How do we avoid drowning in false positives?

Start with a narrow ruleset tied to change events and high-signal runtime detections (RBAC changes, unsigned images, shell spawns). Run in observe mode for two weeks, label every alert as actionable/not, and only then enable blocks. Track false-positive rate and require a tuning PR for every noisy rule.

Is this overkill for a non-regulated SaaS?

No—reduce scope. Keep signatures, SBOMs, and one or two runtime detections. The payback is faster incident triage and fewer Friday night rollbacks. You can still do warn-only in lower tiers and reserve hard blocks for prod.

We’re on EKS with multiple clusters. Where do we start?

Pick one cluster and one service on the critical path. Add digest pinning + signature verification in admission, and Falco with two rules. In CI, generate SBOM and sign artifacts. Ingest K8s audit logs. Expand by namespace, not by cluster, to keep blast radius contained.

Do we need a full SIEM to do this?

Helpful, not required. You can get far with OpenTelemetry, Loki/Tempo, and a modest Elasticsearch or Datadog footprint. The critical piece is correlation: consistent IDs across CI/CD and runtime so you can stitch events together.

What about AI-generated code and hallucinated dependencies?

Treat AI like a junior dev: guardrails plus review. Enforce dependency allowlists, scan SBOMs, and block new packages without a ticket. Use repo-level policies to require PR descriptions referencing tasks. Provenance attestations help prove where code came from and which pipeline built it.

Security-compliance · Oct 2, 2025 · 10 minute read

Real-Time Security Monitoring Without Slowing You Down: Turning Policy Into Guardrails, Checks, and Proofs

Stop shipping blind. Wire your SDLC for real-time signals, automated enforcement, and evidence you can hand to auditors without killing velocity.

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Real-Time Security Monitoring Without Slowing You Down: Turning Policy Into Guardrails, Checks, and Proofs

Key takeaways

Implementation checklist