QuEST: Fast, Expressive, and Cheap Analytics for Distributed Traces Using Cloud Storage

Jessica Berg; Muhammad Haseeb; Haiming Chen; Yaojia Ju; Anirudh Sivaraman; Ravi Netravali; Srinivas Narayana

QuEST: Fast, Expressive, and Cheap Analytics for Distributed Traces Using Cloud Storage

Jessica Berg, Muhammad Haseeb, Haiming Chen, Yaojia Ju, Anirudh Sivaraman, Ravi Netravali, Srinivas Narayana

Computer Science

Research output: Contribution to journal › Conference article › peer-review

Abstract

Distributed tracing is the practice of tracking a user's request through a microservice application from entrance to exit. The data emitted by this practice is so large that it is often difficult to store and analyze. We propose a new system to store tracing data on top of low-cost cloud object storage, a service provided by major cloud providers. We describe indexing structures that achieve fast query times and considerable query expressiveness by adapting the design of indices to both cloud storage and the unique distributed tracing domain.

Original language	English (US)
Journal	CEUR Workshop Proceedings
Volume	3462
State	Published - 2023
Event	Joint Workshops at the 49th International Conference on Very Large Data Bases, VLDBW 2023 - Vancouver, Canada Duration: Aug 28 2023 → Sep 1 2023

Keywords

Cloud Storage
Distributed Tracing

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "QuEST: Fast, Expressive, and Cheap Analytics for Distributed Traces Using Cloud Storage",

abstract = "Distributed tracing is the practice of tracking a user's request through a microservice application from entrance to exit. The data emitted by this practice is so large that it is often difficult to store and analyze. We propose a new system to store tracing data on top of low-cost cloud object storage, a service provided by major cloud providers. We describe indexing structures that achieve fast query times and considerable query expressiveness by adapting the design of indices to both cloud storage and the unique distributed tracing domain.",

keywords = "Cloud Storage, Distributed Tracing",

author = "Jessica Berg and Muhammad Haseeb and Haiming Chen and Yaojia Ju and Anirudh Sivaraman and Ravi Netravali and Srinivas Narayana",

note = "Publisher Copyright: {\textcopyright} 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; Joint Workshops at the 49th International Conference on Very Large Data Bases, VLDBW 2023 ; Conference date: 28-08-2023 Through 01-09-2023",

year = "2023",

language = "English (US)",

volume = "3462",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

publisher = "CEUR-WS",

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TY - JOUR

T1 - QuEST

T2 - Joint Workshops at the 49th International Conference on Very Large Data Bases, VLDBW 2023

AU - Berg, Jessica

AU - Haseeb, Muhammad

AU - Chen, Haiming

AU - Ju, Yaojia

AU - Sivaraman, Anirudh

AU - Netravali, Ravi

AU - Narayana, Srinivas

PY - 2023

Y1 - 2023

N2 - Distributed tracing is the practice of tracking a user's request through a microservice application from entrance to exit. The data emitted by this practice is so large that it is often difficult to store and analyze. We propose a new system to store tracing data on top of low-cost cloud object storage, a service provided by major cloud providers. We describe indexing structures that achieve fast query times and considerable query expressiveness by adapting the design of indices to both cloud storage and the unique distributed tracing domain.

AB - Distributed tracing is the practice of tracking a user's request through a microservice application from entrance to exit. The data emitted by this practice is so large that it is often difficult to store and analyze. We propose a new system to store tracing data on top of low-cost cloud object storage, a service provided by major cloud providers. We describe indexing structures that achieve fast query times and considerable query expressiveness by adapting the design of indices to both cloud storage and the unique distributed tracing domain.

KW - Cloud Storage

KW - Distributed Tracing

UR - http://www.scopus.com/inward/record.url?scp=85171270602&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85171270602&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85171270602

SN - 1613-0073

VL - 3462

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 28 August 2023 through 1 September 2023

ER -

QuEST: Fast, Expressive, and Cheap Analytics for Distributed Traces Using Cloud Storage

Abstract

Keywords

ASJC Scopus subject areas

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