Improving Docker Registry Design Based on Production Workload Analysis


Ali Anwar, Virginia Tech; Mohamed Mohamed and Vasily Tarasov, IBM Research—Almaden; Michael Littley, Virginia Tech; Lukas Rupprecht, IBM Research—Almaden; Yue Cheng, George Mason University; Nannan Zhao, Virginia Tech; Dimitrios Skourtis, Amit S. Warke, and Heiko Ludwig, and Dean Hildebrand, IBM Research—Almaden; Ali R. Butt, Virginia Tech


Containers offer an efficient way to run workloads as independent microservices that can be developed, tested and deployed in an agile manner. To facilitate this process, container frameworks offer a registry service that enables users to publish and version container images and share them with others. The registry service plays a critical role in the startup time of containers since many container starts entail the retrieval of container images from a registry. To support research efforts on optimizing the registry service, large-scale and realistic traces are required. In this paper, we perform a comprehensive characterization of a large-scale registry workload based on traces that we collected over the course of 75 days from five IBM data centers hosting production-level registries. We present a trace replayer to perform our analysis and infer a number of crucial insights about container workloads, such as request type distribution, access patterns, and response times. Based on these insights, we derive design implications for the registry and demonstrate their ability to improve performance. Both the traces and the replayer are open-sourced to facilitate further research.

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@inproceedings {210500,
author = {Ali Anwar and Mohamed Mohamed and Vasily Tarasov and Michael Littley and Lukas Rupprecht and Yue Cheng and Nannan Zhao and Dimitrios Skourtis and Amit S. Warke and Heiko Ludwig and Dean Hildebrand and Ali R. Butt},
title = {Improving Docker Registry Design Based on Production Workload Analysis},
booktitle = {16th USENIX Conference on File and Storage Technologies (FAST 18)},
year = {2018},
isbn = {978-1-931971-42-3},
address = {Oakland, CA},
pages = {265--278},
url = {},
publisher = {USENIX Association},
month = feb