"How many hard drives does GMail need to buy this month ...

I'll make a practical estimate and show the math so you can adapt it to any scenario. I don't know the exact inputs you meant (number of users, average new data per user, drive size, replication strategy), so I'll:

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give the general formula,

run three realistic per-user growth scenarios (50 MB, 200 MB, 1 GB per user per month),

run them for three audience sizes (10k, 1M, 1.8B) and a common drive size (20 TB),

include a replication + overhead multiplier (typical for production storage), and

show one example calculation digit-by-digit so you can trust the arithmetic.

Formula

Total new data per month (MB) = users avg_MB_per_user

Total new data (TB) = Total_MB 1,000,000 (1 TB = 1,000,000 MB, decimal TB)

Raw drives required = Total_TB drive_TB

Production drives required = ceil( Raw_drives replication_factor overhead_factor )

Typical choices I'll use in examples below:

drive_TB = 20 (20 TB drive)

replication_factor = 3 (three copies / geo-replication)

overhead_factor = 1.2 (indexing, snapshots, slack)

One concrete calculation (step-by-step)

Scenario: 1,000,000 users, 50 MB/user/month, 20 TB drives, 3 replication, 1.2 overhead.

Total_MB = 1,000,000 50 = 50,000,000 MB.

Total_TB = 50,000,000 1,000,000 = 50 TB.

Raw_drives = 50 20 = 2.5 need ceil(2.5) = 3 raw drives to store data once.

Accounting for replication: 50 TB 3 = 150 TB.

Add overhead: 150 TB 1.2 = 180 TB.

Drives needed = 180 20 = 9 drives exactly. Answer for this scenario: 9 drives (20 TB each).

Quick results table (drive = 20 TB; replication=3; overhead=1.2)

Per-user monthly growth 50 MB / 200 MB / 1 GB

For 10,000 users

50 MB Total TB = 0.5 TB Production TB = 0.531.2 = 1.8 TB Drives 1 (ceil).

200 MB Total TB = 2 TB Production TB = 231.2 = 7.2 TB Drives 1.

1 GB Total TB = 10 TB Production TB = 1031.2 = 36 TB Drives = 2.

For 1,000,000 users (1M)

50 MB Total TB = 50 TB Production TB = 180 TB Drives = 9.

200 MB Total TB = 200 TB Production TB = 720 TB Drives = 36.

1 GB Total TB = 1000 TB Production TB = 3600 TB Drives = 180.

For 1,800,000,000 users (approx. 1.8B)

50 MB Total TB = 90,000 TB Production TB = 324,000 TB Drives = 16,200.

200 MB Total TB = 360,000 TB Production TB = 1,296,000 TB Drives = 64,800.

1 GB Total TB = 1,800,000 TB Production TB = 6,480,000 TB Drives = 324,000.

Notes & caveats (important)

I used decimal TB (1 TB = 1,000,000 MB). If you prefer TiB (binary), replace the divisor and results will shift slightly.

Replication factor for a service like Gmail is typically higher (multi-region redundancies, additional copies for backups), so real production needs may be larger than the 3 used here.

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Overhead factor (1.2) is conservative; some environments need 1.4-1.8 to account for indices, erasure coding inefficiencies, spare capacity, hot spares, maintenance copies, etc.

Drives should be procured with maintenance spares and to match your array/cluster architecture (RAID, erasure coding). Buying just the raw count is rarely sufficient you also need controllers, racks, PDUs, networking, cooling, and planning for daily growth.

For very large fleets, operators often buy in bulk by petabyte or exabyte targets, not per-month drive counts, and they stagger purchases to match lifecycle and performance requirements.

Recommendation

If you give me two numbers I'll re-run this immediately and precisely:

# of users (or monthly ingest TB), and

expected avg new data per user per month (MB),

and tell me the drive size you want to plan around (e.g., 18 TB, 20 TB, 22 TB). I'll return the exact drive count, plus suggested safety margin (spares + procurement cadence). If you don't want to provide numbers, tell me your target scale (small team / startup / enterprise / global) and I'll pick sensible defaults and produce a procurement plan.