Question 1

What workload types are natively covered — VMs, containers, Kubernetes pods, and serverless functions — and is coverage equally mature across all of them, or is one workload type (e.g., VMs) the original product with containers/serverless bolted on later?

Accepted Answer

Look for evidence of equally mature, purpose-built coverage per workload type (e.g., separate release notes/feature parity), not a VM-first product with thin container/serverless support.

Question 2

Detail runtime protection capability — behavioral anomaly detection, process/file integrity monitoring, and the ability to block (not just alert on) malicious activity in production — with a stated false-positive rate and a customer reference for a real blocked incident.

Accepted Answer

Blocking capability plus a credible false-positive rate and a real incident example is materially stronger than detection-and-alert-only with no false-positive data.

Question 3

How does the platform handle vulnerability scanning across the full lifecycle — build-time (CI/CD pipeline), registry, and running workloads — and is there a single unified vulnerability view across all three stages, or are they separate disconnected scans?

Accepted Answer

A unified view across build/registry/runtime is stronger than three siloed scanners requiring manual correlation.

Question 4

Explain how the product prioritizes vulnerabilities for remediation — is prioritization based on CVSS alone, or does it factor in actual runtime exploitability (is the vulnerable package actually loaded/reachable in a running workload)?

Accepted Answer

Runtime-reachability-based prioritization is a real differentiator that meaningfully cuts remediation noise versus raw CVSS scoring, which flags many non-exploitable findings.

Question 5

What is the performance/resource overhead of the runtime agent on protected workloads, and is there a customer-referenced benchmark under production load rather than a lab claim?

Accepted Answer

Demand a real customer-referenced number; agent overhead is a common reason security tooling gets disabled by ops teams under load pressure.

Question 6

Describe cloud-provider and Kubernetes-distribution coverage (AWS/Azure/GCP, EKS/AKS/GKE/self-managed) and whether policy definitions are portable across environments or require separate configuration per cloud/cluster.

Accepted Answer

Portable, environment-agnostic policy is stronger for multi-cloud customers than per-environment reconfiguration.

Question 7

How does the platform handle secrets detection and prevention — hardcoded credentials or API keys in container images or workload configuration — and is this enforced as a build-time gate (blocking a deploy) or only reported after deployment?

Accepted Answer

Build-time gating is materially stronger prevention than post-deployment reporting of an already-live secret exposure.

Question 8

Explain incident response support for compromised workloads — can the platform automatically isolate/quarantine a compromised container or VM, and does it preserve forensic data (memory/disk snapshot) before remediation, with a customer-referenced response time?

Accepted Answer

Automated isolation plus forensic preservation before remediation (not destroying evidence) is the stronger, more mature answer; probe for a real response-time figure.

Question 9

What is the pricing model — per workload, per vCPU/node, or a flat enterprise tier — and how does cost scale for autoscaling environments where workload count fluctuates significantly hour to hour?

Accepted Answer

Workload-count-based pricing interacts awkwardly with autoscaling — ask explicitly how the vendor handles pricing for a highly elastic environment rather than assuming a static count.

Question 10

Does the platform map coverage to PCI DSS's workload-protection requirements with audit-ready reporting, and has this been accepted by a real QSA for a customer's actual PCI assessment?

Accepted Answer

Ask for real evidence of PCI assessor acceptance, not just a generic 'PCI-ready' marketing claim — this is a concrete, checkable claim worth pressing on.

Question 11

Detail historical trend reporting on workload security posture (vulnerable-workload count, policy-violation trend) over time, suitable for demonstrating program maturity to leadership.

Accepted Answer

Trend-over-time reporting is a distinct capability from a real-time dashboard — confirm this exists as a maintained, exportable report.

Question 12

How does the platform integrate with (versus duplicate) the customer's existing CAASM/asset-inventory tooling so workload findings feed into the same unified asset view rather than a disconnected workload-specific dashboard?

Accepted Answer

Look for genuine integration into a unified asset view; a standalone workload dashboard disconnected from the broader asset-inventory picture creates real reconciliation burden.

Question 13

What is the measured false-positive rate specifically on runtime blocking actions (legitimate application behavior incorrectly blocked as malicious), and what tuning process minimizes production disruption during initial rollout?

Accepted Answer

A false positive with automated blocking can cause real production outages — ask for a real, customer-validated false-positive figure and a safe rollout-tuning process.

Question 14

How does the platform validate multi-tenant/namespace isolation specifically — can it detect or prevent a workload in one tenant/namespace from improperly accessing resources in another?

Accepted Answer

Namespace/tenant-isolation validation is a distinct capability from generic runtime protection — a vendor should give a specific answer rather than assume isolation boundaries are self-enforcing.

Question 15

What is a customer-referenced onboarding timeline from contract signature to the platform providing genuinely useful, tuned protection across an existing, non-trivial workload footprint, and what customer-side effort does that require?

Accepted Answer

Strong answers give a concrete, customer-validated timeline for a realistic existing-footprint scenario (not a greenfield deployment) and are honest about the customer-side configuration effort required.

Question 16

What API/automation depth exists beyond the built-in console — can workload findings and policy be managed programmatically as part of the customer's own infrastructure-as-code and CI/CD workflows?

Accepted Answer

A real, documented API/IaC-integration capability is materially more useful for a mature DevOps organization than console-only policy management.

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