How data center 3D visualization and AI-powered analytics makes it so much easier for teams to support instant optimization decisions
Traditional data center monitoring provides visibility and alerting but lacks the ability to provide the intelligence necessary to optimize the operation. As a result, you learn about issues after they occur, giving you very little time to react. AI-powered software doesn’t just show you what happens, but also why, allowing you to make informed decisions on how to resolve issues. And, by introducing powerful algorithms that correlate the relationship between the critical infrastructure and IT load, you can materially reduce the rate of occurrence through persistent optimization. The software will observe changes in the environment in real-time and will often inform you that a failure is going to occur before it does.
While we have established that the only reliable way for data center teams to troubleshoot and optimize data center performance is to gather massive amounts of data from right across the facility, it also introduces a potential challenge in terms of the sheer volume of real-time data that is being collected.
Operators have neither the time nor the expertise to interpret, calculate and act on thousands if not millions of data points in a timely manner and on a sustained basis. That’s why at EkkoSense we focus on making it as easy as possible for data center operations teams to gather and visualize cooling, power and space data at a granular level. We bring together a unique machine learning powered SaaS platform, low-cost Internet of Things sensors and Doctorate-level thermal skills to facilitate the crunching of multiple complex M&E datasets to help operations teams support instant optimization decisions, backed by data.
The result is a 3D visualization and analytics platform – EkkoSoft Critical – that’s particularly easy to use and understand. Operators can visualize airflow management improvements, manage complex capacity decisions, and quickly highlight any worrying trends in cooling performance. So instead of the blinded view provided by most infrastructure management systems, you actually get to see what’s happening across your data center floors in real-time.
You might not initially like what you see. Red racks mean the temperature is too hot. That’s risk. That’s problems. That impacts the equipment because heat is the enemy of electronics.
When the internal sensors within servers detect too much heat, they will fight back. They will spin up their internal fans to try to reject the heat. They will start turning off services to lower energy consumption to try to lower the heat being created. This risks both the serviceable life of the server hardware, and negatively impacts the performance of the servers and their ability to meet business needs.
Blue racks mean that they are being overcooled. If it’s too cold, you’re adding humidity to the mix. That’s water, and water and electronics don’t mix. Excess humid air running across the units to cool them risks shortening the serviceable life of the servers. However, the good news is that now you’ve got visibility, you can start doing something about it.
The path to recovery starts with understanding what’s happening and acknowledging that there are thermal issues that need resolving. It’s here that machine learning and AI can change the game for data center teams. Combining the power of artificial intelligence with real-time data from a fully-monitored room enables the creation of a digital twin of your data center – one that not only visually represents your current cooling, power, and thermal conditions, but that also provides tangible recommendations for optimization. This level of decision support can help operations teams take things to the next level, as the EkkoSoft Critical software will also recognize when changes have been made and even refresh the digital twin to reflect updates in real-time.
Powerful correlation engines learn how your data center is operating, why it operates that way, and shows what can be done to improve things. EkkoSoft Critical is able to analyze multiple complex data sets simply and quickly and display it in a 3D environment, empowering data center operators with a real-time view into the operations performance. Our unique Cooling Advisor module also provides operators with specific instruction sets on actions they can take to optimize the environment and reduce risk – while still leaving ultimate determination and control with the operator. This ensures that control and accountability stays with the operator, while removing guesswork from the decisions with results being visible in real-time. This enables those operators to learn and better understand the operation.
Once initial optimization is complete, our AI and machine learning algorithms continue to monitor and analyze the environment. This enables ongoing optimization, with the system persistently looking at ways to improve the environment, while also analyzing the impacts of any changes that have been made. The result is a proven and safe process that’s based on thousands of real-time sensors and expert spatial analysis.
This is the fourth in my series of articles on AI. The first three articles look at why most data center operators are still in the dark, how capturing critical data at a granular level opens up the potential for AI-based optimization, and how 3D visualization and AI-powered analytics make things much easier for data center teams. You can access them here. In my final article I will detail the five key steps underpinning AI & Machine Learning powered data center operations. In the meantime, please download EkkoSense’s machine learning and AI white paper here or get in touch for a free demonstration of the power of EkkoSoft Critical AI.
