Resources

Modern healthcare delivery is undergoing profound digital transformation. Critical functions, from maintaining comprehensive Electronic Health Records (EHR) and managing vast libraries of medical images via Picture Archiving and Communication Systems (PACS) to enabling remote patient consultations through telemedicine and leveraging Artificial Intelligence (AI) for diagnostics, are fundamentally dependent on a robust, highly available, and secure digital infrastructure. The sheer volume of medical data generated is increasing exponentially, placing unprecedented demands on the underlying IT systems. This reliance introduces unique and intense pressures on healthcare IT infrastructure. Data centers supporting healthcare operations must navigate a complex landscape defined by stringent regulatory compliance mandates, most notably the Health Insurance Portability and Accountability Act (HIPAA) and the Health Information Technology for Economic and Clinical Health (HITECH) Act, which govern the privacy and security of patient data. Simultaneously, these facilities must guarantee near-continuous availability for critical patient care systems, where even minutes of downtime can have serious consequences. Compounding these demands are escalating cybersecurity threats specifically targeting valuable Protected Health Information (PHI) and electronic PHI (ePHI). Furthermore, healthcare organizations face constant pressure to improve operational and energy efficiency to control rising costs, all while managing increasingly complex physical and virtual infrastructures, often spanning on-premises, colocation, and cloud environments.

The rapid growth and technological shifts within the data center industry present colocation providers with a complex set of interconnected challenges that span operational, financial, technical, and strategic domains. Successfully addressing these hurdles is essential for sustained success. Managing Capacity, Density, and Scalability: Accurately planning and managing data center capacity is becoming increasingly difficult. Forecasting demand, particularly with the volatile and often project-based nature of AI training workloads, presents significant uncertainty. Simultaneously, providers face pressure to maximize the utilization of existing space, especially in high-demand markets with record-low vacancy rates. A major technical challenge is accommodating the dramatic increase in rack power densities driven by AI and High-Performance Computing (HPC) workloads. Many existing facilities lack the power distribution and cooling capacity to handle densities moving towards 30kW, 50kW, or even higher per rack. Providers need infrastructure that is not only dense but also flexible enough to adapt to diverse and evolving client requirements for power, cooling, and network configurations. Optimizing Power and Cooling Efficiency: Power has become a critical constraint and cost factor. Securing sufficient, reliable power from utility grids, which are often strained, is a major hurdle for new developments and expansions. Furthermore, rising energy costs directly impact operational expenditure (OpEx) and profitability. Managing the immense heat generated by high-density server racks is a parallel challenge, necessitating investments in advanced cooling technologies, such as various forms of liquid cooling or highly optimized airflow management systems, to prevent equipment failure and maintain efficiency. Improving overall energy efficiency (often measured by PUE) remains a priority for cost reduction and sustainability, but achieving gains beyond basic measures requires sophisticated monitoring and control strategies.

The unique regulatory and operational pressures within the financial services industry place an exceptional burden on IT infrastructure management. Modern data centers are inherently complex ecosystems housing diverse components like servers, routers, switches, storage arrays, and power distribution units. The trend towards hybrid environments further complicates matters, distributing critical assets across potentially numerous physical locations including owned facilities, colocation sites, and edge deployments. Managing GRC effectively across this distributed and complex footprint demands robust data management and reporting capabilities specifically tailored to infrastructure. Meeting these diverse requirements hinges on the availability of accurate, timely, complete, and auditable data regarding the infrastructure GRC posture. This includes detailed information about every asset, its configuration, physical location, network and power connections, associated software and firmware, and its entire change history. However, achieving this level of data integrity is often hampered by fragmented tooling and persistent manual processes. Common challenges include incomplete asset information in Configuration Management Databases (CMDBs), limited visibility into cabling and interrelationships, lack of precise resource usage data (power, space, cooling), and change processes that "go dark" when moving between IT service management systems and the physical data center floor.

Asset Integrity Monitoring is a practice that focuses on achieving SLA commitments, ensuring equipment and data is secure, financial accountability, and tracking and reporting for regulatory compliance. Knowing what is in production and what equipment…

Managing data centers is more challenging than ever. Data Center managers demand operational efficiencies and uninterrupted availability of critical business applications while remaining flexible. How can data center operators achieve their management and operational goals…

Integrated Data Center Management (IDCM) is deep integration between data center critical facilities infrastructure, the resources (e.g., servers, switches, assets, etc.) within the data center, and the application workloads running there. IDCM’s most simplistic description would be the integration between Building Management Systems (BMS), also referred to as Building Automation Systems (BAS), DCIM solutions, and IT operations – yet the vision of IDCM is much more than that description captures.

Our compact guide explores the implications of the EU Energy Efficiency Directive (EED) for data centers, shedding light on the critical role it plays in promoting sustainable operations. Delve into the EED's vital metrics and learn how to effectively apply them to enhance your data center's environmental, economic, and social performance. Whether you're seeking regulatory compliance or aiming for sustainable transformations, this guide offers the insights you need.

One of the most stressful moments in managing data centers is realizing the status quo isn’t working. Perhaps the spreadsheets and other manual methods are falling further and further out of sync with the assets…

This paper describes a framework for deploying DCIM software. Each data center moves through different phases in managing their infrastructure, often starting with spreadsheets and diagrams, then moving to early stage DCIM and on to…

What is a Workload, and why is management of Workload Assets needed?

Nlyte can start with a CMDB’s Configuration Items: Connecting Nlyte to a CMDB allows you to set rooms and customer data, accurately representing a client’s environment. You can take that as the base representation of…

While DCIM is effective, IT organizations need to go a step further to fully integrate their data center operations into their IT service management (ITSM) processes. DCSM bridges this gap, enabling organizations to manage infrastructure,…

Workflow is essential for any organization implementing data center service management (DCSM). It orchestrates and effectively manages the many processes occurring in a modern data center. The Nlyte workflow engine helps ensure people within the data center can efficiently perform moves, additions, changes and decommissions that conform to the organization’s policies.

Nlyte Colocation: A DCIM Solution Custom-Made for Colocation Facilities.