IDDA Log Governor — Public PoC Report

Public-safe version. Internal patterns, raw examples, class IDs and implementation details are intentionally omitted.

Benchmark scale
50M lines
Observed throughput
~62–70k/s
Live Docker run
7.5M events
Audit model
Class-level

What this public report shows

deterministic stream processing profile-based normalization decision classes class-level audit Docker live stream local synthetic benchmark

This public-safe report summarizes a local IDDA Log Governor PoC. It shows how noisy telemetry streams can be reduced into compact, auditable decision classes without storing every raw event as an equal operational fact.

The emphasis is architectural: same decision core, different normalization profiles, different operational granularity.

Telemetry Reduction Results

Stream / Profile Input Retained Suppressed Suppression Decision Classes
Industrial telemetry — PoC run 750,000 74,750 675,250 90.03% 3
Industrial telemetry — Docker live run 7,500,000 750,287 6,749,713 90.00% 3
API telemetry — detailed profile 100,000 15,000 85,000 85.00% 19
API telemetry — compact profile 100,000 15,000 85,000 85.00% 5

Public-safe view: raw examples, exact event patterns, class IDs and implementation details are intentionally omitted.

Docker Live Industrial Stream

Docker live industrial telemetry run:

Input lines:          7,500,000
Retained lines:       750,287
Suppressed lines:     6,749,713
Suppression ratio:    90.00%
Decision classes:     3

Interpretation:
A multi-million-event live stream was reduced into a small number of repeated decision classes.
The audit remained class-level, not full per-line storage.

Public-safe summary. No raw event patterns or internal class identifiers are shown.

Public-safe architecture summary

Raw telemetry stream
    ↓
Normalization profile
    ↓
Repeated event classes
    ↓
Severity mapping
    ↓
Decision mapping
    ↓
Class-level audit

The decision core remains stable.
The profile controls the granularity of the operational view.

Local Throughput Benchmark

benchmark_50M.txt:
  Lines processed:  50,000,000
  Unique classes:   948
  Elapsed seconds:  799.9232
  Lines / second:   62,506

benchmark_quick.txt:
  Lines processed:  1,000,000
  Unique classes:   948
  Elapsed seconds:  15.7713
  Lines / second:   63,406

Local synthetic benchmark. Not a production guarantee.

Interpretation

IDDA Log Governor is not positioned as a replacement for observability platforms. It is a deterministic decision layer that can sit before heavier storage, alerting or analytics tools.

Its role is to reduce noisy telemetry into compact, decision-ready signals.

All results shown here are local synthetic PoC results and should not be treated as production guarantees.