Trace Sampling

Trace Sampling is a method in distributed tracing that selectively captures a subset of execution traces from a cloud-native application’s observational data stream, distinguished by its use of probabilistic, adaptive, or policy-driven criteria to reduce monitoring overhead while preserving representativeness for subsequent analysis.

40

Publications

2K

Citations

151

Authors

66

Institutions

Publications per year

2017–2026

9

Authors

151

  1. JM
    Jonathan Mace

    John Brown University, United States

    3 publications · 213 citations

    3

    h-index

  2. DB
    Daniel Baumann

    University of Cambridge, United Kingdom

    2 publications · 313 citations

    2

    h-index

  3. PL
    Pedro Las-Casas

    Universidade Federal de Minas Gerais, Brazil

    2 publications · 75 citations

    2

    h-index

  4. ML
    M. L. Fischer

    Lawrence Berkeley National Laboratory, United States

    2 publications · 313 citations

    2

    h-index

  5. DH
    D. H. Neff

    Cooperative Institute for Research in Environmental Sciences, United States

    2 publications · 313 citations

    2

    h-index

1–5 of 151

Venues

  1. Atmospheric measurement techniques

    2 publications · 387 citations

    2

    h-index

  2. ACM SIGCOMM Computer Communication Review

    CCR · 2 publications · 65 citations

    2

    h-index

  3. Science of Computer Programming

    1 publications · 22 citations

    1

    h-index

  4. Proceedings of CASCON

    1 publications · 28 citations

    1

    h-index

  5. Information and Software Technology

    1 publications · 24 citations

    1

    h-index

1–5