Analysing Dependability and Performance of a Real-World Elastic Search Application
| Autor: | Guto Leoni Santos, M. Eduardo Ares, Sergej Svorobej, Luiz Affonso Guedes, Theo Lynn, Manuel Noya Mario, Malika Bendechache, James M. Byrne, Patricia Takako Endo, Ivanovitch Silva |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Fault tree analysis
business.industry Computer science Quality of service Big data 020206 networking & telecommunications 02 engineering and technology Computer simulation Reliability engineering Computational complexity Scalability 0202 electrical engineering electronic engineering information engineering Stochastic Petri net Redundancy (engineering) Dependability 020201 artificial intelligence & image processing business Enterprise software |
| Zdroj: | LADC Bendechache, Malika ORCID: 0000-0003-0069-1860 |
| DOI: | 10.1109/ladc48089.2019.8995709 |
| Popis: | —Increased complexity in IT, big data, and advanced analytical techniques are some of the trends driving demand for more sophisticated and scalable search technology. Despite Quality of Service (QoS) being a critical success factor in most enterprise software service offerings, it is often not a generic component of the enterprise search software stack. In this paper, we explore enterprise search engine dependability and performance using a real-world company architecture and associated data sourced from an ElasticSearch implementation on Linknovate.com. We propose a Fault Tree model to assess the availability and reliability of the Linknovate.com architecture. The results of the Fault Tree model are fed into a Stochastic Petri Net (SPN) model to analyze how failures and redundancy impact application performance of the use case system. Availability and MTTF were used to evaluate the reliability and throughput was used to evaluate the performance of the target system. The best results for all three metrics were returned in scenarios with high levels of redundancy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|