Add GSoC 2026 project proposal for Kubeflow SDK OpenTelemetry integration

Signed-off-by: Dhanisha Phadate <[email protected]>

Author: Dhanisha Phadate

content/en/events/upcoming-events/gsoc-2026.md

@@ -102,5 +102,47 @@ To participate in GSoC with Kubeflow, you **must** meet the GSoC [eligibility re
 - List briefly skills you expect from contributor
 - 
 
+### Project X : Integrate Kubeflow SDK with OpenTelemetry
+
+**Components:** [kubeflow/sdk](https://www.github.com/kubeflow/sdk) 
+
+**Mentors:** [@dhanishaphadate](https://github.com/dhanishaphadate), [@jaiakash](https://www.github.com/jaiakash)
+
+**Contributor:** 
+
+**Details:** 
+
+The Kubeflow SDK enables users with limited Kubernetes knowledge to interact with the Kubeflow ecosystem using standard Python APIs. As AI/ML workloads become more complex and distributed, observability into pipeline execution, model training, and inference workflows becomes critical.
+
+This project aims to integrate the Kubeflow SDK with OpenTelemetry (OTel) to provide standardized, vendor-neutral telemetry for Kubeflow-based workloads. The integration will enable end-to-end visibility into SDK operations by capturing distributed traces, metrics, and logs across pipeline compilation, submission, execution, and training lifecycles.
+
+The project will also explore leveraging existing OpenTelemetry and Generative AI instrumentation patterns—such as span conventions for model execution, prompt handling, and inference steps—where applicable.
+
+[Kubeflow SDK Documentation](https://sdk.kubeflow.org/en/latest/index.html) 
+
+[Opentelemetry for genAI](https://opentelemetry.io/blog/2024/otel-generative-ai/)
+
+[Issue](https://github.com/kubeflow/sdk/issues/164)
+
+**Features Expected:**
+
+- Add OpenTelemetry instrumentation to key Kubeflow SDK components
+- Enable distributed tracing for pipeline execution and SDK operations
+- Collect and export metrics related to AI/ML workloads
+- Provide configurable OTel exporters and sampling options
+- Documentation and examples demonstrating observability setup and usage
+
+**Difficulty:** [intermediate|hard]
+
+**Size:** [350 hours]
+
+**Skills Required/Preferred:**
+
+- Python
+- Understanding of the Kubeflow Ecosystem (preferred)
+- OpenTelemetry (tracing, metrics, logging)
+- Distributed systems and observability concepts
+- Kubernetes and CRDs
+
 ---