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An Open-Source Benchmark Suite for Microservices and Their Hardware-Software Implications for Cloud & Edge Systems
Open accessAbstract
Cloud services have recently started undergoing a major shift from monolithic applications, to graphs of hundreds or thousands of loosely-coupled microservices. Microservices fundamentally change a lot of assumptions current cloud systems are designed with, and present both opportunities and challenges when optimizing for quality of service (QoS) and cloud utilization.
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Cites
Witten, I. H. (2008) · Cited by 9,143
Large-Scale Machine Learning with Stochastic Gradient Descent
Bottou, L. (2010) · Proceedings of COMPSTAT'2010 · doi:10.1007/978-3-7908-2604-3_16 · Cited by 5,795
In-Datacenter Performance Analysis of a Tensor Processing Unit
Jouppi, N. P., Young, C., Patil, N., Patterson, D., Agrawal, G., Bajwa, R., Bates, S., Bhatia, S., Boden, N., Borchers, A., et al. (2017) · Proceedings of the 44th Annual International Symposium on Computer Architecture · doi:10.1145/3079856.3080246 · Cited by 4,537
Self-citationDean, J., & Barroso, L. A. (2013) · Communications of the ACM · doi:10.1145/2408776.2408794 · Cited by 1,852
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
Barroso, L. A., & Hölzle, U. (2009) · Synthesis lectures on computer architecture · doi:10.2200/s00193ed1v01y200905cac006 · Cited by 1,711
(2011) · doi:10.5555/1972457.1972488 · Cited by 1,619
Large-scale cluster management at Google with Borg
Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., & Wilkes, J. (2015) · Proceedings of the Tenth European Conference on Computer Systems · doi:10.1145/2741948.2741964 · Cited by 1,468
Ferdman, M., Adileh, A., Kocberber, O., Volos, S., Alisafaee, M., Jevdjic, D., Kaynak, C., Popescu, A. D., Ailamaki, A., & Falsafi, B. (2012) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/2150976.2150982 · Cited by 818
Delimitrou, C., & Kozyrakis, C. (2014) · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · doi:10.1145/2541940.2541941 · Cited by 704
Self-citationA reconfigurable fabric for accelerating large-scale datacenter services
Putnam, A. R., Caulfield, A. M., Chung, E. S., Chiou, D., Constantinides, K., Demme, J., Esmaeilzadeh, H., Fowers, J., Gopal, G. P., Gray, J., et al. (2014) · ACM SIGARCH Computer Architecture News · doi:10.1145/2678373.2665678 · Cited by 700
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Wen, Y., Zhang, Y., Cheng, G., Deng, S., & Yin, J. (2022) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.7257
Self-citationWasay, A., Tatbul, N., & Gottschlich, J. (2022) · Proceedings of the VLDB Endowment · doi:10.14778/3554821.3554892
Microservice deployment problem in the edge-side of intelligent factories
Xu, D., Li, Z., & Zhang, R. (2023) · International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) · doi:10.1117/12.2660933
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Liang, D., Xiao-guang, Z., Zhang, Y., & Liu, Q. (2022) · doi:10.1145/3577530.3577577
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Natalie, R. Y., Mahendika, D., Salong, A., Xu, S., & Aji, L. J. (2023) · Journal International of Lingua and Technology · doi:10.55849/jiltech.v3i1.497 · Cited by 1
Pykulytsky, O., & Havano, B. (2023) · Advances in Cyber-Physical Systems · doi:10.23939/acps2023.02.133
CO-TRIS: Container Orchestration – Transforming container using Resource Inspection System
Roh, J.-Y., Choi, S.-H., & Park, K.-W. (2023) · IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE) · doi:10.1109/aike59827.2023.00027
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Gu, X., Liu, J., & Wang, Q. (2023) · IEEE International Conference on Collaboration and Internet Computing (CIC) · doi:10.1109/cic58953.2023.00024
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Kvasov, A., Şahin, M., Hébert, C., & de Oliveira, A. S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-54129-2_42
Wang, D., Shen, H., & Tian, H. (2023) · IEEE International Conference on Parallel and Distributed Systems (ICPADS) · doi:10.1109/icpads60453.2023.00352
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Mallellu, S. P., Maheswari, V. U., Aluvalu, R., & Kantipudi, M. P. (2024) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/979-8-3693-1682-5.ch008
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Liang, M., Gan, Y., Li, Y., Torres, C., Dhanotia, A., Ketkar, M., & Delimitrou, C. (2024) · IEEE Micro · doi:10.1109/mm.2024.3419067
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Ma, Y., Smith, S. R., Dai, B., Franke, H., Sukhwani, B., Asaad, S., Xiong, J., Kindratenko, V., & Chen, D. (2024) · IEEE ... International Conference on Cloud Computing · doi:10.1109/cloud62652.2024.00023
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Ghorab, R. M., & Doudali, T. D. (2024) · doi:10.1145/3660605.3660942 · Cited by 1
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Toczé, K. (2024) · Linköping studies in science and technology. Dissertations · doi:10.3384/9789180757485
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Luo, L., Zhao, G., Xu, H., Chung, C.-J., & Xie, L. (2024) · International Workshop on Quality of Service · doi:10.1109/iwqos61813.2024.10682836
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Frantz, R., García, J. S., Copik, M., Monroy, I. T., Olmos, J. J. V., Bloch, G., & Girolamo, S. D. (2024) · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · doi:10.1109/scw63240.2024.00126
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Morrison, D. R. (2024) · Queue · doi:10.1145/3711677
Mohammadi, N., Rasoolzadegan, A., Hosseinpour, S., Sabeghi, M., & Shahrestani, A. (2026) · Empirical Software Engineering · doi:10.1007/s10664-026-10949-6
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Tang, Z., Li, Y., Mao, Z., Zhao, L., & Li, K. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-2830-8_35
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White, O., Jing, Y., Ghosn, A., Steiner, M., Vahldiek-Oberwagner, A., Vij, M., & Vilanova, L. (2025) · doi:10.1145/3723851.3723854
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Wang, Y., Shi, Q., Chen, X., & Peng, X. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-5032-3_4
Li, Q., Kraft, P., Kozyrakis, C., Zaharia, M., & Stonebraker, M. R. (2025) · The VLDB Journal · doi:10.1007/s00778-024-00899-0
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Kelantonakis, G., Kourou, F., & Magoutis, K. (2025) · ACM/SPEC International Conference on Performance Engineering (ICPE) · doi:10.1145/3676151.3719363
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Li, Z., Yu, R., & Liu, J. (2025) · ACM/SPEC International Conference on Performance Engineering (ICPE) · doi:10.1145/3680256.3721317
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Lubas, Y., Straesser, M., Rohwer, I., Kounev, S., & Bauer, A. (2025) · ACM/SPEC International Conference on Performance Engineering (ICPE) · doi:10.1145/3680256.3721321
Tang, Y., Tan, Z., Chen, J., Yao, X., Zhong, G., & Liu, F. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-4503-9_17
Microns: Connection Subsetting for Microservices in Shared Clusters
Liao, J., Li, J., Zhou, Z., Xu, F., Liu, F., & Chen, X. (2025) · ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) · doi:10.1145/3726854.3727294
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Anand, V., Las-Casas, P., Fonseca, R., & Kaufmann, A. (2025) · doi:10.1109/aiops66738.2025.00009
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Schutte, M., Mol, L. V., Christodoulou, G., & Katsifodimos, A. (2025) · Database Programming Languages · doi:10.1145/3735106.3736537
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Bian, S., Wang, W., Yang, Y., & Zhao, L. (2024) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc64274.2024.00111
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Xu, K., Tziantzioulis, G., & Wentzlaff, D. (2025) · IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) · doi:10.1109/ispass64960.2025.00027
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Righi, A., Aneggi, A., Li, X., & Janes, A. (2025) · IEEE International Symposium on Service-Oriented System Engineering (SOSE) · doi:10.1109/sose67019.2025.00010
Geng, Y., Zhang, H., Wu, Z., Li, Y., Wang, J., & Yin, X. (2025) · ACM SIGCOMM Conference (SIGCOMM) · doi:10.1145/3718958.3750477
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Yang, J., Park, E., Baek, K., & Ko, I. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-97207-2_30
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Metadata
- Authors
- Gan, Y., Zhang, Y., Cheng, D., Shetty, A., Rathi, P., Katarki, N., Bruno, A., Hu, J., Ritchken, B., Jackson, B., Hu, K., Pancholi, M., He, Y., Clancy, B., Colen, C., Wen, F., Leung, C., Wang, S., Zaruvinsky, L., Espinosa, M., Lin, R., Liu, Z., Padilla, J., & Delimitrou, C.
- Affiliations
- Cornell University (US)
- Cornell University, Ithaca, NY, USA
- Venue
- Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems
- Publisher
- ACM
- Published
- 2019-04-04
- Pages
- 3-18
- OpenAlex
- W2931122162
- Cited by
- 665
- References
- 72
- Citations by year
- 2026: 103 · 2025: 127 · 2024: 117 · 2023: 91 · 2022: 67 · 2021: 71 · 2020: 67 · 2019: 21
- FWCI
- 45.01
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (publishedVersion)
- Funders
- NSF (CNS-1422088)
- Topics
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Computer Networks and Communications › Software System Performance and Reliability
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Keywords
- microservices, benchmark suite, hardware-software co-design, cloud systems, edge computing, quality of service, monolith to microservices migration
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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