Mach: Firefighting Time-Critical Issues in Complex Systems Using High-Frequency Telemetry
Authors: 
Franco Solleza, Shihang Li, William Sun, Richard Tang, 
Malte Schwarzkopf, 
Nesime Tatbul, Andrew Crotty, David Cohen, Stan ZdonikAuthors Info & Claims
Pages 4425 - 4428
Abstract
To understand the complex interactions in modern software, engineers often rely on high-frequency telemetry (HFT) data generated via tools like eBPF. However, today's database systems are too slow for HFT's rate and volume and cannot process HFT within the limited resources available on individual host machines.
Mach is a new storage engine for collecting and querying HFT. Key to Mach is the Temporal Skip Log (TSL)---a lightweight, write-optimized, log-based data structure specialized for HFT. Mach supports high ingest rates and makes data immediately queryable while operating within a limited on-host resource envelope.
Our demo shows how Mach helps engineers collect and query HFT in near real-time when diagnosing performance problems. In contrast, current systems and data reduction techniques fail to keep up. While a widely used time series database (InfluxDB) drops much of the HFT, the audience will see how Mach loses no data and allows them to interactively explore HFT from application and kernel events as they arrive.
References
[1]
[n.d.]. FasterLog. https://microsoft.github.io/FASTER/docs/fasterlog-basics/
[2]
[n.d.]. InfluxDB. https://www.influxdata.com/
[3]
[n.d.]. OpenTelemetry Collector. https://opentelemetry.io/docs/collector/
[4]
Badrish Chandramouli, Dong Xie, Yinan Li, and Donald Kossmann. 2019. Fish-Store: Fast Ingestion and Indexing of Raw Data. PVLDB 12, 12 (2019), 1922--1925.
[5]
Dengfeng Gao, Christian S Jensen, Richard T Snodgrass, and Michael D Soo. 2005. Join Operations in Temporal Databases. VLDB J. 14 (2005), 2--29.
[6]
Brad Glasbergen, Michael Abebe, Khuzaima Daudjee, Daniel Vogel, and Jian Zhao. 2020. Sentinel: Understanding Data Systems. In SIGMOD. 2729--2732.
[7]
Brad Glasbergen, Fangyu Wu, and Khuzaima Daudjee. 2021. Dendrite: Bolt-on Adaptivity for Data Systems. In SIGMOD. 2726--2730.
[8]
Franco Solleza, Andrew Crotty, Suman Karumuri, Nesime Tatbul, and Stan Zdonik. 2022. Mach: A Pluggable Metrics Storage Engine for the Age of Observability. In CIDR.
[9]
Goutham V. 2017. How and Why Prometheus' New Storage Engine Pushes the Limits of Time Series Databases. https://youtu.be/C4YV-9CrawA?si=S6poj7qBUu2LS3UR Talk at DockerCon EU 2017.
[10]
Chen Wang, Xiangdong Huang, Jialin Qiao, Tian Jiang, Lei Rui, Jinrui Zhang, Rong Kang, Julian Feinauer, Kevin Mcgrail, Peng Wang, Diaohan Luo, Jun Yuan, Jianmin Wang, and Jiaguang Sun. 2020. Apache IoTDB: Time-series Database for Internet of Things. PVLDB 13, 12 (2020), 2901--2904.
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VLDB Endowment
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Published: 01 August 2024
Published in PVLDB Volume 17, Issue 12
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