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Choose whether CDN delivery/request cost is already in your bill or should be added to the target case.
Use a preset as a realistic starting point, then replace values with analytics, billing, or CDN logs.
Use CDN analytics, origin logs, object storage billing, or a transfer estimate for the same monthly window.
{{ cacheable_percent }}%
Dynamic, personalized, POST, or bypassed traffic stays uncacheable and still reaches origin.
{{ current_hit_percent }}%
Use traffic hit rate when byte savings matter most; use request hit rate when origin compute dominates.
{{ target_hit_percent }}%
A target below the current hit rate intentionally models a regression or a conservative rollout.
Enter 0 when you only want bandwidth savings. Request counts are in millions.
M requests
Use a blended $/GB from the origin bill, including storage egress or hosting transfer charges.
$ / GB
Set to 0 for bandwidth-only analysis, or include origin compute and request costs that disappear on cache hits.
$ / M origin req
Use a blended CDN $/GB after free tier, regional mix, contract discounts, or flat-fee assumptions.
$ / GB
Set to 0 for no-request-fee or flat-fee CDN contracts.
$ / M requests
{{ miss_overhead_percent }}%
Keep low for clean cache fills; raise it when logs show duplicated pulls or range fragmentation.
Use 0 when fixed fees are already budgeted or not part of the decision.
$ / mo
Payback is shown when monthly net savings is positive.
$
Annual planning uses 12 months; short trials can use 1 to 3 months.
months
MetricValuePlanning noteCopy
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ScenarioHit rateOrigin transferMonthly costDeltaCopy
{{ row.scenario }} {{ row.hitRate }} {{ row.originTransfer }} {{ row.monthlyCost }} {{ row.delta }}
LeverModeled signalMonthly impactOperator actionCopy
{{ row.lever }} {{ row.signal }} {{ row.impact }} {{ row.action }} 
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Tags: Cloud, Finance, HTTP
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CDN cache-hit improvements reduce cost only when they reduce expensive origin work by more than any added delivery, request, fixed, or implementation cost. A higher hit rate means more cacheable traffic is served from edge locations and fewer cacheable requests reach the origin. The financial value depends on the share of traffic that can be cached, the current hit rate, the target hit rate, origin egress pricing, request pricing, miss amplification, and the CDN charges that remain in the optimized path.

Cache-hit rate is often discussed as a performance metric, but cost analysis needs a more specific model. Uncacheable traffic still reaches the origin. Cache misses can amplify origin load when redirects, object fan-out, retries, image transforms, or application calls are triggered behind a single client request. A workload with a modest hit-rate gain can save a meaningful amount when origin transfer is expensive, while a workload with low cacheable share may see limited savings even after a large cache-policy effort.

This calculation is useful when deciding whether to tune headers, separate static and dynamic routes, adjust time-to-live policy, enable edge caching for API responses, or place a CDN in front of an origin for the first time. It frames cache work as a monthly cost comparison with payback and break-even hit-rate checks, rather than treating hit-rate lift as automatically valuable.

What It Answers:

  • How much origin egress and request cost changes when hit rate moves from the current state to the target state.
  • Whether adding or tuning CDN delivery produces net monthly savings after CDN delivery, request, fixed, and setup costs.
  • What hit rate is needed to break even under the current rate card.
  • Which scenario is more cost effective across conservative, planned, and aggressive hit-rate assumptions.

Input Model:

The model starts with total delivered traffic and monthly requests, then splits both into cacheable and uncacheable portions. Only the cacheable portion benefits from hit-rate improvement. The current hit rate describes how much cacheable traffic already avoids origin. The target hit rate describes the expected result after policy changes, object tuning, route cleanup, or CDN adoption.

Two cost modes are supported conceptually. In an existing-CDN optimization, CDN delivery and request costs are assumed to be already present, so the analysis focuses on the change in origin cost and any fixed monthly change cost. In an add-CDN evaluation, target-state cost includes CDN delivery and request charges because those become part of the new delivery path. This distinction prevents an optimization project from being judged by costs that already exist, and prevents a new CDN project from ignoring added CDN spend.

Driver Cost effect Planning question
Cacheable share Limits how much traffic can be moved away from origin. Can headers and route design make more content cacheable?
Hit-rate lift Reduces cacheable misses and origin pulls. Is the target realistic for the content mix?
Origin rates Sets the avoided transfer and request value. Is origin load materially expensive?
CDN rates Adds delivery-path cost in add-CDN cases. Does the edge delivery charge still leave net savings?

Interpreting the Results:

Gross origin savings show the avoided origin bill before added CDN or project costs. Net savings are the more important decision number because they compare the complete current and target monthly states. A positive net savings result supports cache-policy work or CDN adoption, while a negative result suggests that the project may still be justified for latency, resilience, or origin protection, but not by monthly cost reduction alone.

Use the break-even hit rate as a feasibility check. If the required hit rate is higher than the workload can reasonably achieve, the cost case is weak. For API JSON, personalized pages, or short-lived objects, the practical hit-rate ceiling may be much lower than for software downloads, media assets, or versioned static files. The payback period should be compared with the expected life of the workload and the one-time effort required to implement the change.

Technical Details:

The origin-load model keeps uncacheable traffic at origin and applies hit rate only to cacheable traffic. Miss amplification increases origin transfer when a cache miss causes more backend work than the client-visible response size. Monthly cost is then the sum of transfer, request, fixed, and target-path delivery charges for the selected scenario.

origin_GB = ( uncacheable_GB + cacheable_GB x (1-hit_rate) ) x miss_factor
origin_cost = origin_GB x origin_rate_per_GB + origin_requests_M x origin_rate_per_M
net_monthly_savings = current_total_cost - target_total_cost

Practical Checks:

  • Estimate cacheable share from logs or route classes rather than assuming all traffic can be cached.
  • Separate large-object traffic from small high-request workloads; they respond differently to transfer and request pricing.
  • Include implementation cost when header, invalidation, origin-shield, or application changes require engineering time.
  • Review the result after real hit-rate data is available, because cache policy changes can behave differently under production traffic.

References: