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Towards Observability for Production Machine Learning Pipelines
Summary: End-to-end observability for production ML pipelines to address post-deployment issues like data shift and silent failures. Proposes a bolt-on data-management architecture enabling detection, diagnosis, and reaction, wrapping existing tools to deliver ML observability.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 12912
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 4.3886184e-05
- Overall Rank
- 9,116 | 36.65%
- DOI
-
10.14778/3565838.3565853
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 18 |
On Random Sampling over Joins |
1999 |
SIGMOD |
0.00092569117 |
| 70 |
Hive - A Warehousing Solution Over a Map-Reduce Framework |
2009 |
VLDB |
0.00059744625 |
| 192 |
HoloClean: Holistic Data Repairs with Probabilistic Inference |
2017 |
VLDB |
0.00035692958 |
| 431 |
The Aqua Approximate Query Answering System |
1999 |
SIGMOD |
0.00023397171 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 788 |
ActiveClean: Interactive Data Cleaning For Statistical Modeling |
2016 |
VLDB |
0.00016618698 |
| 1,320 |
Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters |
2016 |
SIGMOD |
0.00012606067 |
| 1,403 |
Detecting Data Errors: Where are we and what needs to be done? |
2016 |
VLDB |
0.00012180046 |
| 1,422 |
Data Management Challenges in Production Machine Learning |
2017 |
SIGMOD |
0.00012050431 |
| 1,481 |
Automating Large-Scale Data Quality Verification |
2018 |
VLDB |
0.00011715754 |
| 1,942 |
SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging |
2021 |
SIGMOD |
0.00010010569 |
| 2,157 |
MISTIQUE: A System to Store and Query Model Intermediates for Model Diagnosis |
2018 |
SIGMOD |
9.4153917e-05 |
| 2,164 |
Elastic Machine Learning Algorithms in Amazon SageMaker |
2020 |
SIGMOD |
9.3953268e-05 |
| 2,267 |
Ground: A Data Context Service |
2017 |
CIDR |
9.1554363e-05 |
| 2,417 |
Combining Quantitative and Logical Data Cleaning |
2016 |
VLDB |
8.8502556e-05 |
| 4,006 |
Data Platform for Machine Learning |
2019 |
SIGMOD |
6.5371762e-05 |
| 4,197 |
Overton: A Data System for Monitoring and Improving Machine-Learned Products |
2020 |
CIDR |
6.3625568e-05 |
| 4,347 |
On Biased Reservoir Sampling in the Presence of Stream Evolution |
2006 |
VLDB |
6.2588401e-05 |
| 4,731 |
MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines |
2021 |
SIGMOD |
5.9558692e-05 |
| 5,380 |
ReproZip: Computational Reproducibility With Ease |
2016 |
SIGMOD |
5.53752e-05 |
| 5,698 |
Dagger: A Data (not code) Debugger |
2020 |
CIDR |
5.3669165e-05 |
| 6,481 |
Joins on Samples: A Theoretical Guide for Practitioners |
2020 |
VLDB |
5.039683e-05 |
| 6,724 |
Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing |
2021 |
SIGMOD |
4.9449472e-05 |
| 6,735 |
Hindsight Logging for Model Training |
2021 |
VLDB |
4.9420202e-05 |
| 8,166 |
Capturing and Querying Fine-grained Provenance of Preprocessing Pipelines in Data Science |
2021 |
VLDB |
4.567959e-05 |
| 9,224 |
VisClean: Interactive Cleaning for Progressive Visualization |
2020 |
VLDB |
4.3657563e-05 |
| 11,315 |
Towards Observability for Machine Learning Pipelines |
2022 |
CIDR |
4.1905499e-05 |
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| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 6,464 |
Materialization and Reuse Optimizations for Production Data Science Pipelines |
2022 |
SIGMOD |
5.0471003e-05 |
| 8,253 |
Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines |
2023 |
SIGMOD |
4.5444167e-05 |
| 4,731 |
MLINSPECT: A Data Distribution Debugger for Machine Learning Pipelines |
2021 |
SIGMOD |
5.9558692e-05 |
| 13,244 |
Cloud Observability: A MELTing Pot for Petabytes of Heterogenous Time Series |
2021 |
CIDR |
- |
| 7,138 |
Ease.ml/ci and Ease.ml/meter in Action: Towards Data Management for Statistical Generalization |
2019 |
VLDB |
4.8164681e-05 |
| 4,006 |
Data Platform for Machine Learning |
2019 |
SIGMOD |
6.5371762e-05 |
| 6,290 |
Lightweight Inspection of Data Preprocessing in Native Machine Learning Pipelines |
2021 |
CIDR |
5.1220786e-05 |
| 1,422 |
Data Management Challenges in Production Machine Learning |
2017 |
SIGMOD |
0.00012050431 |
| 2,456 |
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities |
2021 |
SIGMOD |
8.7649259e-05 |
| 11,315 |
Towards Observability for Machine Learning Pipelines |
2022 |
CIDR |
4.1905499e-05 |