👥 Concurrent User Traffic to Bandwidth Pipe
1,000 concurrent users streaming 720p at 5 Mbps = 5 Gbps. At 10,000 users it is 50 Gbps — time for dedicated interconnects. Model the worst-case before launch day. The pipe size you budget for is not the pipe size you need at peak.
📶 Traffic Profile
Peak concurrent sessions × Kbps per user ÷ 1,000 = minimum Mbps. Add 1.3× headroom so CUBIC and BBR have room to breathe. Daily transfer estimate included — because the cloud egress meter runs 24/7.
Concurrent Users to Bandwidth: How Many Mbps Does 5,000 Users Need?
When architecting a web application, the question "how much bandwidth do I need?" is deceptively simple. The answer depends on two variables: peak concurrent sessions and average bandwidth consumption per user session. This calculator applies the fundamental formula Bandwidth (Mbps) = Users × Kbps per user / 1000 to produce a minimum line speed requirement — and then applies a 1.3× provisioning multiplier to account for TCP overhead, bursts, and degradation avoidance.
The Bandwidth Formula: Breaking It Down
The core calculation is straightforward but often underestimated during capacity planning:
- Minimum Bandwidth (Mbps) = Peak Concurrent Sessions × Kbps per User ÷ 1000
- Minimum Bandwidth (Gbps) = Mbps ÷ 1000
- Provisioned Bandwidth = Minimum Bandwidth × 1.3 (30% headroom)
- Daily Transfer (TB) = Gbps × 10.8 (assumes steady-state usage over 24 hours; 1 Gbps sustained = ~10.8 TB/day)
Per-User Bandwidth Benchmarks by Application Type
| Application Type | Kbps per User | Notes |
|---|---|---|
| Simple Web App (CRUD, text-heavy) | 100 – 250 | Small JSON payloads, minimal assets. Typical SaaS dashboard. |
| Rich Web App (SPA, images) | 250 – 500 | Larger JS bundles, image assets, frequent API polling. |
| Video Conferencing (per stream) | 500 – 2,000 | WebRTC HD video. Bidirectional = double for total pipe. |
| HD Video Streaming | 2,000 – 5,000 | Netflix ~3 Mbps for HD, ~7 Mbps for 4K. Add 15% for ABR overhead. |
| Real-Time Gaming | 50 – 100 | Small state updates, but extremely latency-sensitive. |
Why Provision 1.3× Headroom?
Running a network link at 100% utilization invites disaster. TCP congestion control algorithms (CUBIC, BBR) need headroom to probe for available bandwidth. At >80% utilization, bufferbloat becomes a real problem — latency spikes as packets queue in switch buffers, triggering retransmissions that compound the congestion. The 1.3× multiplier (effectively targeting ~77% peak utilization) keeps your pipe in the safe operating zone and absorbs micro-bursts that statistical multiplexing cannot smooth out.
CDN Offloading and Edge Caching
If your application serves substantial static content or API responses that can be cached, a CDN can dramatically reduce the origin bandwidth requirement. Each cache hit eliminates a round-trip to your origin server. With a 90% cache hit ratio, your origin bandwidth demand drops to 10% of the raw requirement — turning a 5 Gbps pipe into a 500 Mbps pipe. Use our CDN Cache Offload Calculator to model your specific savings.