SECOPS
Correlate WAF events with Datadog app errors into a weekly tuning report
Weekly, joins Cloudflare WAF blocks against Datadog application error and latency metrics to separate rules that block real attacks from rules that block legitimate traffic.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionPull week of firewall events by rule and endpointCloudflare
- ActionQuery Datadog error, latency, and volume metricsDatadog
- LogicCorrelate blocks vs app health; score false positive vs effective
- ActionGenerate ranked per-rule tuning reportOpenAI
- OutputPublish report to ConfluenceConfluence
What it does
Cross-references a week of Cloudflare WAF blocks with Datadog telemetry from the same time windows and endpoints. Blocks that coincide with upstream app errors or known-good client behavior are flagged as suspected false positives; the result is a ranked, evidence-backed tuning report.
When to use it
When you want a defensible, data-driven view of which managed rules to tune — backed by what the application actually saw — instead of guessing from WAF counts alone. Good for a weekly secops review ritual.
How it works
- 1A weekly schedule starts the run.
- 2It pulls the week's Cloudflare firewall events grouped by rule and endpoint.
- 3It queries Datadog for error rates, latency, and request volume on the matching endpoints and windows.
- 4A logic step correlates the two: high block volume with healthy app metrics and trusted clients scores as false-positive; blocks alongside attack-shaped traffic score as effective.
- 5An OpenAI step writes a ranked report with per-rule recommendations.
- 6The report is published to a Confluence page for the team.
Set it up
What you configure once, before turning it on.
- 1Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
- 2Connect DatadogMetrics, traces, log search.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect ConfluenceSpaces, pages, blueprints.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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