D 2021

Cloud Native Data Platform for Network Telemetry and Analytics

TOVARŇÁK, Daniel; Matúš RAČEK and Petr VELAN

Basic information

Original name

Cloud Native Data Platform for Network Telemetry and Analytics

Authors

TOVARŇÁK, Daniel; Matúš RAČEK and Petr VELAN

Edition

Izmir, Turkey (Virtual), 17th International Conference on Network and Service Management, p. 394-396, 3 pp. 2021

Publisher

IFIP Open Digital Library, IEEE Xplore

Other information

Language

English

Type of outcome

Proceedings paper

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

Publication form

electronic version available online

References:

URL

Marked to be transferred to RIV

Yes

RIV identification code

RIV/00216224:14610/21:00120063

Organization

Ústav výpočetní techniky – Repository – Repository

ISBN

978-3-903176-36-2

DOI

https://doi.org/10.23919/CNSM52442.2021.9615568

UT WoS

000836226700063

EID Scopus

2-s2.0-85123423271

Keywords in English

Data Lakehouse;Network Flows;Log Data

Links

VI20202022164, research and development project.
Changed: 23/3/2023 04:10, RNDr. Daniel Jakubík

Abstract

In the original language

In this manuscript, we present a prototype of a modular data platform that is able to continuously ingest, process, retain, and analyse large amounts of network telemetry data in a scalable and straightforward manner. It follows a recently proposed Data Lakehouse architectural pattern, which is an evolution of two well-known approaches used in this area -- data warehouses and data lakes. The platform is based on open standards and open-source components, and it follows cloud native principles in order to be able to run in modern computing environments such as public, private, and hybrid clouds. The primary focus of the prototype is network telemetry and analytics over traffic flows and infrastructure logs for the purposes of cyber-security digital forensics and incident response. During the demonstration part, we will further describe internal workings of the presented data platform and showcase its capabilities and possible applications on a public dataset.
Displayed: 2/5/2026 21:25