The data center underpins a storage, compute, and networking revolution that’s deepening connectivity across our world. Yet driving efficiency, reliability, and resiliency in your data center is not simply a matter of upgrades. It requires rethinking how data is stored, processed, and accessed to keep pace with evolving business models and shifting market landscapes.
Innovation to support this rethinking abounds, but can introduce new platforms, systems, and technologies that may challenge your staff’s level of familiarity. Compounding this are the numerous aspects of data center improvement, from responsiveness and availability to resource utilization and security. Whether choosing a guidepost or allocating funds, here are some thoughts to keep in mind as you approach four important data center concerns.
Gain flexibility by simplifying operations
Ensuring that new data science projects integrate smoothly into the data center, fulfilling all expectations for availability, security, and governance will make things easier for your teams. You should be able to innovate without having to fundamentally change data center management, as IT departments already face significant storage, compute, networking, and middleware challenges.
Your ideal infrastructure will include features designed to reduce the effort required from IT, such as:
- Ease of integration with existing systems
- Ability to support a hybrid or multicloud environment
- Accelerators for deployment of AI-ready storage, compute, and networking architecture
- Automation solutions for provisioning, patching, and other routine tasks
- Management tools that provide a unified view of all resources
Simplifying the monitoring and management of your data center will grant your organization more flexibility to address regulatory requirements, control costs, and create a foundation for reliable, scalable performance.
Ensure your data center is AI-ready (even if your business is not)
Tremendous hype around generative artificial intelligence (GenAI) is creating an insatiable demand for faster, more efficient data centers to power intelligent solutions. Not every organization considers itself “all in on AI.” Yet all need to hit goals, reduce operational expenses, and keep ops running—and that alone can require infusing AI into processes or building data center clusters to train large language models (LLMs) at scale.
To protect your data center investment, don’t underestimate the increasing role AI will play. Consider how your network will perform as it evolves to handle various AI use cases. Will your data center be able to take AI projects from the lab environment to production at scale? Can it address use cases ranging from light training up to multi-cluster, compute-heavy workloads?
Network growth in any form, whether added services or increased traffic, should not disrupt business. Make sure that modernizing or building new data centers doesn’t get in the way of those you already have and rely on to run machine learning, IoT, and other core processes. According to the 2024 Global Networking Trends Report, 61 percent of IT leaders plan to simplify data center network operations with an AI-native platform approach within the next two years.
Continuously fortify your culture of security to drive value
Data centers are becoming more distributed, with more locations and devices in the network increasing endpoints and potential attack surfaces. Especially as hybrid work has impacted where data resides, maintaining control becomes even more difficult. Critical features such as data encryption and firewalls are necessary, but do not offer enough protection on their own in the current threat environment.
Modern data centers demand a highly secure and agile network infrastructure that can follow workloads wherever they go. Ideal security solutions will offer full network visibility, including users, devices, applications, workloads, processes—and your data center. Traffic partitioning, especially multi-layered or microsegmentation, can help reduce the attack surface, and if a potential threat is detected, will enable you to contain the threat and keep it from moving across your data center.
Organizations committed to data protection should enforce consistent policies, use application permit listing, or adopt innovative solutions such as zero-trust spine-leaf fabrics, which ensure connectivity and strict controls at every endpoint. Your approach to security should not only provide protection, but also help you automate, drive efficiency, and adapt as the demands of cybersecurity evolve.
Align your data center roadmap to clear sustainability goals
Exacerbated by higher scaling and speed demands, the compute density of servers used to train LLMs is making AI the biggest data center disruptor since the public cloud. According to Epoch AI, the computational power required to train frontier AI models doubles in cost every nine months. Utilities that have historically planned out demand by a decade must now contend with the surge in speculative investment as organizations race to secure energy sources.
Keep a level head regarding the big picture. Understand that this demand growth is not only a result of the increased power consumption per rack and heat output that AI processes introduce, but also due to the exponential increase in innovative use cases for consuming data. This does not mean energy concerns are diminished. Instead, take steps to ensure that energy is central to every technology decision you make.
Focus on details and strategy. Businesses that succeed in this area tend to align their technology roadmaps to clear sustainability goals across the entire value chain. ClusterPower, for example, built the largest data center facility in Romania with sustainability in mind. The more components in your stack that are designed for optimal efficiency and can deliver power with the least amount of loss, the more solid a foundation you’ll have for data center sustainability.
Take advantage of switches that offer observability at scale with streaming telemetry and advanced analytics. Visibility of power consumption across IT infrastructure in data centers gives us insights to offer recommendations that can lower cost structure and increase efficiency. These range from rerouting traffic or implementing activity-based power management features to consolidating applications into services, reconfiguring design, and identifying opportunities to refurbish.
For the latest on data center infrastructure and energy management, check out our Insider Series webinar, You’re Ready for AI. Is your Data Center? You’ll gain practical information about how to select the solutions that are right for your organization, prepare your data center for volatility, and scale with greater flexibility.
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