Diana Atanasova
Open Source Engineer at VMware
Bulgaria
Summary
🤩
Rockstar🎓
Top SchoolDiana Atanasova is an Open Source Engineer with 11 years of experience building backend systems in Go and Java, currently contributing to cloud-native ML workflows at VMware and to EdgeX Foundry’s IoT middleware. She focuses on backend logic, API design, database integrations and security—skills honed through work on Kubeflow Pipelines (adding auth and SA token flows) and refactoring device command handling in a major EdgeX Go monorepo. Diana’s background in telco MANO and NMS platforms gives her a strong foundation in networked systems and operational automation, while her master’s in Applied Mathematics and Informatics underpins a methodical approach to complex problems. Comfortable with Kubernetes, gRPC, Docker and both Redis and MySQL, she combines pragmatic engineering with an open-source maintainer mindset. Colleagues rely on her for durable, auditable solutions that bridge ML, edge computing, and traditional carrier-grade systems.
11 years of coding experience
10 years of employment as a software developer
Master's degree, Applied Mathematic and Informatic, Master's degree, Applied Mathematic and Informatic at Technical University of Sofia
Github Skills (30)
api-rest10
kubernetes10
authorizations10
python10
apidoc10
back-end-development10
api-design10
restful-api10
kubeflow10
go10
mlops10
api10
authorization10
kubernetes-pods10
pipeline10
Programming languages (8)
Github contributions (5)
edgexfoundry/edgex-go
Apr 2019 - Feb 2020
EdgeX Golang Services Monorepo | Owner: Core/Support WG
Role in this project:
Back-end Developer
Back-end DeveloperContributions:22 commits, 25 PRs, 57 comments in 10 months
Contributions summary:Diana primarily focused on refactoring and enhancing the core command functionality within the EdgeX Go monorepo. They modified the interface for `CommandResponseFromDevice` and implemented new endpoints for device command execution via device name. The user also addressed issues related to updating device state and implemented database changes. Their contributions demonstrate a focus on backend logic, API enhancements, and database interaction within the context of an IoT edge computing framework.
golangmonorepoedgexowner-coreowner
kubeflow/pipelines
May 2021 - Aug 2022
Machine Learning Pipelines for Kubeflow
Role in this project:Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:54 reviews, 5 commits, 14 PRs in 1 year 2 months
Contributions summary:Diana's contributions primarily focus on refactoring and enhancing machine-learning pipelines within the Kubeflow Pipelines framework. They updated pipeline names, addressing specific issues related to naming conventions and ensuring compatibility. The user implemented features to authorize the `readArtifacts` and `ReportMetrics` endpoints, and enabled SA Token based authentication between the Persistence Agent and the Pipeline API server. These changes improved the security and maintainability of the platform.
pipelinetektondata-sciencemachine-learningmlops
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