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To investigate a sudden traffic rise, start with request-level data and a defined time window—not page views alone. Compare the affected period with normal activity for the same site and endpoint, then check paths, response codes, request rates, client attributes, and whether traffic reached your origin. A spike can indicate automation, but it does not by itself prove abuse: verified crawlers and monitoring services may be legitimate.
Start by establishing what changed
Record when the increase began, how long it lasted, and which data source shows it: client-side analytics, CDN or security analytics, origin access logs, or application telemetry. These sources measure different parts of a request’s journey. A page-view increase is not necessarily a matching increase in requests, and a request increase does not necessarily mean more human visitors.
If your platform exposes edge-versus-origin data, check whether requests were served from the CDN, mitigated there, or forwarded to your origin. Cloudflare Security Analytics, for example, reports incoming HTTP requests, including requests that its security products did not handle, and can distinguish mitigated, Cloudflare-served, and origin-served traffic. See Cloudflare Security Analytics.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitches- Mark the spike’s start and end times, including the timezone.
- Record the comparison window and whether it is a typical period for that site—for example, the same weekday and hour if traffic varies by schedule.
- Keep requests, sessions, and visits separate in your notes; they are different measurements.
- Check whether the origin experienced more load, errors, or latency, rather than assuming an analytics spike reached the server.
Find the requests behind the spike
Compare the unusual interval with an ordinary interval for the same site and, where possible, the same endpoint. Look for concentrations that explain the change rather than relying on the total alone.
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- Paths and methods: identify whether requests clustered on login, API, checkout, search, or another expensive route; note methods such as GET or POST.
- Status codes: check for unusual success, redirect, authorization, or error responses. Repeated 403 or 404 responses can be a useful signal, but are not proof of malicious behavior.
- Rate and duration: note requests per interval, burst patterns, and whether activity persisted or came in short waves.
- Client attributes: compare IP addresses or other available client identifiers, user-agent strings, and geographic concentration. A single shared address can represent many users behind a network, while an easily changed user-agent string is not reliable identification on its own.
- Delivery path: check cache status and whether requests were served at the edge or reached the origin, if those fields are available.
Cloudflare’s bot guidance highlights sudden spikes of low bot-score traffic, high-volume user agents, and geographic concentration as patterns worth reviewing. Treat these as investigation leads, not standalone findings. Cloudflare’s guide to stopping malicious bots while allowing legitimate traffic describes these patterns and mitigation considerations.
Choose the right monitoring vantage point
No single dashboard answers every question. Client analytics can show visits and user behavior, while edge data and server logs reveal requests that analytics scripts may not record. Application telemetry can add endpoint-level context such as workload or errors. Choose the source according to what you need to establish.
| Monitoring source | Best suited to | Key limitation to check |
|---|---|---|
| Client-side web analytics | Visits, sessions, and on-page behavior | Does not necessarily capture every HTTP request, including requests that do not run the analytics code. |
| CDN or security analytics | Edge-visible request volume, paths, response and delivery details, and available bot signals | Coverage, sampling, history, and response controls vary by provider and plan. |
| Origin access logs | Requests that reach the server, with request and response details recorded by the origin | Does not include requests stopped or served before reaching the origin; retention and fields depend on configuration. |
| Application telemetry | Endpoint behavior, application errors, and the workload associated with requests | Usually needs correlation with edge or access data to explain traffic that did not reach the application. |
For each source, confirm which requests it covers, whether it includes paths and response codes, whether it records edge-versus-origin delivery, how client attributes are represented, and what history is actually available. Also consider setup effort, privacy implications, and the risk that a control at the edge could affect a legitimate integration.
Check sampling and history before drawing conclusions
A dashboard may summarize sampled data rather than every request. Cloudflare says Security Analytics uses sampled data by default; raw logs are available 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 the investigation depends on a complete request-by-request account, consult raw logs where available instead of treating a sampled summary as a census. See Cloudflare Bot Analytics and the Security Analytics documentation.
Do not promise a retention period based on a generic product description. Verify the current plan documentation for the account in question, and preserve relevant logs promptly if an incident may outlast the available history.
Interpret bot signals without overcalling abuse
Automated requests can be legitimate or harmful, and a vendor’s classification is specific to that vendor’s product. In its documented context, Cloudflare categorizes verified bots, automated traffic, likely automated traffic, and likely human traffic. Its guide describes bot score 1 as automated, scores 2–29 as likely automated, and scores 30–99 as likely human. These scores are not a universal standard and should be read alongside the request’s path, rate, behavior, and effect on the site.
Cloudflare’s verified bots include confirmed crawlers and services such as Googlebot, Bingbot, and uptime monitors. An automated request is not inherently abusive; disrupting a search crawler or an availability monitor can create its own operational problem. Preserve known legitimate automation and investigate whether an unfamiliar source is actually causing harm before applying a control.
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An alert is most useful when it points to a measurable change that matters to your site—such as a rise in requests to a costly endpoint or unusual automated traffic—and gives you enough request detail to investigate. Establish a baseline for the affected endpoint first. A normal rate for a homepage may be inappropriate for a login or API route.
Cloudflare documents a Bot Detection Alert for accounts with at least one Enterprise zone. Its basic logic looks for an unusual spike (Z-score above 3.5) and more than 200 bot requests in five minutes, using bot score below 30; it uses a six-hour baseline and excludes verified bots. Cloudflare says sufficient data may take up to 30 minutes to become available after alert creation. These are settings for that specific Cloudflare feature, not general thresholds to copy onto another site. Details are in Cloudflare Bot Detection Alerts.
- Define the impact: decide whether the concern is origin load, service latency, abusive account activity, scraping, or another concrete effect.
- Set a baseline: measure ordinary request rates for the relevant endpoint and account for predictable peaks.
- Scope a rule: when considering a challenge, rate limit, or block, narrow it by relevant path and method rather than applying it site-wide by default.
- Observe before escalating: use a log-only or observation mode when available, then review what would match and whether legitimate traffic is included.
- Mitigate and verify: apply the least disruptive control likely to address the issue, then check rule matches, origin load, and user-facing behavior.
Cloudflare’s rate-limiting guidance includes example rules, including one that uses repeated origin 403/404 responses as a bot signal. Examples depend on plan-specific features and should not be treated as ready-made defaults. Review Cloudflare’s rate-limiting best practices before adapting a rule.
What a traffic spike may mean—and what it does not
Cloudflare’s 2024 State of Application Security report says that an average 31.2% of the application traffic processed by Cloudflare was identified as bot traffic, and that 93% of the bots it identified were unverified. Those figures describe Cloudflare’s measured traffic and definitions; they are not estimates for all internet traffic or every website. The report discusses possible effects including server load, slower service for legitimate visitors, scraping, spam, and account takeover, but none is a guaranteed consequence of every bot spike. Cloudflare State of Application Security 2024.
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