By Bill Evanger
Once thought to be “nice to haves”, data center infrastructure management (DCIM) tools have become essential to data center operations. By monitoring, measuring, and managing data center resources, DCIM tools enable operators to both manage and optimize their data center infrastructure. Organizations that utilize DCIM system are generally better equipped to meet ever-increasing demand and achieve their environmental, social, and governance (ESG) targets.
Before DCIM emerged in the early 2000s, data center operators relied upon disparate tools to manage their facilities and IT equipment. Early DCIM tools combined some features of building management systems (BMSs), IT service management systems, electrical power management systems, and other tools to facilitate the operation of increasingly dense data centers. They captured performance data from racks, cooling equipment, and power distribution units, providing the insights needed to manage space effectively, ensure reliable cooling and keep a lid on energy costs.
Over time, DCIM solution expanded to include asset management, capacity management, and more. As DCIM matured, these functions were federated into stable platforms which could be integrated into the broader ITSM ecosystem and further reduce or streamline the disparate toolsets data center operators were still having to manage as stand-alone systems.
Centralized management is increasingly important with hybrid IT environments, edge computing, and remote data center operations. To meet these new demands, DCIM is evolving to provide increased visibility across the distributed IT environment and provide the intelligence needed for predictive analysis and faster troubleshooting.
The evolution of DCIM is being driven by several key trends. First is the emergence of cloud-based DCIM solutions. By their nature, cloud-based tools provide greater visibility than on-premises DCIM. Additionally, cloud-based DCIM collects data from all data centers and edge sites in a data lake and uses artificial intelligence (AI) and machine learning to transform that data into actionable insights.
Machine learning enables DCIM to determine what is “normal” and generate alerts on abnormal events. Data center operators can also become more proactive and less reactive, performing predictive maintenance based on big data analytics. This enables them to reduce costs and risks, increase efficiency and better allocate resources.
The convergence of IT and operational technology (OT) is further transforming DCIM. In the past, IT systems and building systems were managed in functional silos. Now that many OT systems are network-enabled, they can be managed alongside IT systems using the same platform. BMSs are also offering some DCIM features and the ability to share data with DCIM tools. These systems enable data center operators to better meet IT’s growing demands while also managing power and cooling constraints.
Platform integration continues to be a driving trend, with many data center operators looking to eliminate duplicate data entry tasks, as well as expand the use of DCIM data into areas such as their CMDB, Purchasing, and Fixed Asset platforms. Integration and interoperability will continue to play pivotal roles as DCIM further matures into a more service-optimization-oriented ecosystem.
Many organizations are adopting the latest Data center infrastructure management solutions as part of an overall effort to bring their data centers up-to-date. According to research firm IDC, the average data center is more than 10 years old. DCIM platforms enable operators to break down IT and OT silos and meet today’s efficiency mandates.
When evaluating DCIM tools, organizations should look for these key features:
ResearchAndMarkets.com expects the global DCIM market to see a compound annual growth rate of 16.36 percent through 2027. If you’re looking to implement DCIM or upgrade your existing platform, Rahi can help you select the right solution and integrate it into your data center operations.
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