Self-healing cloud services in private multi-clouds

Harrison Mfula, Jukka K. Nurminen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

2 Citations (Scopus)

Abstract

As clouds continue to dominate as the de facto means of consuming shared computing resources, cloud providers are required to ensure that their services always meet or exceed service level agreements in terms of availability, reliability, scalability, performance etc every hour, day and year. These challenging requirements are even exacerbated when it comes to multi-cloud environments. In the era of automation and continuous cost reductions, using humans to manually test and trigger corrective actions when needed in order to fulfill these service level agreements is considered cumbersome and too expensive. In order to thrive, cloud service providers need a solution which is efficient, cheaper to deploy and easy to operate. This paper introduces a distributed container based solution for testing and self-healing of cloud resources. The proposed solution is based on a containerized multi-Agent architecture which leverages Elasticsearch, Logstash, Kibana (ELK) stack and uses a rule-based self-healing algorithm implemented using Drools rule engine and Spring Boot framework. Preliminary tests show that the solution meets its target objectives in terms of maintaining service level agreements, lowering deployment costs, high performance and operability.

Original languageEnglish
Title of host publication2018 International Conference on High Performance Computing & Simulation (HPCS)
EditorsKhalid Zine-Dine, Waleed W. Smari
PublisherInstitute of Electrical and Electronic Engineers IEEE
Pages165-170
Number of pages6
ISBN (Electronic)978-1-5386-7879-4
ISBN (Print)978-1-5386-7878-7
DOIs
Publication statusPublished - 29 Oct 2018
MoE publication typeNot Eligible
Event16th International Conference on High Performance Computing and Simulation, HPCS 2018 - Orleans, France
Duration: 16 Jul 201820 Jul 2018

Conference

Conference16th International Conference on High Performance Computing and Simulation, HPCS 2018
CountryFrance
CityOrleans
Period16/07/1820/07/18

Fingerprint

healing
Service Level Agreement
resources
Cost reduction
Preliminary Test
Agent Architecture
Resources
cost reduction
Containers
Scalability
Costs
automation
Container
containers
Automation
Trigger
Leverage
Availability
availability
engines

Keywords

  • Cloud computing
  • Multi-cloud
  • Self-healing

Cite this

Mfula, H., & Nurminen, J. K. (2018). Self-healing cloud services in private multi-clouds. In K. Zine-Dine, & W. W. Smari (Eds.), 2018 International Conference on High Performance Computing & Simulation (HPCS) (pp. 165-170). [8514346] Institute of Electrical and Electronic Engineers IEEE. https://doi.org/10.1109/HPCS.2018.00041
Mfula, Harrison ; Nurminen, Jukka K. / Self-healing cloud services in private multi-clouds. 2018 International Conference on High Performance Computing & Simulation (HPCS). editor / Khalid Zine-Dine ; Waleed W. Smari. Institute of Electrical and Electronic Engineers IEEE, 2018. pp. 165-170
@inproceedings{d36627d83e38421e935c8917c0606652,
title = "Self-healing cloud services in private multi-clouds",
abstract = "As clouds continue to dominate as the de facto means of consuming shared computing resources, cloud providers are required to ensure that their services always meet or exceed service level agreements in terms of availability, reliability, scalability, performance etc every hour, day and year. These challenging requirements are even exacerbated when it comes to multi-cloud environments. In the era of automation and continuous cost reductions, using humans to manually test and trigger corrective actions when needed in order to fulfill these service level agreements is considered cumbersome and too expensive. In order to thrive, cloud service providers need a solution which is efficient, cheaper to deploy and easy to operate. This paper introduces a distributed container based solution for testing and self-healing of cloud resources. The proposed solution is based on a containerized multi-Agent architecture which leverages Elasticsearch, Logstash, Kibana (ELK) stack and uses a rule-based self-healing algorithm implemented using Drools rule engine and Spring Boot framework. Preliminary tests show that the solution meets its target objectives in terms of maintaining service level agreements, lowering deployment costs, high performance and operability.",
keywords = "Cloud computing, Multi-cloud, Self-healing",
author = "Harrison Mfula and Nurminen, {Jukka K.}",
year = "2018",
month = "10",
day = "29",
doi = "10.1109/HPCS.2018.00041",
language = "English",
isbn = "978-1-5386-7878-7",
pages = "165--170",
editor = "Khalid Zine-Dine and Smari, {Waleed W.}",
booktitle = "2018 International Conference on High Performance Computing & Simulation (HPCS)",
publisher = "Institute of Electrical and Electronic Engineers IEEE",
address = "United States",

}

Mfula, H & Nurminen, JK 2018, Self-healing cloud services in private multi-clouds. in K Zine-Dine & WW Smari (eds), 2018 International Conference on High Performance Computing & Simulation (HPCS)., 8514346, Institute of Electrical and Electronic Engineers IEEE, pp. 165-170, 16th International Conference on High Performance Computing and Simulation, HPCS 2018, Orleans, France, 16/07/18. https://doi.org/10.1109/HPCS.2018.00041

Self-healing cloud services in private multi-clouds. / Mfula, Harrison; Nurminen, Jukka K.

2018 International Conference on High Performance Computing & Simulation (HPCS). ed. / Khalid Zine-Dine; Waleed W. Smari. Institute of Electrical and Electronic Engineers IEEE, 2018. p. 165-170 8514346.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

TY - GEN

T1 - Self-healing cloud services in private multi-clouds

AU - Mfula, Harrison

AU - Nurminen, Jukka K.

PY - 2018/10/29

Y1 - 2018/10/29

N2 - As clouds continue to dominate as the de facto means of consuming shared computing resources, cloud providers are required to ensure that their services always meet or exceed service level agreements in terms of availability, reliability, scalability, performance etc every hour, day and year. These challenging requirements are even exacerbated when it comes to multi-cloud environments. In the era of automation and continuous cost reductions, using humans to manually test and trigger corrective actions when needed in order to fulfill these service level agreements is considered cumbersome and too expensive. In order to thrive, cloud service providers need a solution which is efficient, cheaper to deploy and easy to operate. This paper introduces a distributed container based solution for testing and self-healing of cloud resources. The proposed solution is based on a containerized multi-Agent architecture which leverages Elasticsearch, Logstash, Kibana (ELK) stack and uses a rule-based self-healing algorithm implemented using Drools rule engine and Spring Boot framework. Preliminary tests show that the solution meets its target objectives in terms of maintaining service level agreements, lowering deployment costs, high performance and operability.

AB - As clouds continue to dominate as the de facto means of consuming shared computing resources, cloud providers are required to ensure that their services always meet or exceed service level agreements in terms of availability, reliability, scalability, performance etc every hour, day and year. These challenging requirements are even exacerbated when it comes to multi-cloud environments. In the era of automation and continuous cost reductions, using humans to manually test and trigger corrective actions when needed in order to fulfill these service level agreements is considered cumbersome and too expensive. In order to thrive, cloud service providers need a solution which is efficient, cheaper to deploy and easy to operate. This paper introduces a distributed container based solution for testing and self-healing of cloud resources. The proposed solution is based on a containerized multi-Agent architecture which leverages Elasticsearch, Logstash, Kibana (ELK) stack and uses a rule-based self-healing algorithm implemented using Drools rule engine and Spring Boot framework. Preliminary tests show that the solution meets its target objectives in terms of maintaining service level agreements, lowering deployment costs, high performance and operability.

KW - Cloud computing

KW - Multi-cloud

KW - Self-healing

UR - http://www.scopus.com/inward/record.url?scp=85057352219&partnerID=8YFLogxK

U2 - 10.1109/HPCS.2018.00041

DO - 10.1109/HPCS.2018.00041

M3 - Conference article in proceedings

AN - SCOPUS:85057352219

SN - 978-1-5386-7878-7

SP - 165

EP - 170

BT - 2018 International Conference on High Performance Computing & Simulation (HPCS)

A2 - Zine-Dine, Khalid

A2 - Smari, Waleed W.

PB - Institute of Electrical and Electronic Engineers IEEE

ER -

Mfula H, Nurminen JK. Self-healing cloud services in private multi-clouds. In Zine-Dine K, Smari WW, editors, 2018 International Conference on High Performance Computing & Simulation (HPCS). Institute of Electrical and Electronic Engineers IEEE. 2018. p. 165-170. 8514346 https://doi.org/10.1109/HPCS.2018.00041