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Log Volume Per Day Calculator

Work out log volume per day instantly with clear inputs, formula shown and shareable results.

About Log Volume Per Day Calculator

Application log volume is request rate times lines per request times line size across the day, and it grows with traffic whether or not the logs are read. Six lines per request at 420 bytes on a busy service produces hundreds of gigabytes daily, which is why structured logging at appropriate levels — and sampling of high-volume success paths — is a cost control rather than a style preference.

Formula

Log volume

application bytes = rate x lines per request x bytes per line x 86400; total = application + infrastructure; peak ingest ~ 3x average

Worked example

With the default values below, Log Volume Per Day Calculator returns Log volume per day of 341.42 GiB. Change any input above and every figure here is recalculated in your browser.

Inputs used

Request rateminimum 0.001 req/s
1,500 req/s
Log lines per requestminimum 0.01
6
Average line sizeminimum 1 bytes
420 bytes
Infrastructure and platform logs per dayminimum 0 GB
40 GB

Results

Log volume per day
341.42 GiB
Application log volume
304.16 GiB
Log lines per day
777,600,000
Peak ingest bandwidth (3x average)
101.83 Mbps

Step by step

  1. 1Values used
  2. 2Log volume
  3. 3Log volume per day= 366,592,000,000
  4. 4Application log volume= 326,592,000,000
  5. 5Log lines per day= 777,600,000
  6. 6Peak ingest bandwidth (3x average)= 101.83 Mbps

Assumptions and limits

  • The result is derived only from the 4 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

Which logs are usually safe to drop?

Successful health checks, static asset requests and debug-level output in production. They typically account for the majority of volume and are almost never read.

Is sampling logs acceptable?

For high-volume success paths yes, provided errors are always kept in full. Head-based sampling with error escalation is the common pattern.

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Log Volume Per Day Calculator – Calculate Log volume per day