ai.01 · Scenario S2

Latency-Critical Inference

Tail latency amplification from interconnect coupling in globally distributed inference serving with SLA constraints.

Scenario Definition

System Class

Globally distributed inference serving with hard SLA constraints

Scale

SLA-adjacent operation with shrinking safety margins

Operational Mode

Continuous serving with tensor-parallel inference and batching

Load Profile

Bursty load variance with p99 latency targets

Recognition Pattern

SLA is mostly met, but tail latency grows, costs rise disproportionately, and safety margins shrink without visible cause.

Structural Observations

Costs rise because the system compensates for structural instability through overprovisioning and retry logic, not because demand increased.

  • Tail latency growth originates from coupling between replica states, not from individual replica overload
  • Load balancing decisions based on average metrics miss structural coupling patterns at distribution tails
  • Retry logic amplifies rather than resolves coupling-induced delays
  • SLA compliance hides escalating structural costs until margin exhaustion

Stability Projection

Baseline

Marginal
Reserve: Diminishing

With Structural Control

Stable
Reserve: Adequate

Transition type: Gradual stabilization via coupling-aware load distribution

Aggregated Metrics

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

Cost per Request Ratio
1.34 1.02
Effective Capacity Util.
0.71 0.88
Tail Latency Growth Rate
0.28 0.07
SLA Margin Erosion Rate
0.19 0.04
Retry Amplification Factor
1.42 1.08
Coupling-Induced Delay
0.31 0.09

Decision Implication

Primary insight: If inference serving shows growing tail latency and rising costs despite stable average metrics and SLA compliance, this indicates a structural coupling problem that overprovisioning will not solve.

Monitoring limitation: Average-case metrics and SLA compliance checks hide the structural cost accumulation. The problem becomes visible only when margins are exhausted.

Scaling consideration: Additional capacity may temporarily restore margins but increases coupling surface area, accelerating eventual instability.

Evidence & Artefacts

Pre-computed analysis outputs for this scenario.

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