Runtime exposure management: what it means for cloud security teams

TL;DR: Cloud-native teams are drowning in overlapping visibility tools, while AI-assisted development and faster deployments are pushing vulnerabilities into production before alert queues can keep up, according to Aqua Security. The real shift is from collecting findings to reducing exploitable exposure in runtime, where business context and operational clarity now matter more than raw signal volume.

NHIMG editorial — based on content published by Aqua Security: Built for This Moment

Questions worth separating out

Q: How should security teams prioritise cloud vulnerabilities when alert volume is overwhelming?

A: Prioritise vulnerabilities by whether they are present in running workloads, reachable from an attack path, and connected to business-critical services.

Q: Why do visibility tools fail to reduce cloud security risk on their own?

A: Visibility tools fail when they produce findings without telling teams which ones matter in production.

Q: What do security teams get wrong about CNAPP consolidation?

A: They often assume consolidation automatically creates clarity.

Practitioner guidance

• Rebuild triage around runtime exposure Map vulnerabilities to live workloads, public reachability, and business criticality before assigning remediation priority.
• Collapse overlapping CNAPP ownership Assign a single team to own exposure triage across posture, workload, and runtime tools, then define which platform is authoritative for each decision type.
• Measure production risk reduction, not alert volume Track how many exploitable issues are removed from reachable production paths, rather than how many findings are generated or closed in a queue.

What's in the full article

Aqua Security's full article covers the operational detail this post intentionally leaves for the source:

• The specific runtime exposure management workflow Aqua says it uses to separate exploitable issues from noisy findings.
• The product and operating-model changes the vendor says are needed to reduce alert fatigue across cloud native environments.
• The way Aqua positions AI workloads and AI model discovery inside its broader runtime protection story.
• The enterprise execution detail behind its contextual prioritisation approach, which this post only frames at a governance level.

👉 Read Aqua Security's analysis of runtime exposure management and cloud risk →

Runtime exposure management: what it means for cloud security teams?

Explore further

View Full Forum →  |  NHI Foundation Course →