{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T15:07:21Z","timestamp":1784300841102,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":17,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T00:00:00Z","timestamp":1783209600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,7,5]]},"DOI":"10.1145\/3803437.3805232","type":"proceedings-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T14:27:39Z","timestamp":1784298459000},"page":"591-596","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From Load Tests to Live Streams: Graph Embedding-Based Anomaly Detection in Microservice Architectures"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0117-8911","authenticated-orcid":false,"given":"Srinidhi","family":"Madabhushi","sequence":"first","affiliation":[{"name":"Amazon Prime Video, Seattle, Washingtoon, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1425-6469","authenticated-orcid":false,"given":"Pranesh","family":"Vyas","sequence":"additional","affiliation":[{"name":"Amazon Prime Video, Austin, Texas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0446-5541","authenticated-orcid":false,"given":"Swathi","family":"Vaidyanathan","sequence":"additional","affiliation":[{"name":"Amazon Prime Video, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5948-3043","authenticated-orcid":false,"given":"Mayur","family":"Kurup","sequence":"additional","affiliation":[{"name":"Amazon Prime Video, Austin, Texas, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8682-5996","authenticated-orcid":false,"given":"Elliott","family":"Nash","sequence":"additional","affiliation":[{"name":"Amazon Prime Video, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2607-9366","authenticated-orcid":false,"given":"Yegor","family":"Silyutin","sequence":"additional","affiliation":[{"name":"Amazon Prime Video, Seattle, Washington, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Correction of Error (CoE). https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.coe.en.html","author":"Services Amazon Web","year":"2025","unstructured":"Amazon Web Services. 2020. Correction of Error (CoE). https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.coe.en.html. Accessed: July 2025."},{"key":"e_1_3_2_1_2_1","volume-title":"Game day. https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.gameday.en.html","author":"Services Amazon Web","year":"2025","unstructured":"Amazon Web Services. 2020. Game day. https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.gameday.en.html. Accessed: July 2025."},{"key":"e_1_3_2_1_3_1","volume-title":"Root Cause Analysis (RCA). https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.rca.en.html","author":"Services Amazon Web","year":"2025","unstructured":"Amazon Web Services. 2020. Root Cause Analysis (RCA). https:\/\/wa.aws.amazon.com\/wellarchitected\/2020-07-02T19-33-23\/wat.concept.rca.en.html. Accessed: July 2025."},{"key":"e_1_3_2_1_4_1","volume-title":"Scaling Prime Video for peak NFL streaming on AWS. https:\/\/reinvent.awsevents.com\/content\/dam\/reinvent\/2024\/slides\/arc\/ARC311_Scaling-Prime-Video-for-peak-NFL-streaming-on-AWS.pdf","author":"Services Amazon Web","year":"2025","unstructured":"Amazon Web Services. 2024. Scaling Prime Video for peak NFL streaming on AWS. https:\/\/reinvent.awsevents.com\/content\/dam\/reinvent\/2024\/slides\/arc\/ARC311_Scaling-Prime-Video-for-peak-NFL-streaming-on-AWS.pdf. Accessed: July 2025."},{"key":"e_1_3_2_1_5_1","volume-title":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 55\u201364","author":"Beladev Moran","year":"2020","unstructured":"Moran Beladev, Lior Rokach, Gilad Katz, Ido Guy, and Kira Radinsky. 2020. td-graphembed: Temporal dynamic graph-level embedding. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management. 55\u201364."},{"key":"e_1_3_2_1_6_1","volume-title":"Convolutional neural networks on graphs with fast localized spectral filtering. arXiv preprint arXiv:1606.09375","author":"Defferrard Micha\u00ebl","year":"2016","unstructured":"Micha\u00ebl Defferrard, Xavier Bresson, and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. arXiv preprint arXiv:1606.09375 (2016)."},{"key":"e_1_3_2_1_7_1","volume-title":"Proceedings of the 2019 SIAM International Conference on Data Mining. SIAM, 594\u2013602","author":"Ding Kaize","year":"2019","unstructured":"Kaize Ding, Jundong Li, Rohit Bhanushali, and Huan Liu. 2019. Deep anomaly detection on attributed networks. In Proceedings of the 2019 SIAM International Conference on Data Mining. SIAM, 594\u2013602."},{"key":"e_1_3_2_1_8_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_1_9_1","volume-title":"Variational graph auto-encoders. arXiv preprint arXiv:1611.07308","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling. 2016. Variational graph auto-encoders. arXiv preprint arXiv:1611.07308 (2016)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","first-page":"12012","DOI":"10.1109\/TKDE.2021.3118815","article-title":"A comprehensive survey on graph anomaly detection with deep learning","volume":"35","author":"Ma Xiaoxiao","year":"2023","unstructured":"Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z Sheng, Hui Xiong, and Leman Akoglu. 2023. A comprehensive survey on graph anomaly detection with deep learning. IEEE Transactions on Knowledge and Data Engineering 35, 12 (2023), 12012\u201312038.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_1_11_1","volume-title":"2020 IEEE International Conference on Service-Oriented System Engineering (SOSE). IEEE, 86\u201395","author":"Meng Si","year":"2020","unstructured":"Si Meng, Xianglin Zhan, Jianfeng Huang, and Thomas Fuhrman. 2020. Cross-correlation analysis for microservice architecture understanding and prediction. In 2020 IEEE International Conference on Service-Oriented System Engineering (SOSE). IEEE, 86\u201395."},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"34","author":"Pareja Aldo","year":"2020","unstructured":"Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B Schardl, and Charles E Leiserson. 2020. EvolveGCN: Evolving graph convolutional networks for dynamic graphs. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34. 5363\u20135370."},{"key":"e_1_3_2_1_13_1","volume-title":"A survey on oversmoothing in graph neural networks. arXiv preprint arXiv:2303.10993","author":"Rusch T Konstantin","year":"2023","unstructured":"T Konstantin Rusch, Michael M Bronstein, and Siddhartha Mishra. 2023. A survey on oversmoothing in graph neural networks. arXiv preprint arXiv:2303.10993 (2023)."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 13th International Conference on Web Search and Data Mining. 519\u2013527","author":"Sankar Aravind","year":"2020","unstructured":"Aravind Sankar, Yanhong Wu, Liang Gou, Wei Zhang, and Hao Yang. 2020. Dysat: Deep neural representation learning on dynamic graphs via self-attention networks. In Proceedings of the 13th International Conference on Web Search and Data Mining. 519\u2013527."},{"key":"e_1_3_2_1_15_1","volume-title":"A single point of contact (SPOC) to bring your departments together. https:\/\/www.topdesk.com\/en\/blog\/single-point-of-contact-spoc\/","year":"2025","unstructured":"TOPdesk. 2025. A single point of contact (SPOC) to bring your departments together. https:\/\/www.topdesk.com\/en\/blog\/single-point-of-contact-spoc\/. Accessed: July 2025."},{"key":"e_1_3_2_1_16_1","volume-title":"Graph attention networks. arXiv preprint arXiv:1710.10903","author":"Velickovic Petar","year":"2017","unstructured":"Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Li\u00f2, and Yoshua Bengio. 2017. Graph attention networks. arXiv preprint arXiv:1710.10903 (2017)."},{"key":"e_1_3_2_1_17_1","volume-title":"Proceedings of the 28th International Joint Conference on Artificial Intelligence. 4419\u20134425","author":"Zheng Li","year":"2019","unstructured":"Li Zheng, Zhenpeng Li, Jian Li, Zhao Li, and Jun Gao. 2019. Addgraph: Anomaly detection in dynamic graph using attention-based temporal gcn. In Proceedings of the 28th International Joint Conference on Artificial Intelligence. 4419\u20134425."}],"event":{"name":"FSE Companion '26: 34th ACM International Conference on the Foundations of Software Engineering","location":"Concordia University Montreal QC Canada","acronym":"FSE Companion '26","sponsor":["SIGSOFT ACM Special Interest Group on Software Engineering"]},"container-title":["Proceedings of the 34th ACM International Conference on the Foundations of Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3803437.3805232","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T14:44:36Z","timestamp":1784299476000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3803437.3805232"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,5]]},"references-count":17,"alternative-id":["10.1145\/3803437.3805232","10.1145\/3803437"],"URL":"https:\/\/doi.org\/10.1145\/3803437.3805232","relation":{},"subject":[],"published":{"date-parts":[[2026,7,5]]},"assertion":[{"value":"2026-07-17","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}