Data Management Glossary
Capacity Planning
What is capacity planning?
Capacity planning is the estimation of space, hardware, software, and connection infrastructure resources that will be needed a period of time. In reference to the enterprise environment, there is a common concern over whether or not there will be enough resources in place to handle an increasing number of users or interactions. The purpose of capacity planning is to have enough resources available to meet the anticipated need, at the right time, without accumulating unused resources. The goal is to match the resource of availability to the forecasted need, in the most cost-efficient manner for maximum data storage cost savings.
True data capacity planning means being able to look into the future and estimate future IT needs and efficiently plan where data is stored and how it is managed based on the SLA of the data. Not only must you meet the future business needs of fast-growing unstructured data, you must also stay within the organization’s tight IT budgets. And, as organizations are looking to reduce operational costs with the cloud (see cloud cost optimization), deciding what data can migrate to the cloud, and how to leverage the cloud without disrupting existing file-based users and applications becomes critical.
Data storage never shrinks, it just relentlessly gets bigger. Regardless of industry, organization size, or “software-defined” ecosystem, it is a constant stress-inducing challenge to stay ahead of the storage consumption rate. That challenge is not made any easier considering that typically organizations waste a staggering amount of data storage capacity, much of which can be attributed to improper capacity management.
Are you making capacity planning decisions without insight?
Komprise enables you to intelligently plan storage capacity, offset additional purchase of expensive storage, and extend the life of your existing data storage by providing visibility across your storage with key analytics on how data is growing and being used, and interactive what-if analysis on the ROI of using different data management objectives. Komprise moves data based on your objectives to secondary storage, object storage or cloud storage, of your choice while providing a file gateway for users and applications to transparently access the data exactly as before.
With an analytics-first approach, Komprise provides visibility into how data is growing and being used across storage silos. Storage administrators and IT leaders no longer have to make storage capacity planning decisions without insight. With Komprise Intelligent Data Management, you’ll understand how much more storage will be needed, when and how to streamline purchases during planning.
Why is storage capacity planning even more important as storage media prices increase?
Rising storage media prices, particularly for flash and high-performance systems, make capacity planning a critical enterprise IT priority. Without visibility into data growth and usage patterns, organizations often over-provision expensive storage or accelerate refresh cycles unnecessarily. Effective capacity planning helps IT teams forecast growth, reduce waste, and ensure high-performance storage is reserved for active workloads while controlling infrastructure costs.
What role does unstructured data management play in storage capacity planning?
Unstructured data management provides the visibility and automation needed to plan storage capacity effectively. By analyzing file and object storage environments, IT operations and infrastructure organizations can identify inactive data, duplicate files, and growth trends across datasets. This insight enables IT teams to reclaim unused capacity, move cold data to lower-cost storage tiers, and forecast future storage needs more accurately.
Learn more about Komprise Storage Refresh Assessment.
How important is the right approach to data tiering when planning a storage refresh?
Data tiering is a key strategy when planning a storage refresh because it helps reduce the amount of data that must remain on expensive primary storage. By identifying inactive files and transparently moving them to lower-cost object or cloud storage, organizations can significantly shrink the footprint of high-performance systems. The right tiering approach preserves transparent file access while lowering storage costs and extending the lifespan of new infrastructure investments.
Learn more about Komprise Transparent Data Tiering.
What is storage capacity planning?
Storage capacity planning is the process of forecasting how much storage infrastructure an organization will need over a defined period, and ensuring those resources are available at the right time, at the right cost, and in the right location. Effective capacity planning balances current usage against projected growth to prevent both under-provisioning, which leads to unplanned purchases and operational disruption, and over-provisioning, which wastes capital on storage capacity that goes unused.
Capacity planning applies to all storage environments including NAS, SAN, object storage, and cloud. It encompasses not just raw capacity but also performance requirements, data access patterns, compliance obligations, and the total cost of ownership across the storage lifecycle. The goal is to make storage investment decisions based on actual data behavior rather than estimates, gut feel, or vendor refresh cycles.
The unstructured data growth challenge
Storage capacity planning has always been important, but the scale and pace of unstructured data growth has made it a critical, ongoing discipline rather than a periodic exercise. Unstructured data — documents, images, video, research files, medical imaging, sensor data, and NAS archives, now represents 80-90% of all enterprise data according to Gartner. It is growing at annual rates of 55-65%, and IDC projects that unstructured data volumes will triple between 2023 and 2026.
The challenge is not simply that there is more data. It is that most of it is cold. Industry research consistently shows that 60-70% of enterprise unstructured data has not been accessed in over 90 days, yet it occupies the same expensive primary storage as actively used files. Without visibility into what data exists, how old it is, who owns it, and how fast different parts of the environment are growing, capacity planning decisions are based on aggregate volume metrics that tell IT teams how much storage they have but not what to do about it.
Two trends are making this worse in 2025 and 2026.
- First, AI initiatives are increasing demand for high-performance primary storage to support active training datasets, inferencing workloads, and RAG pipelines.
- Second, flash and SSD prices are rising significantly, with enterprise SSD prices increasing 53-58% quarter-over-quarter in Q1 2026. The combination of exploding unstructured data volumes, rising storage media costs, and growing AI-driven demand for premium storage is creating a capacity planning crisis for many enterprise IT teams.
How storage vendors approach capacity planning
Most enterprise storage platforms include some level of built-in capacity monitoring and reporting. Here is how the major approaches compare:
- Storage-centric capacity planning tools from vendors including NetApp, Dell Technologies, and HPE provide capacity dashboards, utilization metrics, and growth trend reports within their own platforms. These tools are effective for monitoring within a single vendor ecosystem but have no visibility into capacity across other vendors or cloud environments. They report on how much storage is being consumed without answering the more important question of what is consuming it and whether that data should still be on primary storage at all.
- Cloud storage management tools from AWS, Microsoft Azure, and Google Cloud provide lifecycle policies and utilization analytics within their respective platforms. These are strong for cloud-native environments but create blind spots when the same organization also manages on-premises NAS.
- Storage area network and block storage tools address structured workloads and database performance but are largely irrelevant to the unstructured data capacity challenge, which lives in file and object environments.
The common limitation across all storage-centric tools is that they are descriptive rather than prescriptive. They tell you how full storage is getting. They do not tell you what should be moved, tiered, deleted, or right-placed to address the situation before a refresh is required.
Analytics-driven storage capacity planning with Komprise
Komprise Intelligent Data Management takes an analytics-first approach to storage capacity planning that is independent of any storage vendor and covers the full hybrid file and object storage estate in a single view.
Komprise Analysis scans all file and object data across multi-vendor NAS and cloud storage environments without agents or changes to infrastructure, building a comprehensive inventory of every file and share. From that inventory, Komprise Deep Analytics queries the Global Metadatabase using any combination of metadata criteria including file type, age, owner, access history, size, and custom tags to answer the precise questions that capacity planning requires: which data is cold and can be tiered, which data is growing fastest and in which departments, which shares are owned by departed employees, and what the projected storage consumption will be under different policy scenarios.
Komprise provides interactive what-if scenario modeling that shows IT teams exactly how much capacity they can reclaim under different tiering policies before committing to any action. A storage administrator can model the impact of tiering all files not accessed in 12 months, or files over a certain size owned by a specific department, and see the projected capacity savings and cost reduction in real time before running the policy.
When capacity action is needed, Komprise Intelligent Tiering moves cold data to lower-cost cloud or object storage using Transparent Move Technology, which stores data in its native format on open, standards-based object storage with no rehydration penalty and no vendor lock-in. Users continue accessing files from their original paths via Dynamic Links with no awareness that data has moved. Capacity is reclaimed from primary storage immediately and the organization avoids purchasing additional expensive flash or NAS storage.
For organizations facing a storage refresh decision, the Komprise Flash Stretch Assessment provides a customized pre-purchase analysis showing exactly how much primary storage capacity can be reclaimed through intelligent tiering, what the projected savings are across different cloud and object storage destinations, and how much of the refresh budget can be deferred or eliminated. At current market prices, Komprise has identified savings opportunities of $350,000 or more per petabyte of flash storage for organizations that right-place cold unstructured data before committing to new hardware.
Key benefits of Komprise for storage capacity planning
Visibility across all storage silos. Komprise provides a unified view of capacity utilization, data growth, file age, and access patterns across multi-vendor NAS and cloud environments without requiring separate tools for each platform.
Actionable insight, not just metrics. Deep Analytics precision queries identify exactly which data is cold, redundant, or misplaced, turning capacity reporting from a dashboard exercise into a data-driven action plan.
What-if scenario modeling. Interactive policy modeling shows the projected capacity impact of different tiering strategies before any data is moved, enabling IT teams to present defensible capacity plans to finance and executive stakeholders.
Non-disruptive capacity reclamation. Intelligent Tiering moves cold data off primary storage automatically and transparently, without disrupting users, applications, or workflows.
Storage-agnostic flexibility. Komprise works across any NAS, cloud, or object storage environment, so capacity plans are not constrained by a single vendor’s tools or ecosystem.
Chargeback and showback reporting. Komprise provides department-level visibility into storage consumption and costs, enabling IT teams to hold business units accountable for their data growth and justify capacity investment decisions to finance leadership.
AI workload readiness. By continuously right-placing cold data off primary storage, Komprise ensures that high-performance flash capacity is available for AI training, inferencing, and RAG workloads rather than being consumed by inactive files.
Capacity Planning FAQs
What is the difference between storage capacity planning and storage capacity management?
Capacity planning is the forward-looking process of forecasting future storage needs and deciding in advance what resources will be required. Capacity management is the ongoing operational practice of monitoring current utilization, identifying waste, and taking corrective action to keep consumption within planned bounds. The two are complementary. Effective capacity planning creates the baseline and the forecast. Effective capacity management executes the policies and maintains the plan over time. Komprise supports both by providing continuous visibility through the Global Metadatabase and automated policy enforcement through Smart Data Workflows, so capacity planning decisions translate directly into capacity management actions without manual intervention.
How does unstructured data growth make storage capacity planning harder than it used to be?
Traditional capacity planning assumed relatively predictable growth driven primarily by structured database expansion and known application storage requirements. Unstructured data growth is neither predictable nor evenly distributed. Different departments, projects, and applications generate data at wildly different rates, and the nature of the data (large media files, genomics datasets, imaging archives, research outputs, etc.) means that a single project can consume petabytes of capacity in months. Without file-level analytics that show which data is growing fastest, which is cold, and which is safe to tier or delete, storage teams are left making capacity decisions based on aggregate utilization trends that cannot distinguish between a fast-growing AI project that needs premium capacity and a department archive that has not been accessed in three years.
What role does cold data play in storage capacity planning?
Cold data is the single largest addressable opportunity in most enterprise storage capacity plans. If 60-70% of enterprise NAS capacity is occupied by data not accessed in over 90 days, then a significant portion of every storage refresh budget is being spent to maintain cold data on expensive primary storage rather than to support active workloads. Addressing cold data through Komprise Intelligent Tiering before a refresh decision is made can eliminate or significantly reduce the refresh requirement, and in many cases can defer a planned purchase by two to four years. The Komprise Flash Stretch Assessment quantifies this opportunity precisely for each organization’s specific environment.
How does Komprise capacity planning differ from what storage vendors provide?
Storage vendor capacity tools report utilization within their own platform. Komprise provides analytics across all platforms simultaneously, including on-premises NAS from multiple vendors, cloud object storage, and hybrid environments. More importantly, Komprise answers the question that storage vendor tools cannot: not just how full storage is getting, but what is in it, whether that data should be there, and what the quantified impact of right-placing it would be. This difference between descriptive and prescriptive capacity planning is what separates a storage refresh conversation from a storage optimization conversation.
How does AI infrastructure demand change storage capacity planning priorities?
AI training, inferencing, and RAG pipelines require fast, accessible storage for active datasets. When 60-70% of primary storage is occupied by cold unstructured data, AI teams compete with inactive files for the same premium capacity. This drives up the cost of AI infrastructure because organizations must purchase more high-performance storage than AI workloads actually need. Komprise addresses this by continuously right-placing cold data off primary storage, keeping it accessible via Dynamic Links and indexed in the Global Metadatabase for any AI workflow that legitimately needs it, while freeing premium capacity for the workloads where performance genuinely matters.