To optimize data center operations, a capacity plan must be developed. This process includes determining service level requirements and analyzing current capacity.
This analysis should be based on historic measurements combined with proper analytic methodology. Proper capacity planning avoids overprovisioning, idling resources, and waste. It also ensures that future processing requirements are met without compromising performance benchmarks.
Predictive analytics is a subset of data analytics that forecasts future outcomes based on historical information and advanced data science techniques. It allows organizations to reliably predict trends and behaviors milliseconds, days, or even years into the future.
Some predictive analytics models focus on timing, such as how sales fluctuate during different seasons or when a customer will cancel their subscription. Others use machine learning to identify patterns, such as how Netflix analyzes customers’ viewing histories to make recommendations.
Many other predictive analytics tools use regression and machine learning techniques, such as decision trees and neural networks, to identify underlying relationships in a dataset. They are employed in marketing, credit scoring and risk assessment, home lending, insurance, healthcare, and law enforcement. They’re also used in weather forecasting, creating video games, and translating speech to text.
In addition to predicting future capacity needs, DCIM tools can identify potential opportunities for improvement in data center infrastructure. This includes evaluating the ability of equipment racks to handle higher-density loads, determining how to optimize cooling, and identifying ways to reduce energy consumption.
With second-generation DCIM solutions, data center managers can track capacity down to the data and power port level. This granularity clues them into how much space is available for new IT hardware and also helps to avoid stranded power, where ports are allocated but not used.
Once capacity requirements are established, DCIM can facilitate change management and ensure that the changes necessary to achieve them are implemented. This can include changing hardware or reconfiguring the data center to accommodate additional equipment.
Savvy planners must accurately picture their current capacity to avoid wasting hardware. But they also need to plan for future needs.
DCIM software allows data center managers to track room-level capacity down to the power and data port level. This granular information enables planners to locate space for new equipment with ease.
Monitoring IT infrastructure components’ performance also helps them identify when a part is likely to fail. This reduces maintenance costs and minimizes downtime risk by allowing data centers to perform preventative maintenance only when needed.
Brown explains that next-generation DCIM solutions use data pooling and analytics to identify trends that might indicate a single point of failure. These tools also offer capacity planning guidance that helps data center technicians upgrade or replace aging equipment before they cause outages.
Managing data center hardware is crucial to optimal performance. Unlike spreadsheets and homegrown databases, DCIM software keeps tabs on devices at every stage, from deployment to decommissioning. This helps prevent inaccurate records and eliminates manual processes that lead to mistakes.
Monitoring data center infrastructure can reveal trends that help with capacity planning. For example, next-generation solutions pool data from multiple customers for benchmarking and offer data-based suggestions on improving infrastructure performance.
DCIM also helps with room-level capacity planning by identifying where additional equipment can be placed for optimum operational efficiency from a power, cooling, and network perspective. “What-if” models forecast the exact capacity impact of new projects, and automated workflows reduce human error. In addition, power failure simulations can highlight out-of-compliance conditions that require immediate attention.
A DCIM solution aims to help data center operators perform productive operations while optimizing performance and energy efficiency. This is possible thanks to the software’s ability to manage change, communicate data, and implement preventive maintenance.
For example, a data center with a DCIM system may monitor power consumption to identify underutilized resources, reducing overall energy costs. It can also use heat map monitoring to track environmental conditions to prevent overheating that could lead to hardware failure.
Lastly, DCIM solutions allow for centralized monitoring of devices from multiple vendors, including their configuration and status. This information can then be used to minimize the risk of power failure, security infringements, and other issues that would impact productivity or cause downtime. A good DCIM suite will also offer alarm management and generate reports that can be triggered manually or automatically.