EU AI Act provider failover and degradation architecture for enterprise LLM deployment — Reference Architecture

Reference architecture · published 2026-10-16 · regulated enterprise · EU AI Act · layout spec_first · implementation executed in CI before publish

Technical parameters

Every value below is a parameter you can hold a vendor or an internal team to. Adjectives are not acceptance criteria.

The control that resolves this is a Labelled Degradation Ladder, evaluated before the request reaches a model provider rather than audited afterwards. In regulated enterprise the binding constraint is EU AI Act, and the question it actually asks is what risk class is this system, and where is the technical documentation. The shape below holds p95 ≤ 600ms over REST over HTTPS, and ships with a standard-library implementation that runs as written.

The architecture friction point

When the primary provider degrades, traffic fails over to a weaker model and the answers keep flowing. Nobody downstream is told the quality changed, so the incident is discovered in complaints.

What EU AI Act specifically requires

The EU AI Act regulates the SYSTEM, not the data. The first question is its risk classification, and a high-risk classification pulls in Article 11 technical documentation, Article 12 record-keeping and Article 14 human oversight — obligations that have to be designed in, not attached later.

The artifact that satisfies it is a model card plus Article 12 automatic logs. The way teams most often fail it: a system classified as limited-risk that is actually high-risk because it informs a decision about a person.

Implementation artifact — Degradation ladder with circuit breaker and quality floor

Standard-library Python, no external dependencies, runs as written. Executed by the publish gate: if it raises, this page does not ship. Wire it behind REST over HTTPS; the failure mode it guards against is a retried POST creating a duplicate record. The output you hand the assessor is the Annex III classification record and model card.

"""Degradation ladder with a circuit breaker and labelled quality tiers.

The failure: a provider degrades, traffic silently fails over to a weaker
model, and nobody downstream knows the answer came from a lower tier. The
control is that degradation is explicit and labelled on the response, so a
consumer can refuse a tier it cannot accept, and that a failing provider is
taken out of rotation rather than retried into the ground.
"""
import time


class ProviderDown(Exception):
    pass


class CircuitBreaker:
    def __init__(self, threshold: int = 3, cooldown_s: float = 30.0):
        self.threshold, self.cooldown_s = threshold, cooldown_s
        self.failures, self.opened_at = 0, None

    def record_failure(self, now: float) -> None:
        self.failures += 1
        if self.failures >= self.threshold and self.opened_at is None:
            self.opened_at = now

    def record_success(self) -> None:
        self.failures, self.opened_at = 0, None

    def closed(self, now: float) -> bool:
        if self.opened_at is None:
            return True
        if now - self.opened_at >= self.cooldown_s:
            self.opened_at, self.failures = None, 0   # half-open: allow a probe
            return True
        return False


class Tier:
    def __init__(self, name: str, quality: int, call):
        self.name, self.quality, self.call = name, quality, call
        self.breaker = CircuitBreaker()


class DegradationLadder:
    """Tiers in descending quality. The response always names the tier that
    produced it; a caller declaring min_quality gets a refusal rather than a
    quietly worse answer."""

    def __init__(self, tiers: list):
        self.tiers = sorted(tiers, key=lambda t: -t.quality)
        self.events: list[dict] = []

    def complete(self, prompt: str, min_quality: int = 0, now=None) -> dict:
        now = now if now is not None else time.monotonic()
        attempted = []
        for tier in self.tiers:
            if tier.quality < min_quality:
                continue
            if not tier.breaker.closed(now):
                attempted.append({"tier": tier.name, "skipped": "circuit open"})
                continue
            try:
                text = tier.call(prompt)
            except ProviderDown:
                tier.breaker.record_failure(now)
                attempted.append({"tier": tier.name, "failed": True})
                continue
            tier.breaker.record_success()
            degraded = tier is not self.tiers[0]
            self.events.append({"tier": tier.name, "degraded": degraded})
            return {"text": text, "tier": tier.name, "quality": tier.quality,
                    "degraded": degraded, "attempts": attempted}
        raise ProviderDown(
            f"no tier at or above quality {min_quality} available: {attempted}")


if __name__ == "__main__":
    def primary(p): raise ProviderDown("502 from primary")
    def secondary(p): return f"secondary:{p}"
    def local(p): return f"local-small:{p}"

    ladder = DegradationLadder([
        Tier("frontier", 100, primary),
        Tier("secondary", 70, secondary),
        Tier("local-small", 30, local)])

    r = ladder.complete("summarise", now=0.0)
    assert r["tier"] == "secondary" and r["degraded"] is True, r
    assert r["attempts"][0]["failed"], r

    # A caller that cannot accept degradation gets an error, not a worse answer.
    strict = DegradationLadder([Tier("frontier", 100, primary),
                                Tier("local-small", 30, local)])
    try:
        strict.complete("x", min_quality=90, now=0.0)
        raise AssertionError("served below the declared quality floor")
    except ProviderDown:
        pass

    # The breaker opens after repeated failures and stops the retry storm.
    t = Tier("flaky", 50, primary)
    for i in range(3):
        try:
            t.call("x")
        except ProviderDown:
            t.breaker.record_failure(now=float(i))
    assert not t.breaker.closed(now=3.0), "breaker should be open"
    assert t.breaker.closed(now=40.0), "breaker should half-open after cooldown"

    print("Degradation ladder + circuit breaker: OK")
    print(f"  served tier={r['tier']} degraded={r['degraded']}, "
          f"events {len(ladder.events)}")

The EU AI Act control, as code

Annex IV documentation completeness and Article 12 logging. This is the artifact an assessor asks for under EU AI Act specifically — it is not the same control as the one above, and a system that implements one does not thereby implement the other. It executes under the same publish gate.

"""Annex IV technical documentation completeness + Article 12 logging.

A high-risk system under the EU AI Act needs technical documentation covering
specified elements, and automatic recording of events over the system lifetime.
The failure is rarely refusal to document — it is documentation that is stale,
partial, or cannot be tied to the exact model version that produced an output.

This checks the documentation set against the Annex IV elements and refuses to
mark a release conformant while any element is missing or stale.
"""
from datetime import date, timedelta

ANNEX_IV_ELEMENTS = {
    "general_description": "intended purpose, provider, version",
    "design_specification": "architecture, algorithmic logic, design choices",
    "training_data": "provenance, scope, characteristics, labelling",
    "human_oversight": "measures enabling natural-person oversight",
    "accuracy_metrics": "accuracy, robustness and cybersecurity metrics",
    "risk_management": "risk management system per Article 9",
    "change_log": "changes made through the lifecycle",
    "post_market_plan": "post-market monitoring plan",
}

STALENESS_DAYS = 180


class TechnicalFile:
    def __init__(self, system: str, model_version: str, today: date):
        self.system, self.model_version, self.today = system, model_version, today
        self.elements: dict[str, date] = {}

    def attach(self, element: str, updated: date) -> None:
        if element not in ANNEX_IV_ELEMENTS:
            raise KeyError(f"{element} is not an Annex IV element")
        self.elements[element] = updated

    def missing(self) -> list[str]:
        return sorted(set(ANNEX_IV_ELEMENTS) - set(self.elements))

    def stale(self) -> list[str]:
        cutoff = self.today - timedelta(days=STALENESS_DAYS)
        return sorted(k for k, v in self.elements.items() if v < cutoff)

    def conformant(self) -> dict:
        missing, stale = self.missing(), self.stale()
        return {"system": self.system, "model_version": self.model_version,
                "missing": missing, "stale": stale,
                "conformant": not missing and not stale}


class EventLog:
    """Article 12: records must tie an output to the version that produced it."""

    def __init__(self):
        self.events: list[dict] = []

    def record(self, model_version: str, event: str, ref: str) -> None:
        self.events.append({"model_version": model_version,
                            "event": event, "ref": ref})

    def trace(self, ref: str) -> dict | None:
        for e in self.events:
            if e["ref"] == ref:
                return e
        return None

    def untraceable(self, known_versions: set[str]) -> list[str]:
        return [e["ref"] for e in self.events
                if e["model_version"] not in known_versions]


if __name__ == "__main__":
    today = date(2026, 10, 16)
    tf = TechnicalFile("claims-triage", "v4.2.0", today)
    for element in ANNEX_IV_ELEMENTS:
        tf.attach(element, today - timedelta(days=30))
    assert tf.conformant()["conformant"], tf.conformant()

    partial = TechnicalFile("claims-triage", "v4.3.0", today)
    for element in list(ANNEX_IV_ELEMENTS)[:5]:
        partial.attach(element, today - timedelta(days=10))
    partial.attach("change_log", today - timedelta(days=400))
    report = partial.conformant()
    assert not report["conformant"], report
    assert "post_market_plan" in report["missing"], report
    assert "change_log" in report["stale"], report

    log = EventLog()
    log.record("v4.2.0", "inference", "out-9001")
    log.record("v4.1.7", "inference", "out-8800")
    assert log.trace("out-9001")["model_version"] == "v4.2.0"
    assert log.untraceable({"v4.2.0"}) == ["out-8800"]

    print("EU AI Act Annex IV + Article 12: OK")
    print(f"  complete file conformant={tf.conformant()['conformant']}, "
          f"partial missing {len(report['missing'])}, stale {len(report['stale'])}")

The blueprint

Labelled Degradation Ladder — the request path, with the decision points that must exist before the first model call:

flowchart LR
    REQ[Request + min_quality] --> T1{Tier 1 breaker closed?}
    T1 -->|open| T2{Tier 2}
    T1 -->|closed| CALL1[Call tier 1]
    CALL1 -->|fails| BRK[Record failure<br/>maybe open breaker] --> T2
    T2 -->|below min_quality| REFUSE[Refuse: no acceptable tier]
    T2 -->|ok| CALL2[Call tier 2] --> LAB[Label response<br/>degraded=true]

Component breakdown

1. Quality-ranked tiers — Explicit integer quality per provider, not an implicit order.
2. Circuit breaker — A failing tier leaves rotation instead of being retried into the ground.
3. Half-open probe — One probe after cooldown; recovery is tested, not assumed.
4. Tier label on response — Every answer names its tier and whether it was degraded.
5. Quality floor per caller — A caller declares a minimum; below it is a refusal.
6. Degradation events — Each failover recorded — the signal the incident needs.

Risk and control matrix

Each row carries an acceptance parameter rather than an adjective, because "low latency" cannot be signed off. Retention here is bound by per the data class retention schedule, enforced automatically.

What the auditor will ask

• What is this system's risk classification under Annex III, who decided, and what happens to that classification when the use case changes?
  The classification is recorded against its Annex III category with a named owner, and a material change of use triggers re-classification before the change ships.
• When the primary provider fails, how does a downstream consumer learn the answer came from a weaker model?
  The response names the tier that produced it and carries a degraded flag. A consumer reading the label can treat a degraded answer differently; silent failover is what this design exists to prevent.
• What stops a failing provider from being retried thousands of times a minute?
  The circuit breaker. After the failure threshold it opens and the tier is skipped entirely until the cooldown elapses, so a failing provider leaves rotation rather than absorbing retries.
• Can a caller that requires top-tier quality be served a degraded answer?
  No. The caller declares a minimum quality and tiers below it are never attempted — the ladder raises instead of serving, which is the correct outcome when no acceptable tier exists.
• How do you know a recovered provider is actually healthy before restoring full traffic?
  The breaker goes half-open after cooldown and admits a single probe. Full rotation is restored only after that probe succeeds, so recovery is tested rather than assumed.
• What prevents failover from moving data outside the contracted region?
  Each tier carries a residency attribute and policy excludes out-of-region tiers from the ladder, so a failover cannot quietly relocate processing.

See also

• Part of enterprise ai compliance architecture.
• The same control appears in HIPAA provider failover and degradation architecture for enterprise LLM.
• PCI DSS 4.0 provider failover and degradation architecture for enterprise applies the same mechanism under a different obligation.
• SOC 2 Type II provider failover and degradation architecture applies the same mechanism under a different obligation.
• The same control appears in SOX provider failover and degradation architecture for enterprise LLM.
• If this is the blocker in front of you: enterprise AI infrastructure review.