With the ECO-Qube architecture, we are solving the missing link between IT and physical infrastructure. Today, each side - the data center facility with cooling systems & electrical infrastructure is optimized with the assumption of IT load being static. This can be witnessed by the ‘1’ in PUE, which assumes that every kW going to IT is static and can not be optimized, the only thing that can be optimized is the % of additional electricity used by the data center for cooling and providing redundancy. The same is true for the IT side. Due to virtualization, most IT applications are unaware of the physical infrastructure, and thus assume it is static (e.g. that the IT server is always on and that the cooling system is static).
Yet in terms of potential efficiency gains, there is plenty of opportunities. IT servers are rarely under full load, often operating at an average of 10-15% utilization rate. Most IT systems are over-provisioned or designed to capture peaks, which means they are underutilized most of the time. Combined with the common practice of turning off energy savings features, this created tremendous waste.
At the same time, cooling systems & data center infrastructure have an availability constraint imposed by the IT - it shall never be turned off. The only signal that the data center operations can optimize against is essentially the server or room temperature, which is not reported by the IT itself, but measured either in the room or near/around the server itself.
What is clearly missing between these two worlds - often referred to as the IT (information technology) and the OT (other technology) - is an interface. And with that interface, a way for the two sides to exchange their requirements, demand profiles and forecasts from their respective environments, enabling each side to perform optimizations to find an optimal balance in terms of energy use, other environmental impacts, availability and costs.
There are many constraints hindering the effective collaboration of these two environments (IT and OT).
The first one is that IT and OT run on different networks, and for good reason. The IT is often connected internet-accessible, exposing it to cybersecurity risks which are part of the business of IT.
OT on the other hand is not connected to the internet to avoid any possibility of a hostile takeover of the facility infrastructure, hacking or other intrusions.
Thus simply connecting the OT network to the IT network will likely have unintended consequences, exposing the facility itself to the internet (via the IT) and introducing new security risks, which in turn risks the availability that the OT is committed to delivering to the IT.
As in real life, when connecting both sides is difficult, it’s best to meet in a secure environment outside the existing environments. With ECO-Qube, we are introducing the idea of an Environmental Data Agent (EDA), a separate system that sits between IT and OT, isolating each of the networks from each other, while collecting the required information from each side to perform optimizations as well as pass-through signals & results from optimizations.
This is simply an information exchange, but is further expanded by enriching the data received from either side (e.g. adding CO2 emission factors to electricity data from the physical infrastructure or transforming computing resource consumption of the IT into electricity demands). It also enables the allocation of an individual server to a PDU or to a rack and therefore enables thermal optimizations and server-level control.
The EDA is designed as a standalone IT system running on Kubernetes. This makes it versatile in its deployment, it can run on dedicated Linux-based controller hardware (given it has at least two physical network interfaces) or it can run within the IT itself, creating multi-tenant capabilities, e.g. for co-location facilities in which many IT tenants rent space or compartments in the data center.
Existing DCIM systems may take the role of an Environmental Data Agent by implementing the public API specifications for the EDA. The most important aspect, of enabling widespread adoption, is to make the EDA consistent across any infrastructure. The IT community often runs applications in a variety of heterogeneous data centers - e.g. spanning across a local server room, to co-location facilities all the way to the Cloud.
In all these environments, if an EDA is available, it should ‘look’ and ‘talk’ the same, removing the need for IT to adapt the applications & infrastructure for each environment and thus reducing the barrier to actually implementing the EDA.