{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T14:58:50Z","timestamp":1788879530954,"version":"build-2803163510"},"reference-count":20,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T00:00:00Z","timestamp":1713744000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T00:00:00Z","timestamp":1713744000000},"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":["Int J Syst Assur Eng Manag"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1007\/s13198-024-02329-4","type":"journal-article","created":{"date-parts":[[2024,4,22]],"date-time":"2024-04-22T16:02:31Z","timestamp":1713801751000},"page":"3234-3241","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Artificial intelligence techniques and tools for performance testing & monitoring of server-less computing"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9671-5918","authenticated-orcid":false,"given":"Deepak","family":"Khatri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sunil Kumar","family":"Khatri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deepti","family":"Mishra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,22]]},"reference":[{"key":"2329_CR1","unstructured":"\"Anomaly detection in serverless computing,\" ScienceDirect, https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0167739X2030026X"},{"key":"2329_CR2","unstructured":"AWS CloudWatch, https:\/\/aws.amazon.com\/cloudwatch\/"},{"key":"2329_CR3","unstructured":"Azure Monitor, https:\/\/azure.microsoft.com\/en-us\/services\/monitor\/"},{"key":"2329_CR4","unstructured":"Brown, M., & Williams, K. (2020). Anomaly detection in serverless function performance using machine learning techniques. International Conference on Cloud Computing, 112\u2013127."},{"key":"2329_CR5","unstructured":"Chen, L., Wang, Q., & Zhang, Y. (2019). Predictive analytics for workload prediction and auto-scaling in serverless computing. Proceedings of the International Conference on Cloud Computing and Big Data, 78\u201392."},{"key":"2329_CR6","unstructured":"\"Cost optimization in serverless computing,\" CloudHealth by VMware, https:\/\/www.cloudhealthtech.com\/blog\/serverless-architecture-cost-optimization"},{"key":"2329_CR7","unstructured":"Datadog APM, https:\/\/www.datadoghq.com\/apm\/"},{"key":"2329_CR8","unstructured":"Dynatrace, https:\/\/www.dynatrace.com\/platform\/serverless-monitoring\/"},{"key":"2329_CR9","doi-asserted-by":"publisher","unstructured":"\"Fault prediction in serverless applications,\" ACM Digital Library, https:\/\/dl.acm.org\/doi\/https:\/\/doi.org\/10.1145\/3298950.3316700","DOI":"10.1145\/3298950.3316700"},{"key":"2329_CR10","unstructured":"Google Cloud Monitoring, https:\/\/cloud.google.com\/monitoring"},{"issue":"2","key":"2329_CR11","first-page":"112","volume":"102","author":"R Jones","year":"2019","unstructured":"Jones R, Smith P (2019) Real-time monitoring and automated response systems for serverless applications. J Syst Softw 102(2):112\u2013126","journal-title":"J Syst Softw"},{"issue":"3","key":"2329_CR12","first-page":"590","volume":"6","author":"H Lee","year":"2018","unstructured":"Lee H, Park S, Kim D (2018) Resource prediction for serverless computing using machine learning models. IEEE Trans Cloud Comput 6(3):590\u2013602","journal-title":"IEEE Trans Cloud Comput"},{"key":"2329_CR13","unstructured":"\"Machine learning for resource allocation in serverless computing,\" IEEE Xplore, https:\/\/ieeexplore.ieee.org\/document\/8429574"},{"key":"2329_CR14","unstructured":"New Relic APM, https:\/\/newrelic.com\/application-monitoring"},{"key":"2329_CR15","unstructured":"Nguyen, T., & Nguyen, L. (2018). Dynamic resource allocation in serverless computing using machine learning models. Proceedings of the IEEE International Conference on Cloud Computing, 215\u2013230."},{"key":"2329_CR16","unstructured":"\"Predictive analytics in performance testing,\" TechTarget, https:\/\/searchsoftwarequality.techtarget.com\/definition\/predictive-analytics"},{"key":"2329_CR17","unstructured":"\"Real-time monitoring in serverless computing,\" Logz.io, https:\/\/logz.io\/blog\/serverless-monitoring\/"},{"issue":"2","key":"2329_CR18","first-page":"45","volume":"10","author":"J Smith","year":"2021","unstructured":"Smith J, Johnson A (2021) Performance testing of serverless computing: challenges and approaches. J Cloud Comput 10(2):45\u201362","journal-title":"J Cloud Comput"},{"issue":"4","key":"2329_CR19","doi-asserted-by":"crossref","first-page":"682","DOI":"10.1109\/TSC.2020.2964663","volume":"13","author":"Y Wang","year":"2020","unstructured":"Wang Y, Chen Z (2020) Cost optimization in serverless computing: a machine learning approach. IEEE Trans Serv Comput 13(4):682\u2013696","journal-title":"IEEE Trans Serv Comput"},{"key":"2329_CR20","unstructured":"Zhang, L., Li, S., & Chen, X. (2017). Fault prediction and recovery in serverless computing using machine learning techniques. Proceedings of the International Conference on Cloud Computing and Big Data, 172\u2013186."}],"container-title":["International Journal of System Assurance Engineering and Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02329-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13198-024-02329-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13198-024-02329-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,11]],"date-time":"2024-07-11T13:17:24Z","timestamp":1720703844000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13198-024-02329-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,22]]},"references-count":20,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["2329"],"URL":"https:\/\/doi.org\/10.1007\/s13198-024-02329-4","relation":{},"ISSN":["0975-6809","0976-4348"],"issn-type":[{"value":"0975-6809","type":"print"},{"value":"0976-4348","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,22]]},"assertion":[{"value":"7 October 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 February 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 March 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2024","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"No.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}}]}}