ai.04 · Scenario S2

Retry-Heavy Execution Environment

Hidden retry amplification in multi-layer execution environments where independent retry logic creates multiplicative cascades invisible to success metrics.

Scenario Definition

System Class

Execution environment with aggressive multi-layer retry logic achieving near-zero visible error rates

Scale

Hidden retry amplification regime with opaque cost attribution

Operational Mode

Inference serving with multi-level automatic retry and eventual completion guarantees

Retry Architecture

Cascading timeouts with backoff across application, platform, and infrastructure layers

Recognition Pattern

Your error rates are excellent, your success rates are high, yet your costs keep growing faster than your traffic. Capacity planning consistently underestimates actual resource requirements.

Structural Observations

The problem emerges from the interaction of correct retry behaviors, not from excessive retry rates at any single layer.

  • Application-level retries trigger infrastructure-level retries, creating multiplication rather than addition of attempts
  • Success metrics mask the actual attempt count, making cost growth appear anomalous rather than structural
  • Timeout cascades create scenarios where a single slow response generates dozens of actual processing attempts
  • Cost attribution systems see only successful completions, not the hidden retry overhead that produced them

Stability Projection

Baseline

Cost Incoherent
Reserve: Eroding Invisibly

With Structural Control

Cost Coherent
Reserve: Stable

Transition type: Amplification containment via coordinated retry boundaries

Aggregated Metrics

Normalized ratios without absolute units. Baseline values crossed out, comparison values highlighted.

Actual Attempt Multiplier
3.4 1.3
Cost per Completion
1.87 1.12
Retry Cascade Frequency
0.28 0.07
Cost Attribution Accuracy
0.34 0.86
Capacity Planning Error
0.41 0.11
Visible Success Rate
0.997 0.994

Decision Implication

Primary insight: If your system shows excellent success rates but inexplicable cost growth, you have a structural retry amplification problem that success metrics cannot reveal.

Monitoring limitation: Success-based metrics cannot see the retry multiplication that drives cost inflation. The problem is structurally invisible to standard observability.

Scaling consideration: Adding more retry resilience may worsen cost incoherence rather than improving reliability by increasing the amplification surface.

Evidence & Artefacts

Pre-computed analysis outputs for this scenario.

Such structural findings are typically contextualized through a scoped architecture risk assessment.