Will Google DeepMind Artificial Intelligence Transform Data Center Infrastructure Management (DCIM)?
When it comes to hyper-scale data centers and countless servers, storage and network infrastructure management who knows more about site performance and reliability than Google! But just like other hyperscale and enterprise data center owners and operators, Google is plagued by huge data center energy costs that can add to operational expenditure and thereby reduce operating margins for data center operators.
Data Center Infrastructure Management (DCIM) emerged as a software category focused on providing data centers the ability to monitor power and environmental conditions beyond the rack level to cover data center aisles and overall facility. It helps data centers to implement optimum cooling and reduce downtime by offering real-time alerts. DCIM software help in managing the Power Usage Effectiveness (PUE) of data centers which is a metric used to determine the energy efficiency of a data center and is the ratio of total amount of energy used by a data center facility to the energy delivered to computing equipment – with overall efficiency improving as the PUE value decreases and gets closer to 1. DCIM offerings offer PUE management dashboards as a measure to improve energy efficiency in the data center facility. But PUE is only part of the story.
- The equipment, how we operate that equipment, and the environment interact with each other in complex, nonlinear ways. Traditional formula-based engineering and human intuition often do not capture these interactions.
- The system cannot adapt quickly to internal or external changes (like the weather). This is because we cannot come up with rules and heuristics for every operating scenario.
- Each data center has a unique architecture and environment. A custom-tuned model for one system may not be applicable to another. Therefore, a general intelligence framework is needed to understand the data centre’s interactions.
In order to solve the above challenges, researchers at Google’s DeepMind group have been applying DeepMind’s machine learning to Google data centers and have managed to reduce the amount of energy by up to 40 percent. The implications are significant for Google’s data centers that are already running on renewable energy, given its potential to greatly improve energy efficiency and reduce emissions overall. With DeepMind’s algorithms, Google can help deal with climate change impacting its renewable energy data centers. As per the blog, Google has invested heavily in renewable energy and has already seen significant benefits in energy savings.
Reducing energy usage has been a major focus for us over the past 10 years: we have built our own super-efficient servers at Google, invented more efficient ways to cool our data centres and invested heavily in green energy sources, with the goal of being powered 100 percent by renewable energy. Compared to five years ago, we now get around 3.5 times the computing power out of the same amount of energy, and we continue to make many improvements each year.
With Google’s DeepMind technology, the energy savings and operational efficiencies will go multiple steps further. Companies adopting Google’s Infrastructure as a Service (IaaS) or Platform as a Service (PaaS) on Google Compute Engine (GCE) or Google App Engine (GAE) cloud will also also benefit and report improvement in their enterprise energy efficiency.
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