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Future Internet 2021, 13, 61 8 of 13 Figure 3. Architecture and component layout for a single Competition. We use reverse proxies on VMs to balance and filter traffic to the notebook containers, restrict the kind of operations permitted on data (requirement #5), and provide additional layers of isolation from the Internet. We made the choice of VMs rather than containers as we ran into issues containerizing the proxy application. In addition, as we were devel- oping the application, we needed to log into the proxy periodically and make changes to configurations—this was much easier to do when they were in VMs rather than containers. Once we had the working configuration, we deployed using proxies in VMs. The containers containing teams’ notebooks are also on a separate segment. This seg- ment has access lists that restrict where on the Internet the notebooks can connect. Teams can download software to their notebooks from a limited number of software repositories. Another firewall controls access from the containers to the datasets used as the basis for competition. These datasets are also stored in the Cloud on SDI. The infrastructure in Figure 3 will be duplicated for each competition. This minimizes the opportunity for datasets from one competition leaking into another. It also reduces the effects of any single configuration mistake from affecting all competitions. This architectural decision matches the Cloud design pattern called the Bulkhead pattern [41]. 3. Results In this section, we examine the results of our implementation efforts. We describe how long it took to create the Data Collaborative and what resources were needed to design and implement, and we check if the resulting infrastructure met requirements. After that, we revisit our research questions and answer them in the context of the results. 3.1. Implementation Time and Resource Usage Initial meetings with the members of the team that would build that on the Data Collab- orative’s infrastructure (listed above as authors) started in September 2019. A first workable prototype with deployment documentation was delivered in June of 2020. The four authors of this paper did not work on this project full time—all had other projects done during the time frame of this work. 3.2. Evaluation of the Design and Implementation against Requirements Our design and implementation of the Data Collaborative met the goal of creating a highly scalable analytics platform for competitions. It is in active use, for both COVID-19 work [4] and for general AI-related challenges [42]. We first completed a small competition with 25 teams and are currently in the testing phase of a competition that has hosted some 300 teams [4], so it definitely is an operational utility for the XPRIZE foundation. Table 1 shows a list of the requirements in Section 2.4 and whether the implementation met them.PDF Image | Future Internet
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