How do we avoid drowning in false positives?

Start with a narrow rule set targeting high-signal events (exec in containers, policy violations, public exposure). Track a false-positive budget and kill or tune noisy rules weekly. Route only CRITICAL to PagerDuty; send lower severities to Slack with thresholds.

Which policy engine should we standardize on?

Use OPA/Rego for IaC and service-level decisions, and Kyverno for Kubernetes admission—its UX is friendlier for cluster policies. Avoid running both for the same control. Keep a single policy repo and publish versioned bundles.

How do we produce audit evidence without manual work?

Automate: sign builds and SBOMs with Sigstore, export CI scan results, and store admission decisions/policy evaluations in immutable storage with lifecycle policies. Generate reports from those artifacts—not from memory.

Won’t this slow our delivery teams?

Done right, no. Pre-commit hooks and PR checks catch issues before reviews. Admission controllers prevent bad deploys. Break-glass paths exist but are time-bound and audited. Teams move faster because the rules are clear and automated.

Where should we start if our stack is messy and includes AI-generated code?

Triage critical controls first (identity, secrets, network egress). Run a vibe code cleanup on AI-generated configs and policies in a staging sandbox. Add guardrails before detection: block obviously unsafe patterns, then layer runtime sensors. GitPlumbers can help prioritize and refactor without halting releases.

Security-compliance · Nov 16, 2025 · 9 minute read

When Your SIEM Sleeps Through Production: Building Real-Time Detection and Automated Proofs Without Killing Delivery

No more PDF policies gathering dust. Turn intent into guardrails, real-time signals, and auditable proofs that ship with your software.

Back to all posts

When Your SIEM Sleeps Through Production: Building Real-Time Detection and Automated Proofs Without Killing Delivery

Key takeaways

Implementation checklist