SECOPS

Datadog anomaly to Cloudflare managed-challenge proposal

Triggers when a Datadog monitor flags an origin request-rate or error anomaly, correlates it with Cloudflare edge data.

CategorySecOps
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDatadog monitor alert webhook firesDatadogDatadog
  • ActionPull Cloudflare edge traffic for alert windowCloudflareCloudflare
  • LogicRank segments to find bot-heavy offender
  • ActionDraft managed-challenge WAF ruleCloudflareCloudflare
  • OutputPost proposal linked to alert in SlackSlack

What it does

Uses Datadog as the surge detector instead of polling Cloudflare directly. When a Datadog monitor on origin request rate or 5xx errors fires, this flow pulls the matching window of Cloudflare edge traffic, isolates the bot-heavy segment, and proposes a managed-challenge rule for review.

When to use it

Ideal for teams that already run Datadog as their source of truth for service health. It ties an alert you already trust to a concrete Cloudflare mitigation, so the on-call engineer goes from "origin is hot" to "here is the exact rule to stop it" in one step.

How it works

  1. 1A Datadog monitor alert webhook triggers the flow with the anomaly time window and affected service tags.
  2. 2An action queries Cloudflare analytics for that same window, scoped to the zone serving the service.
  3. 3A logic step ranks segments by bot score and request volume to find the dominant offender.
  4. 4An action drafts a managed-challenge WAF rule targeting that segment (matched by path, country, or ASN).
  5. 5The proposal, linking back to the Datadog alert, is posted to Slack where approval triggers the Cloudflare ruleset update.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DatadogMetrics, traces, log search.
  2. 2
    Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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