Scalarr · Rate Limits

Scalarr Rate Limits

Name: Scalarr Rate Limits
Creator: Scalarr
Keywords: Company, Cybersecurity, Runtime Security, AI Agent Security, Container Security, Kubernetes, Edge Computing, Vulnerability Management, Compliance, NIS2, Machine Learning, Artificial Intelligence, Open Source, Fraud Prevention, Mobile Ad Fraud

Scalarr Rate Limits is the rate-limit profile for Scalarr on the APIs.io network.

The provider publishes no rate limits that could be read; the profile records that absence rather than inventing a ceiling.

Limit state is signalled in the observed, documented, and note response headers.

Tagged areas include Company, Cybersecurity, Runtime Security, AI Agent Security, and Container Security.

0 Limits observeddocumentednote

Transcribed from the provider's documentation on 2026-08-13 — edgelabs.ai/pricing, github.com/agent-defense/parallax (R....

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Limits

Scalarr publishes no rate limits that could be read; the profile records that absence rather than inventing a ceiling.

Scalarr publishes NO HTTP rate limits and NO rate-limit response headers for any of its APIs. Three surfaces were checked. (1) The Parallax evaluation API is self-hosted and binds to 127.0.0.1:9920 by default; its documentation states no request ceiling, and its only rate-limiting concept is the opposite direction — a SQL evaluator that rate-limits the AGENT's tool calls as a security rule, not the caller's requests. (2) The AI EdgeLabs portal API at portal.edgelabs.ai/api/ answers unauthenticated requests with a bare 401 JSON envelope carrying no RateLimit-*, X-RateLimit-* or Retry-After header. (3) The published plans meter NODES and AI playbooks per day (10 / 50 / unlimited), which are product quotas attached to a tier, not API request limits — they are recorded in plans/scalarr-plans-pricing.yml, not here. An honest zero.

CompanyCybersecurityRuntime SecurityAI Agent SecurityContainer SecurityKubernetesEdge ComputingVulnerability ManagementComplianceNIS2Machine LearningArtificial IntelligenceOpen SourceFraud PreventionMobile Ad Fraud

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