Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteA traffic spike alone does not prove that bots caused a website outage. Look for several signals that coincide: an unusual rise in requests or bandwidth, repeated or abnormal request patterns, and errors or strain at the origin. Compare the event with the site’s normal traffic, check the CDN or proxy and origin separately, and rule out legitimate monitoring and provider problems before changing security rules.
Start by defining the outage
Record when the slowdown or errors began, which pages or APIs are affected, and whether failures are intermittent or consistent. Note what users actually experience alongside the time window: slow responses, timeouts, or error codes. Recurring or intermittent 4xx or 5xx errors can be consistent with an origin struggling under load, but errors by themselves do not identify the cause. Google Project Shield’s troubleshooting guidance also lists provider maintenance or an outage as possible explanations.
Compare the outage window with request volume, bandwidth, edge or WAF errors, origin response errors, and origin health. A useful diagnosis explains both the timing and the impact; a metric that changes without lining up with the failures is weaker evidence.
Compare traffic with the site’s normal pattern
Use the site’s own request and bandwidth history as the baseline. Compare equivalent times and days, and account for promotions, launches, news coverage, crawlers, or other expected events. Google Project Shield recommends comparing traffic with its normal range and notes that a seven-day view can help reveal daily peaks and valleys. That is one useful comparison window, not a universal requirement.
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Cloudflare identifies downtime, unexpected request or bandwidth increases, and unusual requests in origin logs as signs worth investigating—not proof that an attack is occurring. Cloudflare’s DDoS guidance describes these as indicators to assess together.
Inspect what the requests are doing
Where logs or provider analytics allow, examine the affected hostnames and paths, HTTP methods, request rates, response codes, user agents, and origin error rates. Check whether requests cluster on an expensive page, a login or API endpoint, or cache misses—or whether activity is broad and plausibly reflects real demand. Cloudflare’s DDoS detection overview describes HTTP request metadata and origin response metrics as relevant detection inputs.
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Large volumes of origin 403 or 404 responses can fit a bot or scraping pattern, but the context matters. Cloudflare’s rate-limiting guidance gives this as an example tied to a particular plan and rule configuration; it is not a universal request-rate threshold or a diagnosis on its own.
Compare the edge, proxy, and origin
If the site uses a CDN, reverse proxy, or WAF, examine its view of incoming traffic separately from origin logs and health. First establish which IP address each system records. A cluster of requests from a few addresses can mean a small number of clients, but it can also mean many visitors are being grouped behind an intermediary.
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AWS notes that Bot Control automatically recognizes some named CDN client-IP headers; other proxy setups may require forwarded-IP configuration for rules that evaluate IP addresses. AWS’s Bot Control documentation explains the configuration caveats. Cloudflare likewise warns that another CDN or proxy in front of its service can cause the downstream service to see only intermediary addresses, which may reduce mitigation accuracy or contribute to false positives. Cloudflare’s request-header guidance describes the proxy-chain issue.
Check whether the edge is healthy while the origin is failing, or whether requests and errors are already abnormal at the edge. These observations help narrow where the problem sits, but they still need to be matched to the request pattern and the outage window.
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Rule out legitimate automation and service problems
Check whether any scheduled work or monitoring changed near the start of the outage. Uptime checkers, internal monitoring, load-balancer health checks, search crawlers, and scheduled jobs can all generate automated requests. AWS explicitly notes that monitoring tools, uptime checkers, and health checks may be identified as bot activity in its Bot Control guidance.
Also check the hosting provider and CDN’s status or maintenance information, and assess the origin directly where possible. A provider incident or maintenance window may explain downtime without a traffic attack. The Project Shield guidance on troubleshooting site availability includes hosting-provider problems among the possibilities to investigate.
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Weigh the competing explanations
When the cause is not obvious, compare the candidate explanations across four questions:
- Did requests or bandwidth rise unusually compared with the site’s baseline?
- Do affected routes, methods, rates, and response patterns look like repeated automated requests?
- Is the origin unhealthy while the edge or CDN remains healthy, or do failures appear at both layers?
- Does a provider incident, deployment, promotion, crawler, monitor, or scheduled job explain the timing?
No single metric settles the diagnosis. A traffic rise plus matching unusual requests and origin strain is more consistent with traffic-driven failure than any one of those observations alone. This is the distinction emphasized by Cloudflare’s list of DDoS indicators, its detection overview, and Project Shield’s troubleshooting advice.
Respond without blocking legitimate users
If the evidence points to automated traffic, preserve a sample of relevant logs and provider analytics before changing rules. Use the existing platform’s logging, challenge, or rate-limit controls at a scope that matches the affected route and traffic. AWS recommends dashboard visibility and detailed WAF logging; anomalous rules and labels can help investigate traffic and spot false positives. Its application-layer DDoS guidance describes managed mitigation that compares current patterns with historical baselines, along with limitations when a CDN does not preserve or forward client attributes.
Rate limits can control automated request rates, and Cloudflare recommends considering them with bot management where appropriate. The effective rule depends on the site’s architecture and legitimate traffic pattern; an example threshold from a provider is not a general-purpose cutoff. See Cloudflare’s rate-limiting best practices and AWS’s application-layer DDoS documentation for provider-specific behavior and configuration.
Do not block a source simply because it is unfamiliar or automated. Legitimate crawlers, monitors, customers behind shared networks, and visitors whose addresses are obscured by proxies can resemble hostile traffic. Validate a proposed rule’s likely effect and watch for legitimate requests being challenged or denied.
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