Publication:
End-to-end MLOps integration: a case study with ISS telemetry data

cris.virtual.departmentInformatik im Maschinenbau
cris.virtual.departmentInformatik im Maschinenbau
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cris.virtual.departmentInformatik im Maschinenbau
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cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
cris.virtual.departmentbrowseInformatik im Maschinenbau
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dc.contributor.authorSteude, Henrik Sebastian
dc.contributor.authorGeier, Christian
dc.contributor.authorModdemann, Lukas
dc.contributor.authorCreutzenberg, Martin
dc.contributor.authorPfeifer, Jann
dc.contributor.authorTurk, Samo
dc.contributor.authorNiggemann, Oliver
dc.date.issued2024-03
dc.description.abstractKubeflow integrates a suite of powerful tools for Machine Learning (ML) software development and deployment, typically showcased independently. In this study, we integrate these tools within an end- to-end workflow, a perspective not extensively explored previously. Our case study on anomaly detection using telemetry data from the International Space Station (ISS) investigates the integration of various tools—Dask, Katib, PyTorch Operator, and KServe—into a single Kubeflow Pipelines (KFP) workflow. This investigation reveals both the strengths and limitations of such integration in a real-world context. The insights gained from our study provide a comprehensive blueprint for practitioners and contribute valuable feedback for the open source community developing Kubeflow.
dc.description.versionNA
dc.identifier.doi10.24405/15316
dc.identifier.urihttps://openhsu.ub.hsu-hh.de/handle/10.24405/15316
dc.language.isoen
dc.relation.conferenceML4CPS – Machine Learning for Cyber-Physical Systems
dc.relation.orgunitInformatik im Maschinenbau
dc.relation.orgunitJust Add AI
dc.relation.orgunitAirbus Defence & Space
dc.relation.orgunitLufthansa Technik
dc.rights.accessRightsopen access
dc.subjectMLOps
dc.subjectKubeflow
dc.subjectISS
dc.subjectAnomaly detection
dc.titleEnd-to-end MLOps integration: a case study with ISS telemetry data
dc.typeConference paper
dspace.entity.typePublication
hsu.uniBibliography
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