Pod Memory Request Calculator
Calculate the memory request for a pod that reflects real working-set usage.
About Pod Memory Request Calculator
Many network-facing services (proxies, API gateways, connection-pooling databases) have memory usage that scales with concurrency rather than staying flat. Modeling the request as a fixed baseline plus a per-connection cost captures that relationship far better than a single flat number, and makes it obvious how much headroom you need as traffic grows.
Formula
memoryRequest = baseline + (perConnectionMemory × avgConnections)
- B
- Baseline memory footprint in MiB (idle, zero connections)
- C_m
- Additional memory per active connection in MiB
- N
- Average concurrent connections
- M
- Recommended memory request in MiB
Worked example
With the default values below, Pod Memory Request Calculator returns Recommended Memory Request of 278. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Baseline Memoryaccepts 0–100,000 MiB
- 128 MiB
- Memory per Connectionaccepts 0–1,000 MiB
- 1.5 MiB
- Average Concurrent Connectionsaccepts 0–1,000,000 connections
- 100 connections
Results
- Recommended Memory Request
- 278 MiB
- Recommended Memory Request
- 0.27 GiB
- Connection-Driven Memory
- 150.0 MiB
- Share Driven by Connections
- 54.0%
Step by step
- 1Connection memory = per-connection × avg connections= 150.0MiB
- 2Memory request = baseline + connection memory= 278.0MiB
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 do I measure per-connection memory overhead?
Load-test the service at two different concurrency levels, record total memory usage at each, and divide the difference in memory by the difference in connection count to isolate the marginal per-connection cost.
Should I use average or peak connections for sizing requests?
Use average for the request (since it drives scheduling and bin-packing) and use peak connections when sizing the corresponding memory limit, to avoid OOMKills during connection spikes.
What if usage doesn't scale linearly with connections?
If memory grows faster than linearly (e.g. due to buffering or backpressure), model a higher effective per-connection value based on your peak-concurrency measurements rather than a light-load average.