The multidimensional strategy enterprises need for AI and cloud workloads
Lost among the hype of the AI tools and the cloud revolution, one critical question is being overlooked: how many dimensions can your storage system scale?
Most enterprise storage systems are designed to scale in at most two key dimensions — capacity (how much data can be stored) and performance (how quickly data can be accessed). Driven by the complex, dynamic and unpredictable nature of AI workloads and cloud-native applications, there’s been a dramatic shift in the demands placed on storage infrastructure. Storage systems built for an earlier era are now being stretched and strained in ways their designers could never have anticipated. These unprecedented demands can’t be met by simply adding sheer capacity or raw performance.
What does this mean for your organization? To keep pace with emerging workloads and unknown future requirements, your storage infrastructure must scale — without tradeoffs — in any dimension that might be conceivably required.
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What is “multidimensional scaling” in data storage?
We’ve observed an uptick in customers who’ve come to us after running into one or more limitations in their outdated, inflexible storage infrastructure. This experience has helped us identify ten distinct dimensions that a storage system must be able to seamlessly scale in order to adapt to whatever the future might throw at it:
- Capacity
- Storage compute
- Applications
- Metadata
- S3 objects
- S3 buckets
- S3 authentications per second
- Throughput
- Objects per second
- Systems management
The ability to scale across these ten dimensions can be referred to as multidimensional scaling.
Future-ready storage: three ways multidimensional scaling powers business growth Technical explanations of each of the ten dimensions can be found in our whitepaper. Instead, let’s explore a few concrete examples of how multidimensional scaling can save your organization time, money, and headaches.
1. Have the flexibility to handle any future demand
The pace of technological change makes it nearly impossible to predict future storage requirements. Workloads that barely existed five years ago — like generative AI and real-time analytics — now dominate IT management discussions. Businesses that commit to rigid storage architectures risk being unprepared for what comes next.
Multidimensional scaling equips organizations with the flexibility to adapt to evolving requirements. Need to onboard a new AI data pipeline with microsecond latencies? Scaling access speeds ensures the infrastructure is ready. Launching a cloud-native application that spans geographies? Scaling authentication requests allows for secure, seamless global access.
This adaptability not only prevents expensive data migration but also empowers businesses to innovate without being constrained by their storage infrastructure.
2. Eliminate storage silos for seamless operations
Data silos have long been the bane of IT teams. They fragment workflows, increase costs, and make it nearly impossible to gain a unified view of your data. With multidimensional scaling, businesses can consolidate their cloud storage into a single, unified platform that handles diverse workloads — from massive AI datasets to high-frequency transactional data.
For example, scalable throughput ensures high-definition video streaming platforms can deliver seamless content playback to millions of users without requiring separate systems for ingesting and delivering media. Meanwhile, scaling the number of supported applications means businesses can run multiple workloads — from data analytics to machine learning — on a single storage solution without bottlenecks. The result? A unified system that reduces complexity and operational overhead.
3. Minimize downtime through predictable scaling
Unplanned downtime is the enemy of productivity and customer satisfaction. Traditional storage systems, which often require manual intervention to expand capacity or support increased traffic, introduce risk every time they hit a limit. Multidimensional scaling sidesteps this issue by ensuring storage systems can grow seamlessly in all directions — whether it’s handling higher transaction rates, supporting more simultaneous users, or accommodating ever-growing datasets.
For example, consider an ecommerce platform during a peak shopping event like Black Friday. With the ability to scale in transactions per second, the platform avoids crippling bottlenecks, ensuring smooth and responsive experiences for millions of shoppers. Likewise, metadata scaling supports the explosion of individual product entries and customer profiles without degrading performance. By adopting a solution designed for such scenarios, businesses can keep operations running smoothly even under extreme demand.
The future of storage is multidimensional: Is your system ready to scale?
Storage may not always be in the spotlight, but it’s the foundation of a winning IT strategy. The ability to scale across all critical dimensions turns storage from a reactive, operational necessity into a powerful driver of growth. By eliminating silos, minimizing downtime, and future-proofing against uncertainty, businesses can unlock new opportunities and avoid the pitfalls of a rigid infrastructure.
The demands of AI, cloud computing, and media-rich workloads are accelerating — your storage must keep up. The organizations that adopt multidimensional scaling today will be the ones best equipped to thrive tomorrow and benefit from long-term sustainability.
So, how many dimensions can your storage system scale?
If you don’t know the answer, it’s time to find out.
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Lost among the hype of the AI tools and the cloud revolution, one critical question is being overlooked: how many dimensions can your storage system scale? Most enterprise storage systems are designed to scale in at most two key dimensions — capacity (how much data can be stored) and performance…
