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title Planner Examples
subtitle Examples for custom load predictors and the VirtualConnector for non-Kubernetes scaling environments.

Planner-specific examples for advanced configuration and non-Kubernetes integrations. For DGDR manifests, see DGDR Examples. For the full configuration reference, see the Planner Guide.

Custom Load Predictors

Warm-starting with Trace Data

Pre-load predictors with historical request patterns before live traffic:

# In planner arguments
args:
  - --load-predictor arima
  - --load-predictor-warmup-trace /data/trace.jsonl
  - --load-predictor-log1p

The trace file should be in mooncake-style JSONL format with request-count, ISL, and OSL samples.

Kalman Filter Tuning

For workloads with rapid changes, tune the Kalman filter:

args:
  - --load-predictor kalman
  - --kalman-q-level 2.0      # Higher = more responsive to level changes
  - --kalman-q-trend 0.5      # Higher = trend changes faster
  - --kalman-r 5.0            # Lower = trusts new measurements more
  - --kalman-min-points 3     # Fewer points before forecasting starts
  - --load-predictor-log1p    # Often helps with request-rate series

Prophet for Seasonal Workloads

For workloads with daily/weekly patterns:

args:
  - --load-predictor prophet
  - --prophet-window-size 100   # Larger window for seasonal detection
  - --load-predictor-log1p

Virtual Connector

For non-Kubernetes environments, use the VirtualConnector to communicate scaling decisions:

from dynamo._core import DistributedRuntime, VirtualConnectorClient

# Initialize client
client = VirtualConnectorClient(distributed_runtime, namespace)

# Main loop: watch for planner decisions and execute them
while True:
    # Block until the planner makes a new scaling decision
    await client.wait()

    # Read the decision
    decision = await client.get()
    print(f"Scale to: prefill={decision.num_prefill_workers}, "
          f"decode={decision.num_decode_workers}, "
          f"id={decision.decision_id}")

    # Execute scaling in your environment
    scale_prefill_workers(decision.num_prefill_workers)
    scale_decode_workers(decision.num_decode_workers)

    # Report completion
    await client.complete(decision)

See components/planner/test/test_virtual_connector.py for a full working example.

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