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The five key steps underpinning AI & Machine Learning powered data center operations - and the specific benefits that you can expect to unlock by following this approach.
AI and machine learning will change the game for data center optimization, but if operations teams are to take full advantage of its potential, then it’s important that they take a structured approach to its deployment. At EkkoSense we recommend a five-step approach:
1. Gather accurate cooling, power, and space data at a highly granular level – this allows you to observe how your data center is performing in real-time. The illustrations used in this series of blogs represent a room that would produce over 100,000 new data points each day – measuring what’s happening at the cooling units, rack temperatures, what the UPS is doing, what power is being produced... and then correlates all that data in real-time. And with the availability of the latest ultra-low-cost wireless sensors, there’s really no excuse not to do this in 2022.
2. Make it easy to visualize complex data easily and quickly – as humans we’re simply not good at staring at complex spreadsheets and trying to extrapolate what they are telling us. What we need is a new way to understand the relationships between all those data points, understand the Zones of Influence, and learn what impacts what. Thermally you want to see those greens and light blues, not the dark blues and reds. By creating comprehensive 3D digital twin visualizations, it’s a lot easier for data center teams to monitor and interpret this information – making it much easier to see what’s happening across your estate, highlighting potential anomalies and displaying suggested airflow and cooling improvements.
3. Apply machine learning and AI analytics to provide actionable insights – augmenting measured datasets with machine learning algorithms to provide data center teams with easy-to-understand insights to support real-time optimization decisions, backed by data. By applying machine learning and AI to the operations of a data center to address areas such as cooling optimization and airflow management – these technologies can be applied to deliver significant results. AI and machine learning changes the game, taking all those complex data sets and crunching the numbers, doing in seconds what people would take weeks to attempt and most likely fail to achieve. With AI in place, you benefit from fully correlated real-time data that’s presented in a distinctive, actionable way.
4. Ensure delivery with actionable recommendations for human auditability – rather than rely on unwieldy automation solutions, EkkoSense advocates a light-touch approach to data center infrastructure management, with operations teams supported by AI-powered, actionable recommendations for greater human auditability. Operators still maintain control over decisions, recognizing that often they will have insights that simply weren’t available within the data sets. And because optimization recommendations are presented each time for human auditability, data center teams are always on hand to ensure that any changes are delivering the expected results.
5. Deploy an ongoing continuous optimization approach - giving data center staff the capability for continuous optimization, while supporting them in keeping pace with their ever-changing critical facilities. You cannot optimize periodically and expect to stay in sync. Drift is natural, because regardless of how static you believe your environment to be, change is always occurring. The machine learning algorithm is persistently monitoring and analyzing your environment. It is always looking for ways to improve the operation of the environment, allowing you to continually improve the way you operate the facility.
Follow these steps and you’ll have an AI and machine learning-powered, software-driven optimization approach that unlocks significant benefits for data center operations. EkkoSoft Critical’s easy-to-understand insights and recommendations are proven to deliver hyper-efficiencies within your critical infrastructure, with benefits including:
· Reducing cooling energy consumption by an average of 30%
· Unlocking up to 60% stranded cooling capacity
· Removing thermal and power risks, enabling 100% ASHRAE thermal compliance
· Providing complete data center operational visibility in real-time
· Empowering your operations teams to make informed decisions, backed by data and with real-time visibility to the impact of those changes.
· Clear data center energy monitoring and savings to help reduce your carbon footprint
· All with a typical ROI of < 12 months – and at a fraction of the cost of more expensive and complex legacy DCIM or CFD systems
This is the final article of five in my series. If you’ve missed them, you can access the previous four here. Want to find out more? Get in touch with me for a 30-minute demo to experience how our AI-powered approach can take your data center optimization to the next level. Download our machine learning and AI white paper here, or see how AI and machine learning are changing the game for data center operators in this video.