Towards Observability for Machine Learning Pipelines
Summary: Introduce MLTRACE, a platform-agnostic observability layer that unifies telemetry, provenance, metrics and lineage across heterogeneous ML pipeline stages to enable cross-stage root-cause analysis. Prototype shows unified tracing eases debugging of unexpected outputs and quality regressions in production. (summarized by gpt-5-mini on Feb 09 2026)
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,118 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 4.3928288e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,152 | MISTIQUE: A System to Store and Query Model Intermediates for Model Diagnosis | 2018 | SIGMOD | 9.4239787e-05 |
| 2,163 | Elastic Machine Learning Algorithms in Amazon SageMaker | 2020 | SIGMOD | 9.3949234e-05 |
| 3,875 | Cloudy with High Chance of DBMS: A 10-year Prediction for Enterprise-Grade ML | 2020 | CIDR | 6.675257e-05 |
| 4,196 | Overton: A Data System for Monitoring and Improving Machine-Learned Products | 2020 | CIDR | 6.3686231e-05 |
| 4,734 | MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines | 2021 | SIGMOD | 5.9615384e-05 |
| 5,684 | Dagger: A Data (not code) Debugger | 2020 | CIDR | 5.3720749e-05 |
| 6,733 | Hindsight Logging for Model Training | 2021 | VLDB | 4.9467666e-05 |
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