New paradigms for Data Center Capacity Planning with the surge in cryptocurrency mining
The continued surge in crypto mining and blockchain technologies provides a host of new challenges for data center operators. The resource-intensive work of crypto mining creates more than just additional demand. It also operates with different priorities. In addition, like with any business relying on data centers, cost and reliability are a continuing concern.
Fortunately, the latest advances in machine learning give operators new tools to increase efficiency, lower costs, and keep downtime to a minimum. Machine learning is now involved in the planning, design, and workload management of modern data centers. Due to the unique needs of crypto mining, using machine learning for data center capacity planning will be essential in keeping these centers operating at peak efficiency while reducing costs and dealing with increasing energy prices.
The Unique Needs of Crypto Mining and Blockchain
Those unfamiliar with large-scale crypto mining may not be familiar with the different challenges and priorities unique to its data center needs. Mining servers require significantly more electricity than most servers for typical operations such as storage or eCommerce. These servers run 24/7 at full power, making it critical to account for significant demands for electricity. The heavy use of these mining servers also creates more heat than usual for a data center, meaning attention needs to be paid to consistent cooling systems to keep servers from overheating. In addition, servers dedicated to crypto mining have a shorter lifespan than typical. This means that planning must account for servers going offline for replacement.
Using Machine Learning for Data Center Capacity Planning
With all the factors to consider in traditional data centers and the unique demands of those focused on crypto mining, machine learning for data center capacity planning has become essential for leaders planning new construction and handling day-to-day center activities. With the vast amount of available data, algorithms can be created and implemented to plan for the right amount of capacity. Manual calculations and experience are no longer enough to determine the number of required servers, cooling capacity, and the requisite power to keep all of it running.
Using machine learning for data center capacity planning can ensure there is enough space, hardware, technical support, and power. At the same time, it can save data centers the cost of building and maintaining too much capacity. While excess capacity is usually better than not having enough, idle resources can cut into margins and profitability. The best solution is to have the necessary capacity and get the most efficient use of those resources.
Machine Learning is the Future of Data Center Capacity Planning
The latest trends show us that, by the end of this year, about 50% of IT assets within data centers will be able to run autonomously thanks to machine learning and AI. This will not only lead to better capacity planning and more efficient use of available resources, but it can also do this with little to no input from operators. With machine learning, system usage can be optimized continually 24 hours a day, only needing assistance when there is the need for physical assistance like replacing hardware.
This continual monitoring, assessing, forecasting, and optimization will be crucial to the profitability of data centers, especially those in the power-hungry crypto mining space. With the price of energy continuing to rise, autonomous machine learning can constantly be searching for ways to reduce energy consumption. By making the most efficient use of hardware and controlling temperatures through a more intelligent approach to cooling, machine learning can reduce energy costs and improve the bottom line.
While machine learning for data center capacity planning will be critical for the future of all data centers, in the short term, it will be especially relevant in the world of crypto and blockchain. Individuals, business leaders, and governments are already concerned about the massive amount of power being allocated for these particular data centers. Demonstrating greater efficiency through machine learning that leads to reduced power usage will likely relieve some concern as more power grids slowly add more green energy capacity. Also, as the cryptocurrency market remains volatile, reducing data processing costs will be good news for those mining at scale.
