Some thoughts informing a new strategy for an e-Science commons. I’d really appreciate some input and criticism.

Thoughts on Strategy for an e-Infrastructure Commons

I’ve been tasked with writing a strategy for “SAGrid” in the context of the National Integrated Cyberinfrastructure System. While a mission statement, goals and strategy originally existed for SAGrid, back when it actually was a grid, things have evolved since we started this adventure in 2009. Since I’ve been so personally involved in the project, it’s hard to extricate myself from the narrative, which is why this is being published on my personal blog rather than in some official document. If you have strong feelings, please don’t hesitate to comment below and hey, maybe you’d like to help me write this strategy ?


Apart from the many technological (r)evolutions that we’ve witnessed during the last few years, there has been one major socialogical shift in the communities of scientists - the shift towards Openness. Open as in :

I’m not learned enough personally to argue (at least not with the data to back up claims) that “Science = Openness”, and certainly there are domains (pharma, duh) where secrecy is paramount. But let’s take a step back and talk not of how things are but how we think they should be. It’s hard to argue the case that a publicly-funded research infrastructure as cross-cutting as e-Infrastructure should be closed. What we should keep foremost in our minds that we are talking about the development of the bedrock of 21st century science…

The Commons

SAGrid (and subsequently the Africa-Arabia Regional Operations Centre was founded on the principle of collective action1 - we created a federation of human, electronic and physical resources that belonged to no single institute, but were shared amongst all, and coordinated by a third-party. Sounded great, and if it had been actually implemented this way, we may have seen far better success, but what actually happened was a sort of reluctant “ceding of territory” by the participating institutes to this coordinating third party (the CSIR in this case), which many people then came to believe was “the grid”. This put it at odds with other projects, institutes and services, instead of allowing it to become a catalyst for the sharing of resources and scaling of activities. This is, in my opinion, a travesty2 and something I’d kinda like to help fix.

There has been a lot said about “The Commons” - there are the Creative Commons, and the Public Domain; there’s even a Creative Commons for Science, and there’s an intensive movement for making a scholarly commons, by opening access to scholarly communications of all kinds. However, we still haven’t made the case well for a commons of Cyberinfrastructure3. Everybody still wants to do everything themselves, when it comes to building computational and data infrastructure. The reasons are manifold… Perhaps because “Nobody does it better” (than themselves); perhaps because they’re scared that “sharing = ceding”; perhaps just because the interfaces were obtuse and unnatural. The grid was not supposed to serve large communities with established structures, but to provide a framework to allow access to all researchers, irrespective of geographic location or institutional affiliation. I’m willing to take the responsibility for most of this failure4, but only because those who were supposed to take the responsibility (the representative Joint Research Unit) arguably did not. Perhaps the timing was wrong, perhaps the milieu unfavourable, perhaps…

Well, certainly all of the above is true, but I think the fundamental point of a Commons is :

You get out what you put in.

Have you tried rebooting the system

I think it’s fair to say that SAGrid did not become what I wanted. It can be useful to draw a line in sand, to define an end of a period, to say “le Roi est mort, vive le Roi !”. With the development of NICIS, we have a perfect opportunity to re-design the collaborative, open, participatory infrastructure that I had originally envisioned along with the founding members5.

Systems thinking for Cyberinfrastructure

The National Integrated Cyberinfrastructure System (NICIS) defines a framework for the creation of national cyberinfrastructure system. Taking shape after long consultation and consideration of the state of affairs, it makes provision for centralised funding and deployment of computing, data and network infrastructure, amongst other things. This acknowledges the wide variety of needs that are faced by scientific communities and individual researchers, as well as the scale of large projects which rely fundamentally on e-Infrastructure. However, it also recognises that there is a need for systems thinking in the development of this framework6.

The point at which researchers are no longer able to provide for themselves the tools which they need to successfully undertake research represents a phase change7 in the system of research - one at which it is more efficient to collaborate and exchange services, than it is to perform everything in a self-contained way. This point is seen over and again in various aspects of society, and thus many of the considerations of this document will be addressed at such “societal” issues of research. Technological advance will not be arrested or even decelerated in the forseeable future - quite to the contrary - but scientific research will be conducted (or at least directed) by collaborations of humans for the forseeable future. I propose that this principle should inform the strategy of the cross-cutting aspect of NICIS “formerly known as SAGrid.”8

Evolving the revolution

Production “service-grids” have had their day. The biggest one ever built9 showed the inherent limitations and spectacular capability of the paradigm. Production service grids had a lot of competition (or, shall we say, complementary support), particularly from volunteer service grids (SETI@Home, World Community Grid, etc) and other forms of distributed computing, but their defining characteristic was that they were decentralised. This is important.

As technology has evolved, instead of “dying”, they have adopted the evolutionary benefits of clouds - resource virtualisation, flexible infrastructure management, self-service, pay-per-use, etc. At the same time, research methodologies used on these infrastructures are also crossing boundaries and domains. Fifteen years ago, HPC and data infrastructure were considered necessary to very few research activities. Ten years ago, taking advantage of the momentum created essentially by big physics projects’ computing requirements these were adopted by other areas such as bioinformatics, as the boundary of what was computationally feasible was beaten back by technological advance. The rise of the network, especially in Sub-Saharan Africa, was a long-awaited revolution that promised to destroy distance10. Sticking with the the lustral theme, in 2010 ‘cloud computing’ was so vaguely defined that it begged ridicule when considered as a serious replacement for production service grids. In 2015, proposing the deployment of a static, isolated (albeit federated and shared) infrastructure would negate the capacity of networks to reduce the barriers to collaboration which impede scientific discovery and innovation.

What does the internet think of all this

In general, I’m wary of putting faith in the unwashed masses of the internet at large, but there is something to be said for general trends. Taking ‘interest in’ (ie, ‘searching for’) topics as a proxy for their uptake and relevance, we can get some idea of where people are focussing their efforts. Now, Google Trends only goes back to 2004, while the seminal work on Grid Computing was written in 199911, so we have to be careful of interpreting the trends. However a second edition12 was coincidentally released in 2004, so we might as well use that as a reference. Here’s how people have searched google for “HPC”, “Big Data”, “Grid Computing” and “Cloud Computing” since then13:

The searches for “grid computing” are making their way to extinction, while those for HPC, while on a general decline, are still quite voluminous. One conclusion we may draw is that grid computing has reached the level of maturity that people don’t need to search for it anymore, while HPC is still evolving fairly constantly. The “Cloud Computing” and “Big Data” trends are in full swing. Bear in mind that the data is from worldwide trends - and the shape of the cloud computing trend may look quite familiar.

The Gartner Hype Cycle for Cloud Computing 2012. Hey, we're all susceptible to Apophenia.

I invite the interested reader however to take a look at the various regional distinctions - the “cloud computing” trend kills the others in the Sub-Saharan Region14.

The Network won

Many claim that the rise of network capacity and fall in price of computing and data resources has led to a “democratisation” of science. What is meant is that there is a lower barrier to entry to research, since there are more resources available, to a wider range of researchers. However, this is not democracy, this is at best egalitariansim, and at worst demagogy. One of the unfortunate side effects of the rapid reduction in barriers to entry is that the sharing motive is undermined and there is a large temptation to “go it alone”. This might lead eager groups, projects, initiatives to quickly develop even sizeable resources, instead of following a slower adoption route on shared or mutualised resources, only to discover later that there is a need to share. At this point though, the damage is done, and re-building the trust necessary to share resources can quite long. We refer to this as the “erosion of the commons”.

Hey, what if we didn’t have to draw battle lines around what was “yours” and what was “ours” ? If decentralisation were a viable option for building e-Infrastructure, we wouldn’t have to. We could allow the network to play the aggregating and multiplying role it does so well, and avoid the erosion of a common platform for research and innovation. Easier said than done, of course - the limiting factor here, I submit, is the governing structure that enables a dynamic and sustainable decentralised e-Infrastructure. Trust is a fundamental aspect of this and is not something that can be simply wished into existence - even less bought. However, we have more than 5 years of local experience in building this trust. The experience of studying similar decentralised distributed computing infrastructures worldwide in the CHAIN-REDS also provides a good solid basis.

NICIS could indeed go a long way to providing a bedrock of trust, but more important, I think, is the aspect of constituency. I submit that a Commons could bring this about and improve things from a resource provider’s point of view.

So, your place or mine

Let’s take a look at how a Commons would improve things from the researchers’ perspective.

The pillars of cyberinfrastructure have been identified in South Africa as Data, HPC and Network. These pillars make particular sense from a national funding agency perspective, influencing development of centralised interventions. However, in the real world, it’s very hard to build something using only one pillar, be it a pillar of “techonlogy”, or an institutional pillar. The point is that research is conducted with judicious, sometimes ubiquitous usage of all of these technology pillars, and frequently across institutional boundaries. Researchers do not identify as “HPC” users or “Data” users - and certainly not as belonging to a particular institute - they are simply researchers, so funding their activities within the ambit of any of these “pillars” creates unnecessary barriers. While the pillars are useful for funding agencies to channel their commitments into significant hardware investments, a false dichotomy has been created between services which are in reality complementary. The separation of pillars, while necessary and useful to central funding agencies, thus creates tension and inefficiencies both in the technical community entrusted to build and operate them, as well as the scientific communities which come to rely on them. There are very good reasons for having centralised funding (in order to address issues at scale) as well as independent or institutional funding streams (to ensure that there is a multiplicity and diversity in research and resources), however as often occurs, some convergence in activities is almost inevitable. When this occurs, whether it is technological, methodological, or scientific convergence, a means should exist whereby experience and resources can be shared.

‘Government Housing’ vs ‘Community Projects’ - ensuring constituency-based participation

Ok, this bit is going to be controversial… bear with me, and remember that I’m trying to make an argument, in order to get to the facts, so feel free to comment (constructively :smile:) down below.

So, not all South Africans have equal access to e-Science resources and services. It is unrealistic to insist that all research universities will instate and host their own institutional HPC centres, let alone stand-alone e-Science Centres; this can only be effectively done in a certain environment and at a certain scale. However, we cannot accept such inequalities in our scientific communities, and efforts should be made to ensure access to quality services and performant resources irrespective of geographic location. This could be done by distributing resources, paid for by some central fund, to remote and disadvantaged communities; I refer to this as the “Government Housing” option - whereby a researcher at a disadvantage just has to wait patiently until the central bureaucracy disburses what it’s able to in order to respond to their need. There are obvious issues with this, foremost the there is lack of choice and limited resources.

“But certainly having hardware on-hand to work with is beneficial to both the technical and the scientific communities which are isolated by the Digital Divide ? Surely giving these people something, even if it’s second-hand equipment, is better than nothing !?”

  • You, shrieking in disblief.

Ok, maybe you didn’t quite shriek, but you were still quite incredulous, you have to admit. Anyway - to that, I counter just two words:


  • Me.

My simple analysis is this. First of all there is a power crisis in South Africa, which will not likely go away soon. Old kit is notoriously power inefficient, meaning that often donations of second-hand materiel, even if free of capital cost, are often a huge burden on the receiving institute. In some cases, these institutes may not even have adequate data centres to host the kit. If institutes are already straining to keep power consumption to a minimum, proposing to deliver power-hungry and inefficient computing resources to them is likely to exacerbate the situation.

Secondly, the pace at which technology is evolving means that the sites which have only access to second- or third-generation equipment will de-facto be second-rate citizens of the e-Science world, learning obsolete methods and technology while the rest steam ahead.

Now, there is certainly a lot that can be done with older equipment, and the turnover rate of cutting-edge infrastructure is indeed very high. However, these resources will only be efficient in a system which allows various workloads to be executed by the relevant resources. This is not possible in state where resources are disconnected, but - while not solved problem - can be done in a decentralised, connected system.

The world is flat

The conventional wisdom says that you conduct your cutting-edge, grand-challenge research on expensive Tier-1 resources, and everything else on the Tier-2 resources. However, this belies the power of the network to flatten the world and as far as resource deployment goes, in my opinion, piecemeal installations are a pretty bad idea. A relevant model, I suggest, is not a hierarchy of resources, but a complex-adaptive system of services. This is a much more realistic representation of a real e-Infrastructure, due to it’s changing, complex nature. The distribution of resources should be thus done in the context of a self-interacting system, rather than islands of kit. Now, the NICIS report clearly recognises that we have (and should have) a System of some kind - an Ecosystem, for example - but I think the critical issue is that it is a complex, dynamic system; one capable of interacting with itself, self-organising and capable of generating structures beyond simple hierarchy. In keeping with the analogy, this all depends on the boundary conditions and external constraints placed on the system.

If the external constraints promoted the natural tendency of the system to support itself, and inhibited the natural tendency of the system to disintegrate, it could do some really useful work. I explored this concept while in the context of the Africa-Arabia Regional Operations Centre last year in Nairobi - here’s a quick refresher :

If you had the time to go through that prezi, well done ! If not, long story short:

Allowing technical communities to re-organise and interact coherently with scientific communities can result in a productive environment for both. Neither a “Government Housing” project, nor a featureless, undirected pool of resources will make a productive e-Science Commons.

The Craftsperson and the Third Career

Finally, let’s discuss a different aspect of an e-Infrastructure Commons - that of the people who operate and develop it. In a service-based economy, two distinct parties exist - the service providers and service consumers. There are distinct relationships between these two parties (service demand and supply for example), however it is assumed that there is very little overlap in activities. We have a model of modern IT professionals, working in a service-provision department, interacting via pre-agreed SLA’s to provide services to professional researchers who select and consume them. However, given the cutting edge nature of these services, and the fact that they are operated within research environments, the reality is that there is often a great deal of overlap. Since there is such complexity in these platforms, at times there is no neat separation between research and research support staff. We have thus seen the emergence of a third career path, being neither researcher nor research support, and emergence of Research Software Engineers - craftspeople who work at the interface of a scientific domain, and the technologies which enable it. Innovation in this boundary between infrastructure, services, and science is highly creative, and difficult to fit into traditional institutional silos, or in our case cyberinfrastructure pillars. Whilst institutes in South Africa are starting to recognise this by the creation of e-Science Centres15 to employ the Research Software Engineers and Craftspeople, this trend has shown great payoff abroad16.

In immediate terms, we consider that identifying and developing capacity in this new career path consists in identifying relevant, transferable skills. This is quite often conflated with the “DevOps” paradigm, where there is better empathy and collaboration between those operating infrastructures and those developing it; indeed, where they often are one and the same team.

DevOps, Software-Defined Infrastructure and transferrable skills

One of the aspects to emerge from the cloud computing paradigm is that hardware and services are being presented to the user in ever-more abstract ways. Virtualisation and abstraction are expressed in any number of computer languages, and for a modern systems expert, a fluency in these languages is essential. At the same time, many of the tools and methodologies usually reserved for the analytic and scientific domains (software engineering, quality control, reproducible methods, visualisation, etc) are being adopted by infrastructure operators. This cross-over is part of what is meant by the new “DevOps” paradigm. The rise of this paradigm has led to what we might term “Software-defined infrastructure”, where not only the configuration of services are described in computer languages, but also the means to achieve their desired state. This makes it possible to not only save and share entire e-Services, contingent only on access to the relevant hardware, but also to execute their configuration given a few relevant variables and initial conditions. Although I didn’t coin it17, it’s probably fair to state:

To a first approximation, Everything = Code

Ok - the actual hardware is not code, but as soon as you turn it on, it’s executing something. The Operating System is code. The hypervisor is code. The Private Cloud manager is code. The guest OS is code. The service running the application is code…

Things get even more ‘meta’ from there… For example, we wrote some Ansible roles which describe a state of services consisting of a Shibboleth IDP supported by an OpenLDAP backend containing identities of people who would like to use a service18. The authors of this service are not the ones operating the various instances of it, and it’s something that can be deployed by changing a few variables and at the push of a button.

Consider now the roles involved in this. Previously, there was The Expert19. All knowledge resided with this shadowy, reclusive individual and there was almost total isolation between them and their users. What we have now is a richer society of software developers, integration services, code reviewers, volunteer contributors… and the eventual operators and user. Now, the motivation for the developers to write generically-applicable code is dependent on having a wide deploy base; the overhead for developing integration services and code reviews similarly is only justifiable if there is a need for high-quality re-usable software, etc. In other words, this highly beneficial symbiotic relationship cannot happen in a vaccuum - it needs the right environment.

Again, this is what SAGrid was supposed to be, and what “the project formerly known as SAGrid” should be within NICIS.

Fork my infrastructure

Something astounding has happened in the last few years, arising from the convergence of the software development and IT operations commmunity, and the ability to virtualise resources: entire infrastructures can be “forked” from pre-existing ones. The rise of “social-coding” websites - most prominently Github has made writing and sharing code much easier and systematic, as well as providing an easy means of provenance, by tracking the network of forks and contributions of repositories. Not only does this dramatically reduce the time to deployment of new resources, services and indeed entire sites, but also introduces new variables into the e-Infrastructure ecosystem, and has significant implications for what training should look like. Leading into my discussion of automation below, a question arises:

Should we be hiring system administrators to operate complex services, or developing a software capability that allows massive automation ? Should we be hiring research scientists to run applications, or research software engineers to develop applications ?

On the one hand, you’ll be giving some people a job close to the hardware. On the other hand, the training material will be obsolete the moment it’s written. The market for HPC system administrators isn’t all that large compared to the industry IT sector, so in this case, the training will always have a limited audience and traction. On the other hand, if you’ve got a robust and quality Software-Defined Infrastructure, why even train the system administrators ? It would be a better investment to improve the software development capabilities of a specialised, (distributed) team and let automated testing, monitors, deployment and integration do the rest.

We, for one, welcome our new robot overlords

A last word on automation. The strategy of “the project formerly known as SAGrid” should explicitly take into account the automation trend. “Robots” refer to services which perform both menial and in some cases advanced tasks which were previously done “by-hand”. We’ve implemented this in automated continuous integration of scientific applications20, and are working on doing this for infrastructure services with Ansible, Puppet and Rundeck. What’s missing in our skillset at the moment is also what seems to be something of a common trend in Big Data - Artificial Intelligence. Developing a deep monitoring and reporting system, and developing appropropriate responses to events is a realistic goal which is already being done by companies with far larger infrastructures and tighter constraints than ours21.

Doing Research on the Research Infrastructure

Many of the areas of development touched on require actual research in their field. The prospect of developing research infrastructure that is both friendly and to the communities that it serves, as well as conducive to inward-looking research that improves and extends it is very appealing. There is a very wide range of topics in e-Science which could immediately be tackled - reproducible research workflows, resilient computing, semantic enrichment of research data sets, machine data mining, multiscale middleware… the list is endless. The point, however, is that this research can only be conducted with access to an e-Infrastructure at scale. Taken together with the focus on Openness and the approximation that “Everything = code”, “the project formerly known as SAGrid” stands to provide a fertile environment for innovation, improving both itself and the communities which it serves. “Itself” here refers both to the pillars of cyberinfrastructure which it cuts across, as well as the wider constituency of resource providers.

Conclusions and future work

NICIS recognises that there is a need for a cross-cutting activity to enhance and fully enable researchers using cyberinfrastructure. In my view this strategy should rest, as SAGrid initially did, on the desire, needs and efforts of a committed community of contributors: universities, research laboratories and large research groups. By adopting a paradigm of constituency - shared ownership and community-developed services and tools, based on open standards - the system could be sustainable. Relevant directed interventions at scale by a central funding agency22 could help ensure that the development of a commons is more attractive than the development of individual, isolated systems. New tools and methodologies are speeding up the deployment and increasing the range of services that can be realistically offered. Enabling this acceleration is Open Source software, and the rise of DevOps culture which allows good collaborative software development methodologies to be applied to infrastructure services themselves. Recognising the importance of these hitherto “hidden” technical experts and allowing them to bridge the scientific and technical communities they serve can bring great benefit to both.

This pontificating can and should go on forever, however in the meantime we really do need a concrete strategy with mission, vision and objectives, in order to define projects that can be funded so that we can implement them. This will of course happen in a more reserved context, but the authors of this strategy should be the stakeholders themselves, not the implementing agency, so that a proper mandate is obtained. Suffice to say that with some strategic changes, we can transform a fairly dated production service grid that tangentially collaborated with other infrastructure initiatives into a fully-interoperable Open E-Science Commons, which is our ultimate goal.

Finally, lots of work needs to be done on funding models and interaction with the private sector. This has been explicitly avoided in this work, to keep things on track. A very good starting point will be the EGI Pay Per Use23, but it would be perhaps hasty to envision a fully market-based cyberinfrastructure in South Africa. I would reserve this until “v2.1”.

Before you complain that I’ve left out something take a look at the length of this article. Congrats, by the way - you made it to the end ! Yes, there is plenty still to write about and do. I look forward therefore to your commments and feedback.


References and Footnotes

  1. Perhaps it’s worth remembering that the very name of the Meraka Institute was supposed to evoke a “Common grazing ground”… 

  2. This is similar to the “Tragedy of the Commons”, although let’s not get too carried away with philosophical or market-based analogies. 

  3. Perhaps the closest yet that we have come is the Research Data Alliance 

  4. As long as I can take credit for the great successes we’ve had - but those are less interesting to us right now. 

  5. The founding members of the SAGrid JRU were : The UCT-CERN Research Centre, UCT Information and Communication Technology Services, iThemba LABS, the University of the Free State Computer Services Department, Department of Information Technology, University of the North­West, Department of Information Technology, University of Johannesburg, University of the Witwatersrand, Bioinformatics research group. 

  6. Dr. Daniel Adams stated “System level planning is a key requirement;” at the ‘Enabling the Integration of Institutional, Regional and National Research Capacity: The “data glue” for Research and e-Infrastructures’ session of the RDA and global Data and Computing e-Infrastructure challenges meeting. 

  7. I submit that this is due to complexity as much as it is due to scale

  8. Sorry, I haven’t come up with a better name yet. However, I am torn between the grandiose-sounding “South African e-Infrastructure Commons” and just not choosing a name and sticking, as great some great artists to, with just a symbol. 

  9. The Worldwide LHC Compute Grid is arguably the biggest and longest-living production service grid ever built. 

  10. One may argue that it is perhaps no coincidence tha the speedy deployment of afordable network infrastructure is tightly correlated with actual democratic revolutions in the region, in many cases. 

  11. “The Grid: Blueprint for a New Computing Infrastructure”, Morgan Kaufmann Publishers, 1999, Ian Foster, Carl Kesselman (Eds) 

  12. “The Grid 2: The Grid: Blueprint for a New Computing Infrastructure”, Elsevier series in grid computing, 2004, Foster, I. and Kesselman, C. (Eds) 

  13. Boy, there’s a lot to play with here, but that’s probably best kept in a separate post. 

  14. This is a “live” integration of the trend. Since it will change over time, I’ve put a snapshot of the graph at the time of writing at doi:10.6084/m9.figshare.1317292 

  15. See, for example the recently-constituted e-Research Centre at the Unversity of Cape Town 

  16. Good examples are the Oxford e-Reseach Centre, the Monash e-Research Centre and the Netherlands e-Science Centre 

  17. If anybody knows who did, please let me know! 

  18. This is described at length at 

  19. Also known as the BOFH 

  20. Most recently presented here 

  21. NetFlix’s Simian Army is a good example. 

  22. The EC FP7 and H2020 funding mechanisms have played this role well, and national funding from South Africa’s DST for example could play such a role at a smaller scale. 

  23. See also the EGI Pay-Per-Use final report