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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →To investigate a sudden traffic rise, compare request-level data for the affected time window with normal activity on the same endpoints. Check paths, response codes, request rates and client attributes across analytics, CDN or security data, and origin logs where available. A spike or bot score is a clue, not proof of abuse: verify what the requests did before applying a narrowly scoped challenge or block.
Start by confirming what increased
Record when the change began, how long it lasted, and which measurement shows it. Page views, sessions, HTTP requests, and origin requests are different measures; a rise in requests does not necessarily mean a comparable rise in human visitors.
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Compare the analytics view with CDN or security request data and origin access logs if you have them. For example, Cloudflare Security Analytics describes incoming HTTP requests, including requests not handled by Cloudflare security products, and can distinguish traffic mitigated, served by Cloudflare, or served by the origin. Those distinctions can help determine whether the origin itself received the extra load.
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Compare the unusual interval with normal activity
Choose an ordinary comparison period and examine the same site and, if possible, the same endpoint. A site-wide total can hide a concentrated burst against one resource. Review:
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- Request paths and methods, especially login, API, checkout, or other resource-intensive endpoints.
- Response status codes and request rates over time.
- IP addresses or other available client attributes, user-agent strings, and geographic concentration.
- Whether requests were served from cache, mitigated at the edge, or passed to the origin, when your platform exposes that information.
Cloudflare’s bot guidance identifies patterns such as sudden spikes in low-score traffic, high-volume user agents, and geographic concentration as reasons to investigate. These are indicators, not proof: legitimate crawlers, uptime monitors, integrations, and other automation can produce unusual traffic too.
Know what your traffic data can and cannot show
A dashboard summary may not represent every request. Cloudflare Security Analytics uses sampled data by default; raw logs are available only in specific circumstances and through Log Explorer for eligible access. Cloudflare Bot Analytics also samples data, and its history and display windows vary by plan. If a forensic conclusion depends on seeing every request, use raw logs where available rather than treating a sampled dashboard as a complete census.
Before relying on a particular history or retention period, check the provider’s current plan documentation. Cloudflare’s pages for Security Analytics and Bot Analytics describe these plan and sampling constraints.
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Interpret bot labels as signals, not verdicts
Cloudflare’s documented classifications distinguish verified bots, automated traffic, likely automated traffic, and likely human traffic. Its guidance describes verified bots as confirmed crawlers and services such as Googlebot, Bingbot, and uptime monitors. In that product context, bot scores of 1 indicate automated traffic, scores 2–29 indicate likely automated traffic, and scores 30–99 indicate likely human traffic.
These labels and scores belong to Cloudflare’s classification system; they are not universal standards. A request classified as automated is not automatically malicious. Check its path, behavior, and purpose, and preserve known legitimate crawlers and services unless you have evidence they are causing a problem.
Set alerts around the traffic that matters
Where your provider offers anomaly alerts, choose a meaningful traffic dimension and inspect the request analytics associated with an alert rather than treating the notification itself as a diagnosis. Cloudflare’s documented Bot Detection Alert is available to accounts with at least one Enterprise zone. Its documented logic uses an unusual spike (Z-score above 3.5) plus more than 200 bot requests in five minutes, with bot score below 30; its baseline window is six hours and it excludes verified bots. Cloudflare says it may take up to 30 minutes after alert creation for sufficient data to be available. These are the settings described for that particular feature, not recommended universal thresholds. See the Bot Detection Alerts documentation for current details.
For any alert, establish a baseline for the affected endpoint before choosing a threshold. Normal request rates differ between a login page, a cached article, and an API that supports an integration. Account for legitimate peaks and the endpoint’s capacity so that the alert identifies a meaningful deviation rather than routine activity.
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Before challenging or blocking traffic, define a limited scope—for example, a particular path and request method—and use observed normal traffic and endpoint capacity to set a threshold. If supported, observe rule matches before enforcing a control. Cloudflare’s rate-limiting guidance includes example rules, including one using repeated origin 403 or 404 responses as a bot signal; examples depend on plan features and should not be treated as ready-made defaults.
- Identify the affected resource: use request data to select the path, method, and time window involved.
- Check the baseline: establish ordinary traffic for that endpoint and account for legitimate crawlers, users, and integrations.
- Choose the smallest effective control: where available, begin with observation or a challenge for the targeted traffic before escalating to a block.
- Review the result: check whether the unwanted requests declined and whether real users, search crawlers, and important integrations still work.
Bot traffic can contribute to server load, slower service for legitimate visitors, scraping, spam, or account takeover, but none of those outcomes follows automatically from every automated-request spike. Cloudflare’s 2024 application security report says bot traffic averaged 31.2% of application traffic processed by Cloudflare, and that 93% of the bots it identified were unverified. Those figures describe Cloudflare’s measured traffic and definitions—not all websites or all internet traffic. The report discusses possible impacts, not guaranteed effects of any individual spike. See Cloudflare’s 2024 report.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose monitoring based on the question you need to answer
| Monitoring view | What it helps establish | What to check |
|---|---|---|
| Client analytics | Visitor and page-view trends. | Whether it reports visits or requests; it may not explain which requests reached the origin. |
| CDN or security analytics | Edge request patterns and, on some platforms, whether traffic was mitigated, served at the edge, or sent to the origin. | Available paths, response codes, client attributes, bot classification, sampling, and plan-based history. |
| Origin access logs | Requests that reached the server and their recorded paths, methods, statuses, and client details. | Log coverage, retention, and whether edge caching or mitigation means some traffic is absent from origin logs. |
| Application telemetry | How requests affected application behavior and resources. | Which events and client details it records, and whether it can be correlated with edge or access-log data. |
No single view necessarily answers every question. Combine the vantage points you have, and account for sampling, retention, privacy implications, configuration effort, false-positive risk, and whether a control acts at the edge or protects the origin. Cloudflare’s own analytics documentation illustrates the importance of checking sampling and plan-dependent history rather than assuming every dashboard has complete, long-term request data.
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