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Future Internet 2021, 13, 61 9 of 13 In general, requirements were fulfilled. Some requirements are hard to prove, such as being “secure.” Table 1. Data Collaborative high-level requirements and whether they were met. Goal 1. Scalable Infrastructure 2. Usable Analytics Platform 3. Isolated Secure Platform 4. Scalable Analytics Compute Platform (self-service capacity adds) 5. Control of data 6. Manageability 7. Fast Implementation 8. Cost-controlled Goal Met? Yes Yes Possibly Probably Yes Yes Yes Yes Title 3 Scaled to 300 Users for one complete competition and one in progress Secure as far as we know—no incidents so far Put in place but not yet exercised Access to datasets is controlled Manageable by small XPRIZE team Started in late 2019 and first competition started in mid-2020 No evidence of cost issues at this point We conclude that the Data Collaborative infrastructure did meet its requirements. 3.3. Revisiting Our Research Questions A successful implementation allows us to revisit our research questions. 3.3.1. Are Applications Developed in the Cloud Moving to Only Use Containers? As described in our design, the Data Collaborative uses a variety of technologies for very different circumstances. There are Cloud design patterns that dictate when Serverless computing, SDI, and containers are best used. Using a VM was a surprise, though. 3.3.2. How Has the COVID-19 Pandemic Affected Application Development and Deployment? As mentioned in the introduction, the COVID-19 Pandemic pushed XPRIZE to focus on new challenges and to accelerate development. Another major effect of the pandemic was on the requirements. Another way to look at its influence is to look at the “non- requirements” for the Data Collaborative, which were not priorities because of the need to implement relatively quickly: 1. 2. 3. Portability between Clouds: Extensive work has been done try to create technology that makes applications portable between Cloud Service Providers [43] and avoiding vendor lock-in [44,45]. This goal was simply not a priority in our efforts to get the Data Collaborative up and running. We chose to use the Cloud Service Provider that we were most familiar with to get the service to production as soon as possible. Ultra-low cost: While a reasonable cost is a key requirement (#8 above), having an extremely low cost, especially at the expense of having a usable and working solution, was not. High Performance: While our requirement for a usable and scalable platform (re- quirements #1 and #2) demands enough performance to be usable, it did not demand high performance. We need the Data Collaborative in a relatively short time frame that worked and was usable. In addition, the contest time frames should allow for time for analyses to complete. Similar to many other IT development projects, developing the Data Collaborative had to be done remotely. There were face-to-face meetings and work sessions during late 2019, but the bulk of development was done remotely at home by the team in locations ranging from Northern California to Southern California and Arizona. We would occasionally encounter problems in working with our Cloud Service Provider, but it was impossible to know whether these were from Cloud Service Provider capacity problems or just network congestion from stay-at-home orders [46].PDF Image | Future Internet
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