AWS WAF vs Cloudflare WAF cost: a practical comparison checklist

AWS WAF vs Cloudflare WAF comparisons often go wrong because teams compare list prices without normalizing traffic shape. Use this checklist to compare apples-to-apples: baseline policies, evaluated requests, and the cost of security logging and analytics.

1) Normalize traffic volume (including spikes)

  • Average requests/month (steady state)
  • Peak hours and attack/bot scenarios
  • Include blocked traffic if it is still evaluated

Tooling: estimate WAF requests and model a surge scenario.

Worked comparison template (copy/paste)

  • Baseline: evaluated requests/month + policies/rules you run in steady state
  • Attack: extra evaluated requests during spikes (hours/days) + any temporary rules you enable
  • Logs & analytics: ingestion GB/day + retention days + query/scan frequency for dashboards
  • Extras: bot management, rate limiting, and any features you actually use (avoid comparing "default plans" to "fully loaded configs")

2) Compare baseline policy/rule costs

  • How many apps/environments require distinct policies?
  • How many rule groups (managed + custom) do you need?
  • Do you pay extra for bot management, rate limiting, or advanced features?

In practice, "how many distinct policies do we maintain?" is often the real baseline driver (copy/paste sprawl creates both cost and operational risk).

3) Don't ignore the second bill: logs and analytics

  • Log delivery and ingestion cost (GB/day)
  • Retention (GB-month)
  • Query/scan costs for dashboards and incident response

If you ship every event into logs and run wide-window dashboards, the log bill can rival the WAF bill.

4) Operational and architecture constraints

  • Where traffic is filtered (edge vs origin) and how that affects origin egress.
  • How quickly you can deploy rule changes safely.
  • How you export events into your existing security tooling.
  • Consider where bad traffic stops. If a platform stops traffic earlier, you may reduce origin load and downstream logging/compute costs.
  • Consider failure modes: a misconfigured rule rollout can create an outage and a cost spike (retries and incidents multiply traffic).

How to validate the choice

  • Run a short measurement window and estimate evaluated requests/day under normal traffic.
  • Keep an explicit spike scenario (your worst bot wave/attack window) and compare costs under that stress.
  • Verify the logging plan: what is logged, where it lands, and how long it is retained.

Related guides

AWS WAF pricing WAF cost spikes during attacks WAF cost optimization

Validation checklist

  • Validate the primary driver with measured usage from a representative window.
  • Confirm units and pricing units (per 10k vs per 1M, GB vs GiB) before trusting the estimate.
  • Re-check incident windows: retries/timeouts often multiply cost drivers.

Related reading

Cost estimation checklist Network transfer costs Request-based pricing

Sources

Related guides

Estimate WAF request volume (CDN/LB to monthly requests)
How to estimate WAF request volume for cost models: from CDN/LB metrics, from logs, and what to do about bot spikes.
WAF cost optimization (reduce requests + rule sprawl)
A practical playbook to reduce WAF spend: cut evaluated requests, keep rule count tight, and avoid downstream logging waste.
WAF cost spikes during attacks: how to budget request surges
A practical guide to WAF cost spikes during attacks: why request-based charges jump, how to model surge traffic, and how to reduce evaluated requests and logging volume safely.
API Gateway vs ALB vs CloudFront cost: what to compare (requests, transfer, add-ons)
A practical cost comparison of API Gateway, Application Load Balancer (ALB), and CloudFront. Compare request pricing, data transfer, caching impact, WAF, logs, and the hidden line items that change the answer.
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Compare Lambda vs Fargate cost with unit economics: cost per 1M requests (Lambda) versus average running tasks (Fargate), plus the non-compute line items that often dominate (logs, load balancers, transfer).
AWS cost checklist: model the drivers that actually move the bill
A practical AWS cost checklist for planning and reviews: define scope, identify top cost drivers (requests, GB, GB-month, hours), and avoid the common blind spots (data transfer, logs, and cross-AZ).

Related calculators

Log Cost Calculator
Estimate total log costs: ingestion, storage, and scan/search.
Log Ingestion Cost Calculator
Estimate monthly log ingestion cost from GB/day or from event rate and $/GB pricing.
Log Retention Storage Cost Calculator
Estimate retained log storage cost from GB/day, retention days, and $/GB-month pricing.
Log Search Scan Cost Calculator
Estimate monthly scan charges from GB scanned per day and $/GB pricing.
RPS to Monthly Requests Calculator
Estimate monthly request volume from RPS, hours/day, and utilization.
API Request Cost Calculator
Estimate request-based charges from monthly requests and $ per million.

FAQ

What usually drives WAF cost in practice?
Request volume (especially during spikes) plus your baseline policy/rule configuration. Logging, storage, and analytics can be a second bill that rivals the WAF line item.
Is a cheaper WAF always the better choice?
Not necessarily. You also need to consider the features you need (managed rules, bot protection, rate limiting), operational workflow, and where traffic is stopped (edge vs origin).
What's the fastest way to compare costs fairly?
Use the same evaluated request volume and the same surge/attack scenario for both, then include logging/retention costs and any add-ons you actually use.
Last updated: 2026-01-27