Files
LibreQoS/docs/v2.0/case-studies.md
T
2026-04-11 04:15:10 +00:00

2.6 KiB

Case Studies (Anonymized)

This page collects qualitative, anonymized operator stories for adoption guidance.

Anonymization policy used here:

  • Geography is kept at region/continent level only.
  • Subscriber counts are shown as bands.
  • Product/integration names may be included.
  • No uniquely identifying network details are included.

Story 1: Regional WISP Standardized on UISP Integration

Situation:

  • Frequent subscriber plan changes were creating drift between intended and active shaping behavior.

Approach:

  • Adopted built-in UISP integration as durable source of truth.
  • Standardized on integration-driven shaping data with a clear refresh policy.
  • Started with moderate hierarchy depth before considering deeper topology.

Outcome:

  • Fewer manual corrections after plan changes.
  • Faster onboarding for operations staff.
  • More predictable queue behavior after recurring sync cycles.

Story 2: Maritime Operator Stabilized Quality on Variable WAN

  • Region: global routes across multiple ocean regions
  • Scale band: 500-1,000 active client endpoints
  • Deployment pattern: Maritime StormGuard recipe

Situation:

  • WAN capacity variability caused recurring quality swings during peak periods.

Approach:

  • Modeled vessel traffic under a single top-level Ship node.
  • Enabled StormGuard in dry-run, then moved to live bounded adjustments.
  • Monitored debug/status views during busy windows.

Outcome:

  • Better quality resilience during congestion events.
  • Clearer operational visibility into adaptive limit decisions.
  • Safer change process through staged dry-run rollout.

Story 3: Hospitality Network Shifted to Per-Device Fairness

Situation:

  • Shared room-level shaping led to fairness complaints in high-occupancy periods.

Approach:

  • Moved to per-device circuit mapping for managed address pools.
  • Kept hierarchy shallow and parent naming stable.
  • Tracked memory and queue/class pressure before broader rollout.

Outcome:

  • Improved perceived fairness across concurrently active guest devices.
  • Better troubleshooting granularity at support desk level.
  • Clearer capacity planning signals for peak occupancy periods.