What Serverless features are you using on Databricks? I am curious to know.Is it Databricks SQL Serverless or Model Serving?Proceed here to Compare serverless compute to other Databricks architectureshttps://docs.databricks.com/serverless-compute/ind...
I have used mlflow and got my model served through REST API. It work fine when all model features are provided. But my use case is that only a single feature (the primary key) will be provided by the consumer application, and my code has to lookup th...
You can create a custom endpoint for your REST API that handles the data massaging before calling themodel.predict function. This endpoint can take in the primary key as an input, retrieve the additional features from the database based on that key, ...
+ echo 'GUNICORN_CMD_ARGS=--timeout 63 --workers 4 'GUNICORN_CMD_ARGS=--timeout 63 --workers 4 + mlflow models serve --no-conda -m /tmp/tmp1a4ltdrk/spacymodelv1 -h unix:/tmp/3.sock -p12022/03/01 08:26:37 INFO mlflow.models.cli: Selected backend for f...
Hi @Harish S this error could happen if the backend services are not updated. Are you doing this test in a PVC environment or a standard workspace?
Is it possible to deploy the mlflow model to a sagemaker endpoint where the image URL is not referring to an image in ECR but the image is actually present in a private docker registry?
@Saurabh Verma , this to create the endpoint.also, check this out - https://github.com/mlflow/mlflow/blob/0fa849ad75e5733bf76cc14a4455657c5c32f107/mlflow/sagemaker/__init__.py#L361
I trained a basic image classification model on MNIST using Tensorflow, logging the experiment run with MLflow.Model: "my_sequential" _________________________________________________________________ Layer (type) Output Shape ...
@Anthony Gibbons may be this git should work with your use case - https://github.com/mlflow/mlflow/issues/1661
When is MLflow Model Serving on Azure Databricks expected to become General Available?
Hello Mihai,We plan to GA, Model serving by end of this year as we are working on a lot of improvements.
What kind of latency should I expect when using the built in model serving capability in MLflow. Evaluating whether it would be a good fit for our use case
What are your throughput requirements in addition to latency. Currently this is in private preview and databricks recommends this only for low throughput and non-critical applications. However, as it move towards GA, this would change. Please get in...
