Storage Growth Forecast
Forecast future storage needs from historical growth rate and planning horizon.
About Storage Growth Forecast
Given a constant daily growth rate, the runway before a disk fills is simply the remaining free capacity divided by that daily growth — the same math behind Kubernetes and cloud-provider disk-full predictions. This linear forecast assumes growth stays roughly steady; sudden traffic spikes, log storms, or new workloads landing on the volume can shrink the runway far faster than the trend suggests, so this estimate should be revisited regularly rather than treated as a one-time calculation.
Formula
Days until full
days_until_full = (total − used) / daily_growth
- T
- total capacity
- U
- currently used capacity
- g
- daily growth rate
Worked example
With the default values below, Storage Growth Forecast returns Days Until Full of 70.0. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Total Capacityminimum 0.001 GB
- 1,000 GB
- Currently Usedminimum 0 GB
- 650 GB
- Daily Growthminimum 0 GB/day
- 5 GB/day
Results
- Days Until Full
- 70.0 days
- Projected Full Date
- Jan 07, 2027
- Remaining Capacity
- 350.00 GB
- Urgency
- Moderate — schedule capacity review
Step by step
- 1Values used
- 2Days until full
- 3Days Until Full= 70.0 days
- 4Projected Full Date= Jan 07, 2027
- 5Remaining Capacity= 350.00 GB
- 6Urgency= Moderate — schedule capacity review
Assumptions and limits
- The result is derived only from the 3 inputs listed above. Anything not among them is not part of the calculation.
- In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
- Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.
How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.
Frequently Asked Questions
How should I measure daily growth accurately?
Take used-space samples (df -h or equivalent) at the same time each day over at least a week, then average the day-over-day differences — a single day's sample can be skewed by one-off events like a large backup or temp file cleanup.
What should I do once I know the disk-full date?
Set a monitoring alert well before the projected date (e.g. at 80% capacity), and start capacity expansion, cleanup, or data archival work with enough lead time to complete before urgency escalates — waiting until the disk is nearly full risks application failures or an emergency, unplanned expansion.
Why might the actual full date differ from this forecast?
Growth rates are rarely perfectly linear — traffic patterns, seasonal spikes, new features generating more data, or scheduled cleanup jobs (log rotation, cache eviction) can all accelerate or decelerate the trend, so this figure is best used as an early-warning estimate rather than an exact prediction.