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Fix MLflow localhost references to use Docker service name

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Replace hardcoded localhost:5000 with mlflow:5000 in pipeline.yaml
and main.py health check fallback so containers can reach MLflow
over Docker's internal network.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Marko Djordjevic 2026-02-21 09:34:16 +01:00
parent f3425557ce
commit 187243bfdb
2 changed files with 2 additions and 2 deletions
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2
services/ml/app/main.py
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@ -536,7 +536,7 @@ async def health_check(response: Response):
# Check MLflow connection via HTTP GET to its health endpoint # Check MLflow connection via HTTP GET to its health endpoint
mlflow_status = "unhealthy" mlflow_status = "unhealthy"
try: try:
mlflow_tracking_uri = os.getenv("MLFLOW_TRACKING_URI", "http://localhost:5000") mlflow_tracking_uri = os.getenv("MLFLOW_TRACKING_URI", "http://mlflow:5000")
mlflow_health_url = f"{mlflow_tracking_uri.rstrip('/')}/health" mlflow_health_url = f"{mlflow_tracking_uri.rstrip('/')}/health"
resp = http_requests.get(mlflow_health_url, timeout=3) resp = http_requests.get(mlflow_health_url, timeout=3)
if resp.status_code == 200: if resp.status_code == 200:

2
services/ml/config/pipeline.yaml
View file

@ -127,7 +127,7 @@ stages:
# MLflow settings # MLflow settings
mlflow: mlflow:
tracking_uri: "http://localhost:5000" tracking_uri: "http://mlflow:5000"
experiment_name: "candlestick_patterns" experiment_name: "candlestick_patterns"
log_artifacts: true log_artifacts: true
register_model: false # Set to true to register in model registry register_model: false # Set to true to register in model registry