IT Operations Analytics: Root Cause Analysis via Complex Event Processing

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14610%2F19%3A00108341" target="_blank" >RIV/00216224:14610/19:00108341 - isvavai.cz</a>

Výsledek na webu

<a href="http://dl.ifip.org/db/conf/im/im2019demo/191791.pdf" target="_blank" >http://dl.ifip.org/db/conf/im/im2019demo/191791.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

IT Operations Analytics: Root Cause Analysis via Complex Event Processing

Popis výsledku v původním jazyce

IT operation analytics (ITOA) is used for discovering complex patterns in data from IT systems. The analytics process still includes a significant portion of human interaction which makes the analysis costly and error-prone. Human operators need to formulate queries over the collected data to identify the complex patterns. Since the queries describe complex relations, the queries are usually multilevel, perplexing, and complicated to create. For the querying the complex relations, complex event processing methods are successfully used in other domains. In this paper, we demonstrate an application of the complex event processing principles in the ITOA domain. We adjust T-Rex complex event processing engine and improve TESLA event processing language to suit for ITOA tasks. Our demonstration includes two real-world use-cases. We show the utilization of the complex event processing for root cause analysis and demonstrate the natural formulation of complex queries that results in the reduction of the volume of the required human interaction.

Název v anglickém jazyce

IT Operations Analytics: Root Cause Analysis via Complex Event Processing

Popis výsledku anglicky

IT operation analytics (ITOA) is used for discovering complex patterns in data from IT systems. The analytics process still includes a significant portion of human interaction which makes the analysis costly and error-prone. Human operators need to formulate queries over the collected data to identify the complex patterns. Since the queries describe complex relations, the queries are usually multilevel, perplexing, and complicated to create. For the querying the complex relations, complex event processing methods are successfully used in other domains. In this paper, we demonstrate an application of the complex event processing principles in the ITOA domain. We adjust T-Rex complex event processing engine and improve TESLA event processing language to suit for ITOA tasks. Our demonstration includes two real-world use-cases. We show the utilization of the complex event processing for root cause analysis and demonstrate the natural formulation of complex queries that results in the reduction of the volume of the required human interaction.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/TH02010185" target="_blank" >TH02010185: Výzkum a vývoj pokročilých analytických nástrojů pro analýzu bezpečnostních a výkonnostních problémů síťové infrastruktury, aplikací a služeb</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)

ISBN

9781728106182

ISSN

1573-0077

e-ISSN

—

Počet stran výsledku

2

Strana od-do

741-742

Název nakladatele

IEEE

Místo vydání

Washington DC, USA

Místo konání akce

Washington DC, USA

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000469937200142