This document discusses the top challenges researchers experience in the use of the Cloud and provides recommendations and guiding principles for putting a solution into place.
research_in_the_cloud_white_paper.pdf | 331 KB |
research_in_the_cloud_white_paper.pdf | 331 KB |
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Version | 1.02 |
Last Revised | 03-Jun-2021 |
Status | Published |
Document Type | Single Topic Advisory |
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Harvard has a large, cost-effective set of on-premises services for researchers. Nevertheless, the University spent well over $1m for research in the Cloud in CY2020 not inclusive of vendor credits which themselves may represent over $1m in research spend. The level of support that researchers experience in their use of the Cloud can vary widely. We have identified the following top challenges and recommendations:
Supporting research in the Cloud effectively requires both expertise in the Cloud and in Research Computing and Data (hereafter referred to as simply “Research Computing”). When researchers decide to use the Cloud, they find themselves needing to largely build up that Cloud expertise, which can include:
The result is that they need to spend time or money that could otherwise be used for research getting themselves or their teams up-to-speed on the Cloud. It also means that they’re on their own for important issues like security and cost management. Nevertheless, Cloud computing is a growing portion of the University’s research spend
Existing services (notably Consolidated Billing and Enterprise Discounts) are viewed positively, but knowledge of those existing services is not sufficiently widely distributed.
We have identified three key challenges/opportunities in the support of research in the Cloud at Harvard:
Guiding Principles:
Any solution put into place must be built with the following principles in mind:
Key Recommendations:
These recommendations are further detailed in the Discussion section.
The methodology used to reach these conclusions included input from the Higher Ed community (via survey – see Appendix A) and from in-person interviews with Harvard research teams (e.g., HMS DBMI), IT staff with explicit research support roles (e.g., FASRC), and more administrative support teams who field researcher requests (e.g., SEAS IT).
For each of the key recommendations, we will discuss methods and requirements for their implementation. We will also attempt to call out where financial investment may be required.
Documentation of existing services/vendors available to researchers should be published in central, easily accessible locations and referenced locally for ease of access.
We generally expect that this implementation can be achieved using current staffing levels. Most of the content for back end support will need to be created by HUIT, but collaboration with local Research Computing teams will be required to frame out researcher-facing service offerings.
We recommend that we provide researchers information in two ways:
These sources of information should cross-link so that only one location need be updated as services and offerings change.
The information at least needs to include:
Certain details relevant to researchers may include confidential information about vendor contracts and should therefore be HarvardKey-protected where necessary.
It is hoped that better communication of available services will attract researchers currently operating outside of University Cloud contracts to join in to central services, which will both better protect the University and also potentially lead to better volume discounts.
Implementation of this recommendation generally involves activities that reduce the amount of up-front work that researchers will need to take on to begin using the Cloud.
We generally expect that the creation of centralized account and tool provisioning can be achieved using current staffing levels, though it will require some refocusing of current staff. However, it is less clear whether local schools are appropriately staffed to support the researchers once they are onboarded (see 4.3).
Specific recommendations for HUIT action include:
Offerings produced under this recommendation will need to be designed to serve the largest number of research needs without overly-burdening existing teams. Hopefully, it will be possible to delegate certain functions such that distributed Research Computing groups could produce templates that could be integrated for larger use. It is also critically important that whatever is produced be perceived by researchers as something that assists them in their Cloud work, not something that gets in their way. If what is produced is not seen as being valuable by researchers, the effort put into it could be wasted.
Minimally, groups currently supporting research in the Cloud should be in regular communication, which will at least improve existing support levels. Action is already taking place in this direction. However, if Harvard is to truly leverage what Cloud computing brings to research (including more cost effective scaling and utilizing specialized services from Cloud providers), we recommend that the local teams that support on-premises research expand their portfolios to explicitly include supporting Cloud research (whether Cloud-native or hybrid), and that they work closely with HUIT to deliver those services. HUIT should also increase its Cloud Consulting service’s focus on research in the Cloud to better support those local Research Computing teams.
This implementation would require augmentation of existing school Research Computing teams and possibly the Cloud Consulting team, which will likely require additional financial investment. Cloud-focused teams are fully-occupied in their support of administrative Cloud computing, and Researched-focused teams are fully-occupied in their support of on-premises research services. In addition to investment in human resources, there will also need to be investment in regular training for interested researchers and for the local staff who support them.
The expansion of local Research Computing portfolios should provide:
HUIT Cloud Consulting should:
It is critically important that this effort be a partnership between HUIT and local Research Computing teams. HUIT can expand its services to provide broad horizontal support of Cloud research, but local Research Computing teams would still be required to provide vertical support.
One major area of concern is whether local Research Computing teams (especially the smaller ones) could reasonably expand their portfolios as described. There may be opportunities to leverage larger local IT teams to augment the capacity of smaller teams, and/or to create shared services or service infrastructures that would be available across Harvard and be leveraged by these smaller teams. This could also help with the problem of scale, where some research projects may require significantly more support than others.
The consequences of not expanding services to include support of research in the Cloud all derive from the fact that, even without that support, researchers are already going to the Cloud. The potential consequences of this include:
A presentation on the results of the Higher Ed survey can be found here.
Researchers are directly going to the Cloud for various reasons despite the availability of on-premises resources. Some of the documented reasons include:
Credits drive many researchers to the Cloud, but may not be a sustainable way to do research in perpetuity. Keeping tabs on credit volumes and credit programs is an area where assistance is already needed by some researchers, and there will likely be more of that in the future.
It should be noted that the three major Cloud providers are all competitors in a fast-moving field with a constantly developing ecosystem. Vendor lock-in in the Cloud space has long been a consideration for Administrative computing, but it an issue for researchers as well. Researchers who depend on vendor credits may want to be able to easily shift workloads from one-vendor to another, and (as with administrative computing) the more vendor-specific tools they use, the harder that will be. In addition, any workload that depends on credits needs to have a plan for how the research will operate after the credits run out, which may mean a plan for shifting the workload to a less expensive location.
Finally, as we consider the support for Level 4 research data in the Cloud, we will need to balance the need for convenience in putting compute and data close to each other with the security and privacy concerns of working with such data. When researchers find themselves driven to the Cloud because of a lack of ability to host Level 4 data in on-premises research spaces, we should also consider whether some of those use cases could also be filled by a de-identification service that is easy to use and available to researchers across the University.
The risks around Level 4 data in the administrative space tend to focus around the financial risks of penalties and/or payouts, and the reputational risk to the University. The research space, however, has some special areas of concern:
This report does not specifically address the research needs of students, but such use cases could be taken into account, especially in the space of the account and tool provisioning detailed in Section 4.2.
Funding agencies like the NIH and the NSF have been encouraging the use of Cloud for researchers using their funding. During early phases of the NIH’s STRIDES program, it sounded as though the funding dollars might go directly from the NIH to the Cloud providers. This possibility raised concerns within Harvard that we might lose out on our ability to assess overhead Facilities and Administrative (F&A) costs to the NIH funding if the funding never hit Harvard’s books. While the STRIDES program did not end up distributing funding directly to the Cloud providers, it is important that Harvard continue to monitor the evolution of Cloud programs at funding agencies to make sure none of them head in the direction of funding Cloud providers directly. The ability to assess F&A costs to grants is a critical funding source for the support of Research Computing generally at the University.
It is difficult to track down total value of vendor credits and how many of those credits are distributed for research activity in particular. AWS has informed us that, in CY2020, Harvard consumed $516k in credits, $250k of which can be attributed to Research and Machine Learning credits. Google has not provided us a similar analysis, but the billing console suggests that in CY2020, Harvard received $931k in “promotions” that went to HMS (VirtualFlow project) and HSPH (Lin Lab).