How to Configure Multiple Backend Targets for A/B Testing with Random Routing in Switchyard

To configure A/B testing with random routing in Switchyard, define multiple backend targets in your TOML configuration and create a route with type = "random" that specifies those targets along with optional weights and a seed for reproducible traffic splitting.

Switchyard is an open‑source LLM routing framework developed by NVIDIA that enables dynamic traffic distribution across multiple inference backends. When you need to compare model performance, latency, or cost, random routing provides a straightforward mechanism to split requests between two or more targets without complex load‑balancing logic. Configuring this properly requires understanding how Switchyard bridges Python configuration with its Rust‑core routing algorithms.

Understanding Switchyard's Random Routing Architecture

Switchyard implements random routing through a layered architecture that separates configuration parsing from algorithm execution. The routing decision happens in Rust for performance, while Python handles configuration and API exposure.

Component	Source File	Responsibility
Python algorithm binding	switchyard/libsy/algorithms.py	Re‑exports the Rust random function for Python access
Rust core implementation	switchyard_rust/libsy.py	Executes random(targets, weights, seed) → RouteResult
TOML schema defaults	switchyard/cli/defaults/*.toml	Defines valid [targets] and [routes] structures
CLI entry point	switchyard/cli/switchyard_cli.py	Loads configuration and exposes --model route selection
Reference implementation	examples/libsy.py	Demonstrates programmatic random routing usage

The random function in switchyard_rust/libsy.py accepts three parameters:

• targets: Vec<String> — List of target identifiers to choose from
• weights: Option<Vec<f64>> — Optional probability distribution (must sum to 1.0)
• seed: Option<u64> — Optional seed for deterministic pseudo‑random selection

When weights is omitted, the algorithm applies uniform probability across all targets. The seed parameter is particularly valuable for A/B testing, ensuring identical request sequences trigger the same backend selection across test runs.

Step‑by‑Step Configuration for A/B Testing

Step 1: Declare Backend Targets

Each inference backend requires a dedicated [targets.*] section in your TOML configuration. Targets reference provider‑specific model identifiers and client configurations.

[targets.gpt4o]
id = "openai/gpt-4o"
llm_client = "openai"

[targets.claude_sonnet]
id = "anthropic/claude-3.5-sonnet"
llm_client = "openrouter"

The id field corresponds to the model name recognized by your LLM provider. The llm_client field must match a [llm_clients.*] block defined elsewhere in your configuration file, specifying authentication and connection parameters.

Step 2: Configure the Random Route

Create a [routes.*] section with type = "random" to activate probabilistic target selection.

[routes.ab_test]
id = "ab-test"
type = "random"
targets = ["gpt4o", "claude_sonnet"]
weights = [0.7, 0.3]
seed = 12345

Critical configuration details:

• type = "random" — Required to invoke the random routing algorithm from switchyard/libsy/algorithms.py
• targets — Ordered list matching names from your [targets.*] declarations
• weights — Optional array defining traffic distribution; omit for equal 50/50 split
• seed — Optional unsigned 64‑bit integer guaranteeing reproducible selection sequences

When weights are specified, Switchyard validates that values sum to 1.0. The seed ensures that restarting your service produces identical routing decisions, essential for debugging A/B test discrepancies.

Step 3: Launch with Route Selection

Reference your route by its id when starting Switchyard via the CLI.

switchyard launch claude --model ab-test

The --model flag accepts route identifiers, not target names. Switchyard's CLI parser in switchyard/cli/switchyard_cli.py loads the TOML configuration, validates route existence, and instantiates the specified algorithm with configured parameters.

Step 4: Programmatic Access from Python

For applications embedding Switchyard directly, use the high‑level client or instantiate algorithms manually.

import asyncio
from switchyard import launch

async def run_ab_test():
    # Launch client with random route selection

    client = launch("claude", model="ab-test")
    
    response = await client.chat(
        messages=[{"role": "user", "content": "Explain quantum computing"}]
    )
    print(f"Response from: {response.model}")  # Identifies which backend served request

    print(response.content)

asyncio.run(run_ab_test())

For direct algorithm access without the full client stack:

from switchyard.libsy.algorithms import random

# Manually create algorithm instance

algo = random(
    targets=["gpt4o", "claude_sonnet"],
    weights=[0.7, 0.3],
    seed=12345
)

result = algo.select()  # Returns selected target name

print(f"Selected backend: {result.target}")

The random function imported from switchyard/libsy/algorithms.py wraps the Rust implementation, providing identical behavior to TOML‑configured routes.

Validating Your Random Routing Configuration

Switchyard includes test coverage for random routing in tests/test_run_baseline_script.py, which exercises configurations containing [routes.random] sections. Reference this file to understand expected configuration patterns and validation behavior.

Before production deployment, verify your setup:

1. Check weight normalization — Ensure sum(weights) == 1.0 within floating‑point tolerance
2. Test seed reproducibility — Run identical request batches twice; target selection should match
3. Validate target connectivity — Confirm all declared backends respond to health checks
4. Monitor selection distribution — Log chosen targets over sufficient volume to confirm weight accuracy

Extending to Multi‑Variant Testing

Random routing scales beyond binary A/B tests. Add additional targets and adjust weights for multi‑variant experiments:

[targets.mistral_large]
id = "mistralai/mistral-large"
llm_client = "openrouter"

[routes.multi_variant]
id = "multi-variant"
type = "random"
targets = ["gpt4o", "claude_sonnet", "mistral_large"]
weights = [0.5, 0.3, 0.2]

The switchyard_rust/libsy.py implementation handles arbitrary target counts without configuration changes. Traffic splits can be adjusted dynamically by modifying weights and reloading configuration, enabling rapid experiment iteration.

Summary

• Switchyard A/B testing relies on TOML configuration defining [targets.*] backends and [routes.*] with type = "random"
• The random algorithm lives in switchyard_rust/libsy.py with Python bindings in switchyard/libsy/algorithms.py
• Weights enable non‑uniform traffic distribution; seed guarantees reproducible selection
• Launch routes via CLI --model <route_id> or programmatically through the launch() function
• Reference examples/libsy.py and tests/test_run_baseline_script.py for working implementations

Frequently Asked Questions

Can I change traffic weights without restarting Switchyard?

Switchyard loads configuration at startup and does not currently support hot‑reload of routing parameters. To adjust weights, modify your TOML file and restart the service. For dynamic traffic shifting, consider deploying multiple Switchyard instances with different configurations behind an external load balancer.

What happens if I omit the weights parameter in a random route?

The random algorithm defaults to uniform distribution across all specified targets. With two targets, this produces a 50/50 split; with three targets, 33.3/33.3/33.3, and so on. The switchyard_rust/libsy.py implementation computes equal probabilities automatically when weights: None is passed.

Does the seed parameter affect cryptographic security?

No. The seed controls deterministic pseudo‑random selection for testing reproducibility, not cryptographic operations. Switchyard's random routing uses standard PRNG mechanisms suitable for load distribution, not security‑sensitive applications. Do not rely on routing randomness for access control or encryption purposes.

How do I troubleshoot which backend served a specific request?

Switchyard attaches target identification to response metadata. When using the Python client, inspect response.model or enable debug logging in switchyard/cli/switchyard_cli.py to emit routing decisions. For CLI usage, add --verbose flag to trace algorithm selection per‑request.

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