So, I’ve been dwelling on data center optimization for the last few months. It’s a bit of a challenge – how do you optimize something that is expected to consume mass quantities of energy? Our needs have been a bit different from the largest data centers – those of Facebook, Google, Apple, Microsoft – but can we leverage some of the innovations that they have brought to the table in the small enterprise data center?
Another thing adding complexity to our environment – we moved the ownership of the data center from IT over to Facilities and formed a new team responsible for data center health. In essence, we’ve changed roles from an IT group to a Co-Location provider. This has changed the perspective from which I look at the data center.
Let’s start with the current challenges:
- Currently, we have little to no power monitoring in place. We have little data being collected that can be used to forecast the future. Current systems limit monitoring and data collection to IP connected CDUs (cabinet level power distribution units), UPS systems and incoming utility feeds. No systems are in place to monitor all the branch electrical circuits feeding the IT load, the cooling loads or general building electrical (lighting, office space).
- Disparate IT systems are in place. The initial foot print was multiple rack unit servers. Over time, we’ve increased the number of blade servers in use – 6 years ago we had a foot print of roughly 56 blades in four enclosures, today we have over 200 blades in 17 enclosures. Recently, we’ve installed a VCE VBLOCK solution as a proof of concept and I’m hearing rumblings of at least six more systems spread across our two primary sites. This poses a few challenges:
- Differing power density requirements and power connection requirements. Low density cabinets use single phase, 208 VAC, 30 amp power with NEMA L6-30 connectors, high density cabinets use 3-phase, 208 VAC, 60 amp power with IEC 60309 connectors. Storage and blade enclosures often use multiple pairs of circuits or may have specialized requirements (i.e., placement of multiple blade enclosures in a low density cabinet may trigger the installation of a 3-phase, 208 VAC, 30 amp circuit pair with NEMA L14-30 connectors in order to prevent overload).
- Space allocation contraints. Do you dedicate space exclusively to standalone servers and space exclusively to blade enclosures? Or do you commingle standalone servers and blade enclosures?
- Storage resources are physically segregated from computer resources within the data center. This has been done with expectations that future requirements will drive additional physical security for storage resources that will not apply to compute resources. Storage resources also require that space be allocated for future expansion so that downtime will not have to be incurred to expand storage frames.
- Currently, no aisle containment solution is in place. Both hot aisle and cold aisle containment are possible based on our design, but a decision needs to be made on which would be more effective and which would provide better results.
- Some top of rack equipment has a reversed airflow (exhausting hot air into the cold aisle).
- Limited blanking panels are in place. This causes more air mix between the hot and cold aisles than is acceptable and definitely impacts our ability to fully optimize the space. Fortunately, this is relatively inexpensive and quick to fix – just order and install more PlenaFill blanking panels.
- Time and staffing levels. While the data center has been operational for two years, IT staffing levels have prevented the implementation of blanking panels and other simple solutions.
- Budget. Budget constraints and lack of vision and understanding have kept necessary tools out of reach.
At current time, we lack the ability to truly determine our PUE (a very controversial metric, but at least somewhat useful). A rough calculation gives me a 3.2 PUE – highly inefficient. Obviously, we have a long way to go. Getting to a PUE of 2.0 would decrease our electrical utilization by 30% and our electrical costs by over $300,000/year.