{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T15:56:26Z","timestamp":1743090986107,"version":"3.40.3"},"publisher-location":"Cham","reference-count":34,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031790584"},{"type":"electronic","value":"9783031790591"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-79059-1_15","type":"book-chapter","created":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T07:34:52Z","timestamp":1739000092000},"page":"239-263","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Observability: Real-Time Application Health Checks"],"prefix":"10.1007","author":[{"given":"Tim","family":"Eichhorn","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4547-7000","authenticated-orcid":false,"given":"Jo\u00e3o Luiz Rebelo","family":"Moreira","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7432-7653","authenticated-orcid":false,"given":"Lu\u00eds Ferreira","family":"Pires","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucas","family":"Meertens","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,9]]},"reference":[{"key":"15_CR1","unstructured":"Ali, S., Boufaied, C., Bianculli, D., Branco, P., Briand, L.C., Aschbacher, N.: An empirical study on log-based anomaly detection using machine learning. ArXiv abs\/2307.16714 (2023). https:\/\/api.semanticscholar.org\/CorpusID:260334470"},{"key":"15_CR2","doi-asserted-by":"publisher","unstructured":"Bertero, C., Roy, M., Sauvanaud, C., Tredan, G.: Experience report: log mining using natural language processing and application to anomaly detection. In: 2017 IEEE 28th International Symposium on Software Reliability Engineering (ISSRE), pp. 351\u2013360 (2017). https:\/\/doi.org\/10.1109\/ISSRE.2017.43","DOI":"10.1109\/ISSRE.2017.43"},{"key":"15_CR3","unstructured":"Bia\u0142ecki, A., Muir, R., Ingersoll, G.: Apache Lucene 4 (2012)"},{"key":"15_CR4","doi-asserted-by":"publisher","first-page":"e489","DOI":"10.7717\/peerj-cs.489","volume":"7","author":"J C\u00e2ndido","year":"2021","unstructured":"C\u00e2ndido, J., Aniche, M., van Deursen, A.: Log-based software monitoring: a systematic mapping study. PeerJ Comput. Sci. 7, e489 (2021). https:\/\/doi.org\/10.7717\/peerj-cs.489","journal-title":"PeerJ Comput. Sci."},{"key":"15_CR5","unstructured":"CAPE Groep: Mendix Marketplace - LogTransporter (2024). https:\/\/marketplace.mendix.com\/link\/component\/218262"},{"key":"15_CR6","unstructured":"Courcy, D.: Elastic 7.16: Streamlined data integrations drive results that matter (2021). https:\/\/www.elastic.co\/blog\/whats-new-elastic-7-16-0"},{"key":"15_CR7","doi-asserted-by":"publisher","unstructured":"Du, S., Cao, J.: Behavioral anomaly detection approach based on log monitoring. In: 2015 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC), pp. 188\u2013194 (2015). https:\/\/doi.org\/10.1109\/BESC.2015.7365981","DOI":"10.1109\/BESC.2015.7365981"},{"key":"15_CR8","unstructured":"Elastic: Anomaly detection job types. https:\/\/www.elastic.co\/guide\/en\/machine-learning\/current\/ml-anomaly-detection-job-types.html"},{"key":"15_CR9","unstructured":"Elastic: Categorize text aggregation. https:\/\/www.elastic.co\/guide\/en\/elasticsearch\/reference\/current\/search-aggregations-bucket-categorize-text-aggregation.html"},{"key":"15_CR10","unstructured":"Elastic: Elastic Common Schema. https:\/\/www.elastic.co\/elasticsearch\/common-schema"},{"key":"15_CR11","unstructured":"Folmer, E., Verhoosel, J.: State of the art on semantic is standardization, interoperability & quality. J. Biomech. (2011)"},{"key":"15_CR12","unstructured":"Gormley, C., Tong, Z.: Elasticsearch the Definitive Guide: A Distributed Real-Time Search and Analytics Engine. O\u2019Reilly Media, 1 edn. (2015)"},{"key":"15_CR13","unstructured":"Grafana Labs: About Grafana. https:\/\/grafana.com\/docs\/grafana\/latest\/introduction\/"},{"key":"15_CR14","doi-asserted-by":"publisher","unstructured":"He, P., Zhu, J., Zheng, Z., Lyu, M.R.: Drain: an online log parsing approach with fixed depth tree. In: 2017 IEEE International Conference on Web Services (ICWS), pp. 33\u201340 (2017). https:\/\/doi.org\/10.1109\/ICWS.2017.13","DOI":"10.1109\/ICWS.2017.13"},{"key":"15_CR15","unstructured":"Kozhukh, D.: An easy look at Grafana architecture (2024). https:\/\/www.kozhuhds.com\/blog\/an-easy-look-at-grafana-architecture\/"},{"issue":"17","key":"15_CR16","doi-asserted-by":"publisher","first-page":"8275","DOI":"10.3390\/app11178275","volume":"11","author":"G Kumar","year":"2021","unstructured":"Kumar, G., Basri, S., Imam, A.A., Khowaja, S.A., Capretz, L.F., Balogun, A.O.: Data harmonization for heterogeneous datasets: a systematic literature review. Appl. Sci. 11(17), 8275 (2021). https:\/\/doi.org\/10.3390\/app11178275","journal-title":"Appl. Sci."},{"key":"15_CR17","doi-asserted-by":"publisher","unstructured":"Layer, L., et al.: Automatic log analysis with NLP for the CMS workflow handling. In: EPJ Web of Conferences, vol. 245, p. 03006 (2020). https:\/\/doi.org\/10.1051\/epjconf\/202024503006","DOI":"10.1051\/epjconf\/202024503006"},{"key":"15_CR18","doi-asserted-by":"publisher","unstructured":"Le, V., Zhang, H.: Log-based anomaly detection without log parsing. In: 2021 36th IEEE\/ACM International Conference on Automated Software Engineering (ASE), pp. 492\u2013504 (2021). https:\/\/doi.org\/10.1109\/ASE51524.2021.9678773","DOI":"10.1109\/ASE51524.2021.9678773"},{"issue":"6","key":"15_CR19","first-page":"633","volume":"4","author":"P Madkan","year":"2014","unstructured":"Madkan, P.: Empirical study of ERP implementation strategies-filling gaps between the success and failure of ERP implementation process. Int. J. Inf. Comput. Technol. 4(6), 633\u2013642 (2014)","journal-title":"Int. J. Inf. Comput. Technol."},{"key":"15_CR20","unstructured":"Mendix: Deploy API (2024). https:\/\/docs.mendix.com\/apidocs-mxsdk\/apidocs\/deploy-api\/"},{"key":"15_CR21","doi-asserted-by":"publisher","unstructured":"Meng, W., et al.: A semantic-aware representation framework for online log analysis, pp.\u00a01\u20137 (2020). https:\/\/doi.org\/10.1109\/ICCCN49398.2020.9209707","DOI":"10.1109\/ICCCN49398.2020.9209707"},{"key":"15_CR22","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, vol. 26 (2013)"},{"key":"15_CR23","doi-asserted-by":"publisher","unstructured":"Mitra, M., Sy, D.: The rise of elastic stack (2016). https:\/\/doi.org\/10.13140\/RG.2.2.17596.03203","DOI":"10.13140\/RG.2.2.17596.03203"},{"key":"15_CR24","doi-asserted-by":"publisher","unstructured":"M\u00fcnch, J., Armbrust, O., Kowalczyk, M., Soto, M.: Prescriptive Process Models. In: M\u00fcnch, J., Armbrust, O., Kowalczyk, M., Soto, M. (eds.) Software Process Definition and Management, pp. 19\u201377. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-24291-5_2","DOI":"10.1007\/978-3-642-24291-5_2"},{"key":"15_CR25","unstructured":"Plotly: Plotly JavaScript Open Source Graphing Library. https:\/\/plotly.com\/javascript\/"},{"key":"15_CR26","doi-asserted-by":"publisher","unstructured":"Srivastava, D.: An introduction to data visualization tools and techniques in various domains. Int. J. Comput. Trends Technol. 71, 125\u2013130 (2023). https:\/\/doi.org\/10.14445\/22312803\/IJCTT-V71I4P116","DOI":"10.14445\/22312803\/IJCTT-V71I4P116"},{"key":"15_CR27","unstructured":"Trent, B.: Categorize your logs with Elasticsearch categorize_text aggregation (2022). https:\/\/www.elastic.co\/blog\/categorize-your-logs-with-the-new-elasticsearch-categorize-text-search-aggregation"},{"key":"15_CR28","doi-asserted-by":"publisher","unstructured":"Wang, J., et al.: LogEvent2vec: LogEvent-to-vector based anomaly detection for large-scale logs in internet of things. Sens. (Switz.) 20(9) (2020). https:\/\/doi.org\/10.3390\/s20092451","DOI":"10.3390\/s20092451"},{"key":"15_CR29","doi-asserted-by":"publisher","unstructured":"Wang, J., Zhao, C., He, S., Gu, Y., Alfarraj, O., Abugabah, A.: LogUAD: log unsupervised anomaly detection based on word2Vec. Comput. Syst. Sci. Eng. 41(3), 1207\u20131222 (2022). https:\/\/doi.org\/10.32604\/csse.2022.022365","DOI":"10.32604\/csse.2022.022365"},{"issue":"11","key":"15_CR30","doi-asserted-by":"publisher","first-page":"843","DOI":"10.4236\/jsea.2017.1011047","volume":"10","author":"Y Wei","year":"2017","unstructured":"Wei, Y., Li, M., Xu, B.: Research on Establish an Efficient Log Analysis System with Kafka and Elastic Search. J. Softw. Eng. Appl. 10(11), 843\u2013853 (2017). https:\/\/doi.org\/10.4236\/jsea.2017.1011047","journal-title":"J. Softw. Eng. Appl."},{"key":"15_CR31","doi-asserted-by":"publisher","unstructured":"Yu, B., et al.: Deep learning or classical machine learning? An empirical study on log-based anomaly detection. In: Proceedings of the IEEE\/ACM 46th International Conference on Software Engineering, ICSE 2024, Association for Computing Machinery, New York (2024). https:\/\/doi.org\/10.1145\/3597503.3623308","DOI":"10.1145\/3597503.3623308"},{"key":"15_CR32","doi-asserted-by":"publisher","unstructured":"Zamfir, V.A., Carabas, M., Carabas, C., Tapus, N.: Systems monitoring and big data analysis using the elastic search system. In: Proceedings - 2019 22nd International Conference on Control Systems and Computer Science, CSCS 2019, pp. 188\u2013193. Institute of Electrical and Electronics Engineers Inc. (2019). https:\/\/doi.org\/10.1109\/CSCS.2019.00039","DOI":"10.1109\/CSCS.2019.00039"},{"issue":"4","key":"15_CR33","doi-asserted-by":"publisher","first-page":"269","DOI":"10.2753\/MIS0742-1222300410","volume":"30","author":"K Zhao","year":"2014","unstructured":"Zhao, K., Xia, M.: Forming interoperability through interorganizational systems standards. J. Manag. Inf. Syst. 30(4), 269\u2013298 (2014). https:\/\/doi.org\/10.2753\/MIS0742-1222300410","journal-title":"J. Manag. Inf. Syst."},{"key":"15_CR34","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3201379","author":"J Zhou","year":"2022","unstructured":"Zhou, J., Qian, Y., Zou, Q., Liu, P., Xiang, J.: DeepSyslog: deep anomaly detection on syslog using sentence embedding and metadata. IEEE Trans. Inf. Forensics Secur. (2022). https:\/\/doi.org\/10.1109\/TIFS.2022.3201379","journal-title":"IEEE Trans. Inf. Forensics Secur."}],"container-title":["Lecture Notes in Business Information Processing","Enterprise Design, Operations, and Computing. EDOC 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-79059-1_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,8]],"date-time":"2025-02-08T07:35:04Z","timestamp":1739000104000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-79059-1_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031790584","9783031790591"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-79059-1_15","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"type":"print","value":"1865-1348"},{"type":"electronic","value":"1865-1356"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"9 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EDOC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Enterprise Design, Operations, and Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"edoc2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.big.tuwien.ac.at\/biweek2024\/edoc.php","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}