TL;DR
- AI workloads are driving unprecedented increases in data center power density, cooling complexity, and operational risk.
- Traditional, legacy DCIM platforms struggle to keep pace with the speed and scale required by modern AI-driven environments.
- Effective DCIM must provide real-time visibility across both white space (IT) and gray space (facility infrastructure).
- Modius OpenData delivers unified, vendor-agnostic DCIM through a single code base and modular architecture that scales as infrastructure evolves.
- By consolidating telemetry, IT assets, power, cooling, and security data into one platform, OpenData enables faster decision-making, improved resiliency, and future-ready operations for AI-era data centers.
The technology and infrastructure that underpin the data center are evolving rapidly. The need for comprehensive management systems that can adapt and scale at the same rate remains constant.
Dynamic and energy-hungry: the nature of AI workloads has forced the industry to reimagine each and every aspect of the data center. From power and cooling to design and construction, facilities are taking on a brand new shape inside and out.
Technology and infrastructure upgrades that once took place over a number of years are emerging at pace, with no sign of slowing down. Today, keeping up with the rate of change and remaining competitive demands detailed oversight and proactive monitoring of mission-critical applications, in all their forms.
That’s where data center infrastructure management (DCIM) comes in. An effective DCIM solution brings together data from across the data center under a single, centralized platform, in order to streamline operational management and proactively identify potential issues before they occur.
The Modius DCIM solution, OpenData, is unique in its ability to monitor both the white and gray spaces of the data center, linking them within a singular overview. With security and scalability built in across 12 scalable modules, the platform seamlessly supports integration of new equipment and systems as they change over the lifetime of the facility.
Craig Compiano, CEO at Modius, explores how a comprehensive DCIM solution such as OpenData can provide the essential backbone for successful data center operations in today’s fast-moving, high-stakes landscape.
Bend, don’t break
Given that physical infrastructure is constantly evolving, it’s essential for DCIM to be able to adapt to physical changes within the data center, without needing to rethink how systems are connected each time an upgrade occurs.
“That’s why the OpenData platform is fully agnostic to individual manufacturers, makes and models, or to the kind of technology the underlying infrastructure represents,” explains Compiano. “They’re all simply points to be collected, normalized, and analyzed.”
Unlike many existing DCIM solutions or outdated legacy platforms that evolved by bringing together various products and multiple software programs under one architecture, OpenData is built on a single code base.
“That gives us more control and makes it easier to make changes,” explains Compiano. “When you have millions of points per minute being measured, analyzed, and then presented to the operator, decisions can only be implemented quickly and accurately if you have a single platform.”
The data management function of OpenData means the system can collect information at scale, across disparate devices as well as geographically distributed locations, and homogenize that scattered data into a single, structured database.
As well as adapting to physical infrastructure, Modius’ modular approach means that operators can customize the OpenData platform to suit specific business needs – with the ability to quickly and easily add modules, and scale up or down when required. This avoids over-engineering your solution or paying for capabilities you don’t need.
Compiano shares a useful analogy to illustrate the importance of a single code base: “If you imagine the alphabet from A to Z, with 24 letters between the two endpoints, if you have to step through every single letter, it’s going to take a few minutes. We want to take the time elapsed from A to Z down to near real time.”
If Z represents the IT load and the impact on the business, OpenData enables operators to see the consequence of any change at A, and its direct impact on Z, without trying to run through multiple disjointed databases housing D to G or K to Q, for instance, and without delay.
As the rapid adoption of AI continues, more and more data can be found at the front end, with an increased demand for lower latency between the initial point of measurement and the final interpretation of the data. In practice, that means more operational demand for the software systems that facilities rely on.
From head to toe
The rise of liquid and hybrid cooling systems to manage today’s high-density workloads is a vital shift. But increasingly power-dense racks, coupled with the introduction of liquid into the data center, have thrown up some new challenges.
“There’s a certain increased risk profile – partly because the IT assets are so much more expensive,” explains Compiano. “The time to failure is now measured in seconds, not minutes, to respond and avoid frying the servers, CPUs, or GPUs. It’s near instantaneous.”
OpenData effectively consolidates both the gray and white spaces, to automatically and seamlessly align supply and demand. The ability to join continuous telemetry data in near real-time with IT assets is a distinct advantage in the age of rising densities and increased power and cooling demands.
Establishing a holistic overview of the entire data center machine is fundamental to futureproofing. When the need to layer in new AI technologies arises, it’s essential to be able to match the telemetry data to the physical infrastructure efficiently and at scale.
Strength upon strength
With data centers at the heart of our digital lives, prioritizing safe and secure operations is more important than ever. Today, more and more critical data needs to be moved at pace from protected networks at the OT layer, to the IT layer to be analyzed, managed, and deployed.
“Security throughout the data transport layers to protect the ‘data in transit’ all become increasingly important to operators that are concerned about what we now view as critical infrastructure,” adds Compiano. “Right from a national level, people now look at data centers the same way they look at power plants and dams.”
OpenData was created with a modular architecture to ensure the security of that critical data transfer process at each and every level. It features encrypted channels to secure data transmission between devices and the platform; access controls to restrict entry to data and functionalities based on user roles and permissions; and X.509 certificates for authentication and secure communication.
“The security mandate has increased tremendously, and so we’ve applied measures at every level of the stack – each one tailored to that specific layer,” adds Compiano.
Powering the future
It’s no secret that the rise of AI will continue to drive up capacity, diversify data center infrastructure, and force new approaches to power and cooling. That means demand for software that can effectively and reliably manage each of those critical elements, whatever they may look like, will grow in situ.
“I think we’re going to see increasing complexity for operators,” states Compiano. “That’s going to drive more interfaces and higher levels of automation on the application side – with DCIM systems informing decision making thanks to near real-time data flow.”
A new generation of data centers with a fresh set of challenges and complexities driven by dynamic AI workloads is already here. The margin for error is shrinking, while demand for speed and accuracy increases. Modern facilities require future-ready DCIM solutions capable of acting as a strong yet flexible backbone to prop up operations as they develop and scale.
With holistic monitoring of the entire data center based on a single application that can seamlessly adapt to changes in both infrastructure and individual operator needs, Modius’ OpenData platform is well-equipped to meet the demands of today’s AI-ready facilities, and the complexities of tomorrow’s data centers and other critical facilities.
For AI-era data centers, visibility and speed are critical.
To see how Modius OpenData delivers real-time, unified DCIM across power, cooling, and IT infrastructure, visit modius.com/opendata to explore the platform and request a personalized demo.
Frequently Asked Questions
1. What is DCIM and why is it critical for AI‑era data centers?
Data Center Infrastructure Management (DCIM) software provides centralized visibility into power, cooling, IT assets, and physical infrastructure. In the AI era, where workloads are more dynamic and energy-intensive, DCIM is critical for maintaining uptime, optimizing efficiency, and responding to issues in near real time.
Modius OpenData addresses these challenges by unifying operational data across the entire facility, enabling faster, more informed decision-making as AI workloads scale.
2. How are AI workloads changing data center operations?
AI workloads are increasing rack density, power consumption, and cooling requirements while shrinking the margin for error during failures. Response times have shifted from minutes to seconds, making manual or fragmented monitoring approaches unsustainable.
Modius OpenData supports AI-driven environments by delivering near real-time telemetry across power, cooling, and IT systems, helping operators align supply and demand before disruptions occur.
3. How is Modius OpenData different from traditional DCIM platforms?
Many legacy DCIM solutions are built by stitching together multiple tools and software layers, which limits scalability and responsiveness. Modius OpenData is built on a single code base with a modular architecture and is fully vendor-agnostic.
This design enables seamless integration of new equipment, consistent data normalization, and faster insights across both white space and gray space infrastructure.
4. Why is unified visibility across white and gray space important?
White space (IT equipment) and gray space (facility infrastructure such as power and cooling) are deeply interdependent in modern data centers. Without unified visibility, operators struggle to understand how physical changes impact IT performance.
Modius OpenData links these environments within a single platform, allowing operators to see the immediate business impact of infrastructure changes and reduce operational risk.
5. How does DCIM support data center security and resilience?
As data centers are increasingly viewed as critical infrastructure, securing data in transit between OT and IT environments has become essential. Modern DCIM platforms must protect telemetry data while enabling rapid analysis and automation.
Modius OpenData incorporates security at every layer, including encrypted communications, role-based access controls, and certificate-based authentication, ensuring secure and resilient operations as data volume and complexity grow