md)
so we can improve.
Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# Google Summer of Code 2025 | Kubeflow
Google Summer of Code 2025
==========================
Google Summer of Code 2025
* * *
The Kubeflow Community plans to participate in [**Google Summer of Code 2025**](https://summerofcode.withgoogle.com/)
. This page aims to help you participate in GSoC 2025 with Kubeflow.
#### Note
While Kubeflow participated in [GSoC 2024](https://www.kubeflow.org/events/gsoc-2024/)
, we are currently awaiting final confirmation of our participation in GSoC 2025. Google will announce the final list of accepted organizations on **February 27, 2025**.
What is GSoC?
-------------
Google Summer of Code (GSoC) is a global program that offers students [stipends](https://developers.google.com/open-source/gsoc/help/student-stipends)
for working on open-source projects during the summer.
For more information, see the [GSoC FAQ](https://developers.google.com/open-source/gsoc/faq)
and watch the video below:
How can I participate?
----------------------
Thank you for your interest in participating in GSoC with Kubeflow!
Please carefully read the following information to learn how to participate in GSoC with Kubeflow.
### Key Dates
Here are the key dates for GSoC 2025, the [full timeline](https://developers.google.com/open-source/gsoc/timeline)
is available on the GSoC website:
| Event | Date |
| --- | --- |
| **Applications Open** | March 24 @ 18:00 UTC |
| **Applications Deadline** | April 8 @ 18:00 UTC |
| **Accepted Proposals Announced** | May 8 |
| **Community Bonding** | May 8 - June 1 |
| **Coding Begins** | June 2 |
| **Midterm Evaluations** | July 14 - 18 |
| **Coding Ends** | September 1 |
| **Final Evaluations** | September 1 - 8 |
### Eligibility
To participate in GSoC with Kubeflow, you **must** meet the GSoC [eligibility requirements](https://developers.google.com/open-source/gsoc/faq#what_are_the_eligibility_requirements_for_participation)
:
* Be at least 18 years old at time of registration.
* Be a student or an [open source beginner](https://developers.google.com/open-source/gsoc/faq#how_do_i_know_if_i_am_considered_a_beginner_in_open_source_development)
.
* Be eligible to work in their country of residence during duration of program.
* Be a resident of a country not currently embargoed by the United States.
### Steps
1. Sign up as a student on the [GSoC website](https://summerofcode.withgoogle.com/)
.
2. Join the [Kubeflow Slack](https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels)
:
* **NOTE:** please **do not** reach out privately to mentors, instead, start a thread in the [`#kubeflow-contributors`](https://cloud-native.slack.com/archives/C0742LBR5BM)
channel so others can see the response.
3. Learn about Kubeflow:
* Read the [Introduction to Kubeflow](https://www.kubeflow.org/docs/started/introduction/)
* Review the [Architecture Overview](https://www.kubeflow.org/docs/started/architecture/)
* Consider [trying out Kubeflow](https://www.kubeflow.org/docs/started/installing-kubeflow/)
(not required, can be challenging)
4. Review the [project ideas](https://www.kubeflow.org/events/gsoc-2025/#project-ideas)
to decide which ones you are interested in:
* You may wish to attend the next [community meeting](https://www.kubeflow.org/docs/about/community/#kubeflow-community-calendar)
for the group that is leading your chosen project.
* **NOTE:** while we recommend you submit a proposal based on the project ideas, you can also submit a proposal with your own idea.
5. Submit a proposal through the [GSoC website](https://summerofcode.withgoogle.com/)
between **March 24th** and **April 8th**:
* Please see [these guidelines](https://google.github.io/gsocguides/student/writing-a-proposal)
on how to write a good proposal.
* Kubeflow requests that you use [this template](https://github.com/kubeflow/community/tree/master/proposals/gsoc)
for your proposal.
* You will need to submit PDF version of your proposal on GSoC website before April 8th, 2025.
6. Wait for the results to be announced on **May 8th**.
Project Ideas
-------------
### Project 1: Kubeflow Platform Enhancements
**Components:** Kubeflow Manifests, Kubeflow Dashboard, Kubeflow Notebooks, Kubeflow Pipelines
**Mentors:** [`@juliusvonkohout`](https://github.com/juliusvonkohout)
, [`@thesuperzapper`](https://github.com/thesuperzapper)
**Contributor:** [`@akagami-harsh`](https://github.com/akagami-harsh)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/PWDq4Zvt)
[PR](https://github.com/kubeflow/pipelines/pull/11965)
**Difficulty:** Hard
**Size:** 350 hours
**Possible Projects:**
* Pipelines: productionize the [SeaweedFS PoC](https://github.com/kubeflow/manifests/tree/master/experimental/seaweedfs)
as secure minio replacement
* Pipelines: isolate artifacts per namespace/profile/user using only one bucket ([`kubeflow/pipelines#4649`](https://github.com/kubeflow/pipelines/issues/4649)
)
* Notebooks/Dashboard: migrate code to kubeflow/dashboard and kubeflow/notebooks ([`kubeflow/kubeflow#7549`](https://github.com/kubeflow/kubeflow/issues/7549)
)
* Dashboard: work on the Central Dashboard angular rewrite ([`kubeflow/dashboard#38`](https://github.com/kubeflow/dashboard/issues/38)
)
* Dashboard: support using groups for auth ([`kubeflow/manifests#2910`](https://github.com/kubeflow/manifests/issues/2910#issuecomment-2468745862)
)
* Manifests: improve scripts and CI/CD in kubeflow/manifests, including matrix calls to test multiple Kubernetes versions simultaneously
**Skills Required/Preferred:**
* GitHub and GitHub Actions
* containers and Kubernetes knowledge
* Experience with Python, Go and JavaScript frameworks
* * *
### Project 2: Kserve Models Web App
**Components:** KServe
**Mentors:** [`@juliusvonkohout`](https://github.com/juliusvonkohout)
, [`@Griffin-Sullivan`](https://github.com/Griffin-Sullivan)
**Contributor:** [`@LogicalGuy77`](https://github.com/LogicalGuy77)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/K9iend9b)
, [Commits](https://github.com/kserve/models-web-app/commits?author=LogicalGuy77)
**Difficulty:** Medium
**Size:** 175 hours
**Goals:**
* Reviving and updating the [`kserve/kserve-models-web`](https://github.com/kserve/models-web-app)
application.
* Clean up and merge the open issues and PRs
* Implement a better CI/CD pipeline.
* Potentially migrate the application to `kubeflow/kserve-model-ui`
* Add features for editing, regression testing, and monitoring/metrics support.
* Synchronize with kserve 0.14+ changes.
**Skills Required/Preferred:**
* GitHub Actions
* containers and Kubernetes knowledge
* JavaScript frameworks
* * *
### Project 3: Istio CNI and Ambient Mesh
**Components:** Kubeflow Manifests
**Mentors:** [`@juliusvonkohout`](https://github.com/juliusvonkohout)
, [`@kimwnasptd`](https://github.com/kimwnasptd)
**Contributor:** [`@madmecodes`](https://github.com/madmecodes)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/WAHCCi8V)
, [PR](https://github.com/kubeflow/manifests/pull/3153)
**Difficulty:** Medium
**Size:** 175 hours
**Goals:**
* Secure our service mesh with istio-cni by default ([`kubeflow/manifests#2907`](https://github.com/kubeflow/manifests/pull/2907)
)
* Provide an out-of-box option for istio-ambient mesh ([`kubeflow/manifests#2676`](https://github.com/kubeflow/manifests/issues/2676)
)
* Controllers to create HTTPRoute and AuthorizationPolicies, that align with way-point proxies
* Manifests to also have a flavour of HTTPRoute and updated AuthorizationPolicies
* Secure Kserve by default ([`kubeflow/manifests#2811`](https://github.com/kubeflow/manifests/issues/2811)
)
* Rootless Kubeflow ([`kubeflow/manifests#2528`](https://github.com/kubeflow/manifests/issues/2528)
)
**Skills Required/Preferred:**
* GitHub and GitHub Actions
* Kubernetes and networking
* Istio, Kustomize
* * *
* * *
### Project 4: Deploying Kubeflow with Helm
**Components:** Kubeflow Manifests, Kubeflow Pipelines, Kubeflow Trainer, Kubeflow Katib, Kubeflow Spark Operator, Kubeflow Model Registry
**Mentors:** [`@chasecadet`](https://github.com/chasecadet)
, [`@varodrig`](https://github.com/varodrig)
, [`@juliusvonkohout`](https://github.com/juliusvonkohout)
**Contributor:** [`@kunal-511`](https://github.com/kunal-511)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/azZltU0y)
, [KEP](https://github.com/kubeflow/community/pull/832)
, [PR](https://github.com/kubeflow/katib/pull/2553)
**Difficulty:** Medium
**Size:** 350 hours
**Goals:**
* To extend our userbase and satisfy the requirement for a helm chart that many users and companies have voiced, a community-driven Helm chart is being developed for Kubeflow v1.10.x.
* Work with Kubeflow components maintainers and kubeflow/manifests to support the creation of Helm charts for a full Kubeflow deployment with similar functionality as the current kustomize manifests for the Kubeflow 1.10.x release.
* Investigate possible systems to automatically generate or maintain charts based on the existing kustomize manifests, such that we have a single source of truth.
**Skills Required/Preferred:**
* Container and Kubernetes knowledge
* Helm (especially templating and chart creation)
* Kustomize (not strictly required, but a plus)
* * *
* * *
### Project 5: JupyterLab Plugin for Kubeflow
**Components:** Kubeflow Notebooks, Kubeflow Pipelines
**Mentors:** [`@ederign`](https://github.com/ederign)
, [`@StefanoFioravanzo`](https://github.com/StefanoFioravanzo)
**Contributor:** [`@Amrit27k`](https://github.com/Amrit27k)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/vtdQwx7U)
[PR](https://github.com/kubeflow-kale/kale/pull/447)
**Difficulty:** Medium
**Size:** 350 hours
**Goals:**
* Work with the new IDE Working Group (name pending - [`kubeflow/community#808`](https://github.com/kubeflow/community/issues/808)
) to create a JupyterLab plugin for Kubeflow
* Modernizing and/or consolidating [Elyra](https://github.com/elyra-ai/elyra)
, [Kale](https://github.com/kubeflow-kale/kale)
, and [Jupyter Scheduler](https://github.com/jupyter-server/jupyter-scheduler)
into a single plugin for Kubeflow
* Eventually, the plugin will likely integrate with:
* Kubeflow Pipelines (priority)
* Kubeflow Notebooks
* Kubeflow Model Registry
* Kubeflow Training Operator
* and more
**Skills Required/Preferred:**
* Python for backend development and API integration
* JavaScript/TypeScript for frontend development
* Modern UI frameworks (e.g., React, Jupyter widgets) is a plus
* Familiarity with Jupyter Notebook, JupyterLab
* Jupyter extension development experience is a plus
* * *
### Project 6: Batch Processing Gateway Integration
**Components:** Kubeflow Spark Operator
**Mentors:** [`@Shekharrajak`](https://github.com/Shekharrajak)
, [`@lresende`](https://github.com/lresende)
, [`@yuchaoran2011`](https://github.com/yuchaoran2011)
, [`@andreyvelich`](https://github.com/andreyvelich)
**Contributor:** [`@fresende`](https://github.com/fresende)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/zRPtxGBI)
, [Issue](https://github.com/kubeflow/spark-operator/issues/2422)
**Difficulty:** Hard
**Size:** 350 hours
**Goals:**
* Integrating the [Batch Processing Gateway (BPG)](https://github.com/apple/batch-processing-gateway)
with Kubeflow for submitting, monitoring, and managing Spark applications across multiple clusters ([`kubeflow/spark-operator#2422`](https://github.com/kubeflow/spark-operator/issues/2422)
)
* Analyse, Design, Plan, and Execute Spark Job Execution Strategies:
* Evaluate the trade-offs between running a Spark kernel directly within a Kubeflow Notebook versus leveraging the Batch Processing Gateway for job submission.
* Assess the cloud-native design of Kubeflow SDK and Notebook environments to determine the optimal approach for Spark integration that maximizes efficiency, scalability, and usability.
* Make a well-informed decision on whether to support Spark kernels within notebooks, use BPG, or implement a hybrid approach for an enhanced user experience.
* Automated Job Routing and Scalable Execution:
* Implement dynamic workload routing using BPG to automatically distribute Spark jobs based on cluster load, resource availability, and workload priority.
* Integrate with the Spark Operator to optimize resource allocation, minimize execution delays, and ensure efficient scaling for petabyte-scale machine learning and data processing workloads.
* Enhanced User API and Notebook Integration:
* Develop a Python SDK for Kubeflow notebooks, enabling users to submit, manage, and monitor Spark jobs via BPG REST APIs for a lightweight, scalable solution.
* Ensure a seamless user experience by providing intuitive APIs that abstract complex job management operations, making it easier for data scientists and ML engineers to experiment and iterate on workflows within
* Comprehensive Debugging and Performance Monitoring:
* Enable full debugging capabilities by integrating Spark UI, logging, and monitoring tools into Kubeflow, allowing users to visualize Spark DAGs, tasks, and execution stages.
* Implement centralized logging and Prometheus-based monitoring to provide real-time insights into Spark job performance across clusters.
* Ensure users can efficiently analyze job execution, detect bottlenecks, and optimize data processing and ML workflows within Kubeflow.
* Note: Most of the logging APIs must be leveraged out of the box from either BPG or Spark - but we need to document, showcase examples to user.
* Comprehensive documentation and user guides to assist users in leveraging the new features effectively.
**Skills Required/Preferred:**
* Proficiency in Python, Java and familiarity with developing SDKs.
* Experience with Kubernetes and managing containerized applications.
* Understanding of Apache Spark and its deployment on Kubernetes clusters.
* Familiarity with RESTful API development and integration.
* Experience with monitoring tools and logging frameworks is a plus.
* * *
* * *
### Project 7: GPU Testing for LLM Blueprints
**Components:** Kubeflow Trainer (Training Operator)
**Mentors:** [`@andreyvelich`](https://github.com/andreyvelich)
, [`@varodrig`](https://github.com/varodrig)
**Contributor:** [`@jaiakash`](https://github.com/jaiakash)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/fwZkvPr0)
, [KEP](https://github.com/kubeflow/trainer/pull/2689)
**Difficulty:** Medium
**Size:** 350 hours
**Goals:**
* Explore using Self-Hosted Runners for GPU testing in Kubeflow Trainer ([`kubeflow/trainer#2432`](https://github.com/kubeflow/trainer/issues/2432)
)
**Skills Required/Preferred:**
* GitHub Actions
* Kubernetes
* PyTorch
* Python
* * *
* * *
### Project 8: Support JAX and TensorFlow Training Runtimes
**Components:** Kubeflow Trainer (Training Operator)
**Mentors:** [`@Electronic-Waste`](https://github.com/Electronic-Waste)
, [`@XshubhamX`](https://github.com/XshubhamX)
, [`@andreyvelich`](https://github.com/andreyvelich)
**Contributor:** [`@mahdikhashan`](https://github.com/mahdikhashan)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/50KbkoaM)
, [Issue](https://github.com/kubeflow/trainer/issues/2673)
**Difficulty:** Hard
**Size:** 350 hours
**Goals:**
* Add support TensorFlow as a training runtime in Kubeflow Trainer ([`kubeflow/trainer#2443`](https://github.com/kubeflow/trainer/issues/2443)
)
* Add support JAX as a training runtime in Kubeflow Trainer ([`kubeflow/trainer#2442`](https://github.com/kubeflow/trainer/issues/2442)
)
**Skills Required/Preferred:**
* Go
* Kubernetes
* JAX
* TensorFlow
* * *
* * *
### Project 9: Export Kubeflow Trainer Models to Kubeflow Model Registry
**Components:** Kubeflow Trainer (Training Operator), Kubeflow Model Registry
**Mentors:** [`@tarilabs`](https://github.com/tarilabs)
, [`@franciscojavierarceo`](https://github.com/franciscojavierarceo)
**Details:** Not Accepted for GSoC 2025, open for contributions
**Difficulty:** Hard
**Size:** 350 hours
**Goals:**
* Integrate Kubeflow Trainer with Kubeflow Model Registry ([`kubeflow/trainer#2438`](https://github.com/kubeflow/trainer/issues/2438)
)
* Trainer has implemented initializers for model and dataset, and will support model exporter in the future.
* By supporting the model registry as one of the destinations of the exporter, Trainer will integrate with Kubeflow ecosystem more deeply.
**Skills Required/Preferred:**
* Kubernetes
* Go
* YAML
* Python
* * *
### Project 10: Support Volcano Scheduler in Kubeflow Trainer
**Components:** Kubeflow Trainer (Training Operator)
**Mentors:** [`@Electronic-Waste`](https://github.com/Electronic-Waste)
, [`@rudeigerc`](https://github.com/rudeigerc)
**Contributor:** [`@Doris-xm`](https://github.com/Doris-xm)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/ZWbY1Rfj)
, [KEP](https://github.com/kubeflow/trainer/pull/2672)
**Difficulty:** Hard
**Size:** 350 hours
**Goals:**
* Integrate Volcano Scheduler with Kubeflow Trainer ([`kubeflow/trainer#2437`](https://github.com/kubeflow/trainer/issues/2437)
)
* Currently, Trainer does not support Volcano for scheduling.
* Since Volcano is a widely adopted scheduler for AI workloads, it could provide Trainer with more AI-specific scheduling capabilities if we integrate Volcano into Trainer
**Skills Required/Preferred:**
* Kubernetes
* Go
* Volcano
* * *
* * *
### Project 11: Support Postgres for Kubeflow Pipelines backend
**Components:** Kubeflow Pipelines
**Mentors:** [`@rimolive`](https://github.com/rimolive)
, [`@shivaylamba`](https://github.com/shivaylamba)
**Contributor:** [`@kaikaila`](https://github.com/kaikaila)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/fw66akzN)
, [Tracking KEP](https://github.com/kubeflow/pipelines/issues/9813)
**Difficulty:** Medium
**Size:** 175 hours
**Goals:**
* Implement support for PostgreSQL as an alternative to MySQL/MariaDB in Kubeflow Pipelines ([`kubeflow/pipelines#9813`](https://github.com/kubeflow/pipelines/issues/9813)
)
* Kubeflow Pipelines must store information about pipelines, experiments, runs, and artifacts in a database. Currently, the only database it supports is MySQL/MariaDB.
* We plan to support PostgreSQL as an alternative to MySQL/MariaDB so users will be able to reuse existing databases, and PostgreSQL will be a good use case for supporting multiple databases.
**Skills Required/Preferred:**
* Kubernetes
* Python
* Go
* YAML
### Project 12: Empowering Kubeflow Documentation with LLMs
**Components:** Kubeflow Website
**Mentors:** [`@franciscojavierarceo`](https://github.com/franciscojavierarceo)
, [`@chasecadet`](https://github.com/chasecadet)
, [`@shravan-achar`](https://github.com/shravan-achar)
, [`@Shekharrajak`](https://github.com/Shekharrajak)
**Contributor:** [`@SanthoshToorpu`](https://github.com/SanthoshToorpu)
**Details:** [GSoC page](https://summerofcode.withgoogle.com/programs/2025/projects/a9JPxfEh)
, [KEP](https://github.com/kubeflow/community/pull/869)
**Difficulty:** Hard
**Size:** 350 hours
**Goals:**
* Leverage LLMs to improve Kubeflow documentation: ([`kubeflow/website#4025`](https://github.com/kubeflow/website/issues/4025)
).
* Explore how other OSS communities leverage LLMs with the user documentation.
* Explore possibilities to use LLMs to improve existing Kubeflow documentation or use LLMs to help with user questions.
**Skills Required/Preferred:**
* JavaScript
* Python
* HTML
* Netlify
* Hugo
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/upcoming-events/gsoc-2025.md)
so we can improve.
Last modified August 20, 2025: [website: added gsoc 25 project details (#4163) (5959384)](https://github.com/kubeflow/website/commit/59593840db32f4c0e1573662b785810c126d2379)
---
# Past Events | Kubeflow
Past Events
===========
Past Kubeflow events
* * *
##### [2023](https://www.kubeflow.org/events/past-events/2023/)
Events from 2023
##### [2024](https://www.kubeflow.org/events/past-events/2024/)
Events from 2024
##### [2025](https://www.kubeflow.org/events/past-events/2025/)
Events from 2025
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/_index.md)
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Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# 2023 | Kubeflow
2023
====
Events from 2023
* * *
##### [Kubeflow Summit 2023](https://www.kubeflow.org/events/kubeflow-summit-2023/)
October 6th, 2023 - Irving, TX, USA - Virtual Attendance Available
##### [Watch: Kubeflow Summit 2023](https://www.youtube.com/playlist?list=PL2gwy7BdKoGdrkYIWGeAdKi9ntfxq8FYt)
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/2023/_index.md)
so we can improve.
Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# Kubeflow Summit 2023 | Kubeflow
Kubeflow Summit 2023
====================
October 6th, 2023 - Irving, TX, USA - Virtual Attendance Available
* * *
About the Event
---------------
The **Kubeflow Summit 2023** will be held in on **6 October** at the **Irving Convention Center in Irving Texas**.
Join us for the Kubeflow Summit 2023, an exciting event dedicated to all things Kubeflow! This year, we are thrilled to offer an in-person experience that will bring together experts, enthusiasts, and beginners alike. Don’t miss out on this incredible opportunity to expand your knowledge and network with the Kubeflow community.
Register now and secure your spot at the Kubeflow Summit 2023!
Event Details
-------------
| | |
| --- | --- |
| Date | October 6th, 2023 |
| Time | 7:30 AM - 5:30 PM CDT |
| Location | [Irving Convention Center at Las Colinas, Irving, TX, USA](https://maps.app.goo.gl/Xnf4Y1ffVLRiPNGR9) |
| Cost | **FREE**, but registration is required. |
| Registration | [Register to Attend
(VIRTUAL)](https://www.eventbrite.com/e/kubeflow-summit-2023-virtual-registration-tickets-726298186427)
[Register to Attend
(IN-PERSON)](https://www.eventbrite.com/e/kubeflow-summit-2023-in-person-registration-tickets-726236511957) |
Registration
------------
The 2023 Kubeflow Summit event is **FREE** to attend, but registration is required.
This year you may attend either _in-person_ or _virtually_:
* [**REGISTER HERE - Attend IN-PERSON**](https://www.eventbrite.com/e/kubeflow-summit-2023-in-person-registration-tickets-726236511957)
* [**REGISTER HERE - Attend VIRTUALLY**](https://www.eventbrite.com/e/kubeflow-summit-2023-virtual-registration-tickets-726298186427)
If you register to attend virtually, you will be sent more information a few days before the event on how access the talks and participate in the conversation.
Speakers
--------
We are excited to announce the following speakers will be presenting at the Kubeflow Summit 2023:
##### Josh Bottom
###### Kubeflow Steering Committee
##### Oswaldo Gomez
###### Roche
##### Omri Shiv
###### Roblox
##### Krzysztof Romanowski
###### Roche
##### Vaibhav Jain
###### Red Hat
##### Amber Graner
###### Kubeflow Community Manager
##### Mathew Wicks
###### Kubeflow Community Manager & Notebooks Lead
##### Diana Atanasova
###### Kubeflow Security Team
##### Julius von Kohout
###### Kubeflow Security Team
##### Johnu George
###### Kubeflow Training Lead
##### Andrey Velichkevich
###### Kubeflow AutoML Lead
##### James Lui
###### Kubeflow Pipelines Lead
##### Kimonas Sotirchos
###### Kubeflow Notebooks & Manifests Lead
##### Dan Sun
###### KServe Lead
##### Jooho Lee
###### Red Hat
##### Qi Liu
###### VMWare
##### Michal Hucko
###### Canonical
##### Vendant Mahabaleshwarkar
###### Open Data Hub
##### Tommy Li
###### IBM
##### Ajay Tyagi
###### DKube
##### Ricardo Rocha
###### CERN
##### Roy Budhaditya
###### Deloitte
##### Prerit Shah
###### Equinor
Agenda
------
Get ready to dive into the world of Kubeflow, the open-source machine learning platform built on Kubernetes. Our summit will feature engaging sessions, hands-on workshops, and networking opportunities to connect with like-minded individuals.
Discover the latest advancements in Kubeflow, learn from industry leaders, and gain insights into real-world use cases. Whether you’re a developer, data scientist, or IT professional, this event is designed to inspire and empower you.
| Start Time | End Time | Speaker | Session |
| --- | --- | --- | --- |
| 7:30 AM | 8:15 AM | \- | Registration Open |
| 8:15 AM | 8:25 AM | Josh Bottom | Welcome & Opening Remarks |
| 8:25 AM | 8:30 AM | Ricardo Rocha | USER STORY: Kubeflow at CERN |
| 8:30 AM | 9:00 AM | Oswaldo Gomez | Simplifying Machine Learning deployments through Cloud Native Buildpacks and KServe |
| 9:00 AM | 9:30 AM | Omri Shiv | The Journey to Supporting 60 Million DAUs starts by supporting 200 |
| 9:30 AM | 9:45 AM | Krzysztof Romanowski | Integrating oauth2-proxy into Istio Service Mesh for Seamless Authentication in Kubeflow |
| 9:45 AM | 9:50 AM | Roy Budhaditya | USER STORY: Kubeflow at Deloitte |
| 9:55 AM | 10:00 AM | Prerit Shah | USER STORY: Kubeflow at Equinor |
| \- | \- | \- | \- |
| 10:00 AM | 10:15 AM | \- | Break |
| \- | \- | \- | \- |
| 10:15 AM | 10:35 PM | Diana Atanasova & Julius von Kohout | Kubeflow Security Team Update |
| 10:35 AM | 10:55 AM | Johnu George | WG Update: Training |
| 10:55 AM | 11:15 AM | Andrey Velichkevich | WG Update: AutoML |
| 11:15 AM | 11:35 AM | James Lui | WG Update: Pipelines |
| 11:35 AM | 11:55 AM | Kimonas Sotirchos | WG Update: Notebooks & Manifests |
| 11:55 AM | 12:15 PM | Dan Sun | KServe Update |
| \- | \- | \- | \- |
| 12:15 PM | 1:30 PM | \- | Lunch |
| \- | \- | \- | \- |
| 1:30 PM | 1:40 PM | \- | Ignite Style Lightning Talks (5 minutes each) |
| 1:40 PM | 1:45 PM | Josh Bottom | Kubeflow Steering Committee Update |
| 1:45 PM | 2:00 PM | Mathew Wicks | deployKF: A Better Way to Deploy Kubeflow and More |
| 2:00 PM | 2:30 PM | Jooho Lee | Scale Your Models to Zero with Knative and Kserve |
| 2:30 PM | 3:00 PM | Qi Liu | Platform to Enable AI workload for Multi-Cloud with Hardware accelerations |
| \- | \- | \- | \- |
| 3:00 PM | 3:15 PM | \- | Break |
| \- | \- | \- | \- |
| 3:15 PM | 3:45 PM | Michal Hucko | How to use Kubeflow with MLflow |
| 3:45 PM | 4:15 PM | Vendant Mahabaleshwarkar | Monitoring the performance of your deployed models using OpenDataHub |
| 4:15 PM | 4:45 PM | Tommy Li | Tekton Optimizations for Kubeflow Pipelines 2.0: Challenges and Benefits |
| 4:45 PM | 5:15 PM | Ajay Tyagi | Scaling your Kubeflow Implementation Enterprise Wide, from tens to hundreds of users |
| 5:15 PM | 5:30 PM | Josh Bottom | Closing Remarks |
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/2023/kubeflow-summit-2023.md)
so we can improve.
Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# 2024 | Kubeflow
2024
====
Events from 2024
* * *
##### [Google Summer of Code 2024](https://www.kubeflow.org/events/gsoc-2024/)
Google Summer of Code 2024
##### [Watch: Cloud Native & Kubernetes AI Day 2024](https://www.youtube.com/playlist?list=PLj6h78yzYM2Mvqk_mNejD7kbe3tldxxsr)
##### [Watch: Kubeflow Summit 2024](https://www.youtube.com/playlist?list=PLj6h78yzYM2Nk-8Zyjaefz9yFJ-NxC-qn)
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/2024/_index.md)
so we can improve.
Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# Google Summer of Code 2024 | Kubeflow
Google Summer of Code 2024
==========================
Google Summer of Code 2024
* * *
Kubeflow Community is excited to announce that we have been [selected](https://summerofcode.withgoogle.com/programs/2024/organizations/kubeflow)
as organization to participate in [**Google Summer of Code 2024**](https://buildyourfuture.withgoogle.com/programs/summer-of-code)
. This page aims to help you participate in the Kubeflow organization for GSoC 2024.
How can I participate in Kubeflow GSoC?
---------------------------------------
Please go to [Google Summer of Code 2024](https://buildyourfuture.withgoogle.com/programs/summer-of-code)
and sign up as a student. Next, look at the [projects below](https://www.kubeflow.org/events/gsoc-2024/#project-ideas-for-2024-gsoc)
to decide which ones you are interested in. Note, that you must submit your proposals through the GSoC website and your proposal must be selected to participate.
Contributor applications open **March 18th, 2024** and close on **April 2nd, 2024**. For more information, see the GSoC website and/or reach out to the GSoC organizers. Please only contact mentors about projects, not the program itself.
### Slack
Please [**Join the Kubeflow Slack**](https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels)
.
Please **do not** reach out privately to mentors, instead, start a thread in the [`#gsoc-participants`](https://kubeflow.slack.com/archives/C06LW6Z3RA6)
channel so others can see the response. Be kind to our mentors, please search to see if your question has already been answered.
### Meetings
You may wish to attend the next community meeting for the group that is leading your chosen project, please see the calendar below for more information.
What if my proposal is not chosen?
----------------------------------
Please understand that not everyone can be selected for Google Summer of Code (GSoC), there are many possible candidates for each project.
However, we still want to encourage you to participate in the Kubeflow project! Get started by attending [working group meetings](https://www.kubeflow.org/docs/about/community/#kubeflow-community-meetings)
for components you want to help with, and reading our [contributing guide](https://www.kubeflow.org/docs/about/contributing/)
.
Project Ideas for 2024 GSoC
===========================
### Project 1: Kubeflow Notebooks 2.0
Kubeflow Notebook is a widely used component of Kubeflow that allows Data Scientists and ML Engineers to run web-based IDEs (JupyterLab, VSCode, RStudio) on Kubernetes clusters.
There is currently an effort to create the next major version of Kubeflow Notebooks.
The main idea is to change the Kubeflow Notebook CRD so that it is no longer just a wrapper around a Kubernetes PodSpec.
This foundational change enables users to:
* Update existing notebooks after spawning, to change their “pod config” (CPU/GPU/RAM), “volumes” (storage), and “image” (what packages are installed) from options that are defined by their admin.
* Make spawning notebooks less confusing for end-users. Pod configs stop being about specific parts of the PodSpec (e.g. tolerations, requests, limits), and become a drop-down list of user-friendly names (e.g. “Big GPU Notebook - A100 - 128GB”), similar to cloud “instance types”.
* Give admins more control over how workspaces are spawned, and the lifecycle of the “options” which are available to users. For example, admins can now “redirect” existing image/pod configs to new ones, but delay the application of these updates until the next pod restart (during which, the interface will display a warning to users that a change is pending).
* Support new web-based IDEs without needing to specifically integrate with them. Cluster admins can define a custom “kind” for their internal app, or even make “flavors” of existing apps (like Jupyter and VSCode) with the packages and pod-sizes required for specific teams in their organization.
You would be part of the larger effort, and involved in one or more code deliverables:
* See Kubeflow Notebooks docs: [https://www.kubeflow.org/docs/components/notebooks/overview/](https://www.kubeflow.org/docs/components/notebooks/overview/)
* See Kubeflow Notebooks 2.0 GitHub proposal: [https://github.com/kubeflow/kubeflow/issues/7156](https://github.com/kubeflow/kubeflow/issues/7156)
* See Kubeflow Notebooks 2.0 design document: [https://docs.google.com/document/d/1\_zk06zebbaTBdJ8TdU07Ibky25hqHGARXjVcsp2qEnU/edit](https://docs.google.com/document/d/1_zk06zebbaTBdJ8TdU07Ibky25hqHGARXjVcsp2qEnU/edit)
**Skills required:** Kubernetes Controllers (Golang - Kubebuilder) AND/OR Web Development (JS - Angular, Python - Flask)
**Difficulty:** medium/high
**Length:** 350 hrs
**Mentors:** Mathew Wicks, Kimonas Sitorchos, Julius von Kohout
**Component:** Notebooks
* * *
* * *
### Project 2: Rootless Kubeflow Container Images (Istio Ambient Mesh)
Kubeflow uses Istio as a service mesh, which by default requires “root level” network permissions for its init-containers. We want to reduce the number of privileged containers required to run Kubeflow, so are investigating using the Istio CNI, and eventually the Istio Ambient mesh.
You would be involved in testing and investigating the impacts of these changes, and helping push the integration forwards.
See the proposal for more information: [https://github.com/kubeflow/manifests/blob/master/proposals/20200913-rootlessKubeflow.md](https://github.com/kubeflow/manifests/blob/master/proposals/20200913-rootlessKubeflow.md)
**Skills required:** Istio, Kubernetes, YAML
**Difficulty:** medium
**Length:** 175 hrs
**Mentors:** Kimonas Sitorchos, Julius von Kohout
**Component:** Notebooks
* * *
* * *
### Project 3: Triage and Categorize Kubeflow GitHub Issues & PRs
The Kubeflow project needs help to triage, categorize, and highlight important Issues/PRs from the [https://github.com/kubeflow/kubeflow](https://github.com/kubeflow/kubeflow)
GitHub repo. There are around 200 open Issues and 200 open PRs, in addition to many Issues/PRs that have been lost to time (closed automatically due to inactivity).
Specifically, your goal would be to:
* Decide which Issues/PRs are still relevant
* Categorize Issues/PRs by type
* De-duplicate multiple Issues for the same request
* Suggest which ones are the most important.
* Help find “good first issues” for new members:
* [https://github.com/kubeflow/manifests/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22](https://github.com/kubeflow/manifests/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22)
* Review which PRs are likely safe to merge (especially dependabot ones)
**Skills required:** GitHub, Kubernetes, YAML, Python, GO, JS
**Difficulty:** medium
**Length:** 175 hrs
**Mentors:** Mathew Wicks, Kimonas Sitorchos, Julius von Kohout
**Component:** Notebooks/General
* * *
* * *
### Project 4: Implement LLM Tuning API for Katib
Recently, we implemented [a new `train` Python SDK API](https://github.com/kubeflow/training-operator/blob/master/docs/proposals/train_api_proposal.md)
in Kubeflow Training Operator to easily fine-tune LLMs on multiple GPUs with predefined datasets provider, model provider, and HuggingFace trainer.
To continue our roadmap around LLMOps in Kubeflow, we want to give user functionality to tune HyperParameters of LLMs using simple Python SDK APIs. It requires making appropriate changes to the Katib Python SDK which allows users to set model, dataset, and HyperParameters that they want to optimize for LLM.
**Skills required:** Kubernetes, YAML, Python
**Difficulty:** medium
**Length:** 350 hrs
**Mentors:** Andrey Velichkevich, Johnu George, Yuan (Terry) Tang, Yuki Iwai
**Component:** Katib
* * *
* * *
### Project 5: Support Distributed Jax for Training Operator
Open issue: [https://github.com/kubeflow/training-operator/issues/1619](https://github.com/kubeflow/training-operator/issues/1619)
We want to integrate Jax in Training Operator to run distributed training and fine-tuning jobs on Kubernetes using the Jax ML framework. We need to create a new Kubernetes Custom Resource for Jax (e.g. JaxJob) and update the Training Operator controller to support it. Potentially, we can integrate Jax with the Training Operator Python SDK to give Data Scientists simple APIs to create JaxJob on Kubernetes.
**Skills required:** Kubernetes, Go, YAML, Python
**Difficulty:** medium
**Length:** 350 hrs
**Mentors:** Andrey Velichkevich, Johnu George, Yuan (Terry) Tang, Yuki Iwai
**Component:** Training Operator
* * *
* * *
### Project 6: Push-based metrics collection for Katib
Open issue: [https://github.com/kubeflow/katib/issues/577](https://github.com/kubeflow/katib/issues/577)
.
Katib implements Metrics Collector as a sidecar container to collect training metrics from the Trials once training is complete. This Metrics Collector waits until the training container is complete and parses training logs to get appropriate metrics like accuracy or loss to get evaluation results for the HyperParameter tuning algorithm.
Sometimes the container sidecar approach might not work for users. For example, if their Trial resources executor doesn’t support sidecar containers. For such use-cases, we want to implement a new API to the Katib Python SDK to allow users to push metrics directly from their training scripts to the Katib DB.
**Skills required:** Kubernetes, Go, YAML, Python
**Difficulty:** medium
**Length:** 175 hrs
**Mentors:** Andrey Velichkevich, Johnu George, Yuan (Terry) Tang, Yuki Iwai
**Component:** Katib
* * *
* * *
### Project 7: Automate docs generation for Kubeflow Python SDKs
Open issue: [https://github.com/kubeflow/katib/issues/2081](https://github.com/kubeflow/katib/issues/2081)
Training Operator and Katib SDKs have [a valid docstring](https://github.com/kubeflow/training-operator/blob/0b6a30cd348e101506b53a1a176e4a7aec6e9f09/sdk/python/kubeflow/training/api/training_client.py#L50-L74)
for each public API that users are running. We want to automatically generate documentation for Kubeflow users from these docstrings, so users don’t need to read source code to understand APIs parameters.
**Skills required:** Python
**Difficulty**: medium
**Length:** 90 hrs
**Mentors:** Andrey Velichkevich, Johnu George, Shivay Lamba, Yuan (Terry) Tang, Yuki Iwai
**Component:** Katib/Training Operator
* * *
* * *
### Project 8: Support various parameter distributions like log-uniform in Katib
Open issue: [https://github.com/kubeflow/katib/pull/2059](https://github.com/kubeflow/katib/pull/2059)
We need to enhance Katib Experiment APIs to support various parameter distributions like uniform, log-uniform, qlog-uniform to make Katib more native to other HyperParameter tuning frameworks like Hyperopt. Currently, Katib supports only uniform distribution of integer, float, and categorical HyperParameters.
**Skills required:** Kubernetes, Python, Go, YAML
**Difficulty:** medium
**Length:** 350 hrs
**Mentors:** Andrey Velichkevich, Johnu George, Yuan (Terry) Tang, Yuki Iwai
**Component:** Katib
* * *
* * *
### Project 9: PostgreSQL integration in Kubeflow Pipelines
Open issue: [https://github.com/kubeflow/pipelines/issues/9813](https://github.com/kubeflow/pipelines/issues/9813)
Kubeflow Pipelines must store information about pipelines, experiments, runs, and artifacts in a database. Currently, the only database it supports is MySQL/MariaDB.
We plan to support PostgreSQL as an alternative to MySQL/MariaDB so users will be able to reuse existing databases, and PostgreSQL will be a good use case for supporting multiple databases.
**Skills required:** Kubernetes, Python, Go, YAML
**Difficulty:** medium
**Length:** 175 hrs
**Mentors:** Ricardo Martinelli, Shivay Lamba
**Component:** Pipelines
* * *
* * *
### Project 10: Enhancing KF Model Registry Python client for seamless ML imports from alternative registries
We aim to extend the capabilities of the KF Model Registry Python client by enabling smooth imports from various machine learning registries. While import from HuggingFace is already implemented (and can be used as a basis) we seek to integrate support for MLFlow, and other popular registry formats.
**Skills required:** Python, ML model serialization formats, YAML, Kubernetes/Kubeflow as a plus
**Difficulty:** medium
**Length:** 175 hrs
**Mentors:** Matteo Mortari, Andrea Lamparelli
**Component:** Model Registry
* * *
* * *
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/2024/gsoc-2024.md)
so we can improve.
Last modified January 21, 2025: [Restructure events section, and add GSoC 2025 page (#3962) (2bb1bc0)](https://github.com/kubeflow/website/commit/2bb1bc07efe7f4274444983d98d82e84f26411e5)
---
# 2025 | Kubeflow
2025
====
Events from 2025
* * *
##### [Kubeflow Virtual Symposium 2025](https://community.cncf.io/events/details/cncf-virtual-project-events-hosted-by-cncf-presents-kubeflow-virtual-planning-symposium-2025/)
##### [Watch: Kubeflow Summit 2025 - Europe](https://youtube.com/playlist?list=PLj6h78yzYM2NiD1QOHcD4PYY-8JxD0pNh&si=riE1ZKawYotJJMDg)
### Feedback
Was this page helpful?
Yes No
Thank you for your feedback!
We're sorry this page wasn't helpful. If you have a moment, please [share your feedback](https://github.com/kubeflow/website/issues/new?title=[Feedback]+events/past-events/2025/_index.md)
so we can improve.
Last modified May 6, 2025: [website: Archive Kubeflow Summit, add Kubeflow Virtual Symposium (#4101) (3010d5d)](https://github.com/kubeflow/website/commit/3010d5d24a68cbae7fbdc82fe5cb3ebdae63ec0d)
---