IT Operations Analytics: Root Cause Analysis via Complex Event
Processing

D 2019

IT Operations Analytics: Root Cause Analysis via Complex Event Processing

DRAŠAR, Martin a Tomáš JIRSÍK

Základní údaje

Originální název

IT Operations Analytics: Root Cause Analysis via Complex Event Processing

Autoři

DRAŠAR, Martin a Tomáš JIRSÍK

Vydání

Washington DC, USA, 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM), od s. 741-742, 2 s. 2019

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL, URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14610/19:00108341

Organizační jednotka

Ústav výpočetní techniky

ISBN

978-1-72810-618-2

ISSN

UT WoS

000469937200142

EID Scopus

2-s2.0-85067007496

Klíčová slova anglicky

IT operation analysis; complex event processing; root cause; IP flows; Tesla; T-Rex

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 24. 4. 2020 15:44, Mgr. Alena Mokrá

Anotace

V originále

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.

Návaznosti

TH02010185, projekt VaV

Název: Výzkum a vývoj pokročilých analytických nástrojů pro analýzu bezpečnostních a výkonnostních problémů síťové infrastruktury, aplikací a služeb (Akronym: ITOA)

Investor: Technologická agentura ČR, Výzkum a vývoj pokročilých analytických nástrojů pro analýzu bezpečnostních a výkonnostních problémů síťové infrastruktury, aplikací a služeb

Přiložené soubory

2019-IM-it-operations-analytic-root-cause-analysis-via-complex-event-processing-poster.pdf

2019-IM-it-operations-analytic-root-cause-analysis-via-complex-event-processing.pdf

Citovat

DRAŠAR, Martin a Tomáš JIRSÍK. IT Operations Analytics: Root Cause Analysis via Complex Event Processing. Online. In 2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM). Washington DC, USA: IEEE, 2019, s. 741-742. ISBN 978-1-72810-618-2.

@inproceedings{1524436,
   author = {Drašar, Martin and Jirsík, Tomáš},
   address = {Washington DC, USA},
   booktitle = {2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)},
   keywords = {IT operation analysis; complex event processing; root cause; IP flows; Tesla; T-Rex},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Washington DC, USA},
   isbn = {978-1-72810-618-2},
   pages = {741-742},
   publisher = {IEEE},
   title = {IT Operations Analytics: Root Cause Analysis via Complex Event Processing},
   url = {https://ieeexplore.ieee.org/document/8717814},
   year = {2019}
}

TY  - CONF
ID  - 1524436
AU  - Drašar, Martin - Jirsík, Tomáš
PY  - 2019
TI  - IT Operations Analytics: Root Cause Analysis via Complex Event Processing
PB  - IEEE
CY  - Washington DC, USA
SN  - 9781728106182
KW  - IT operation analysis
KW  - complex event processing
KW  - root cause
KW  - IP flows
KW  - Tesla
KW  - T-Rex
UR  - https://ieeexplore.ieee.org/document/8717814
L2  - http://dl.ifip.org/db/conf/im/im2019demo/191791.pdf
N2  - 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.
ER  -

DRAŠAR, Martin a Tomáš JIRSÍK. IT Operations Analytics: Root Cause Analysis via Complex Event Processing. Online. In \textit{2019 IFIP/IEEE Symposium on Integrated Network and Service Management (IM)}. Washington DC, USA: IEEE, 2019, s.~741-742. ISBN~978-1-72810-618-2.

Přehled o publikaci