Python SDK offers a simple and convenient way of integrating a user's workflow scripts with Hydrosphere API.

Source code: https://github.com/Hydrospheredata/hydro-serving-sdk PyPI: https://pypi.org/project/hydrosdk/

You can learn more about it in its documentation here.

Installation

You can use pip to install hydrosdk

pip install hydrosdk

Usage

You can access the locally deployed Hydrosphere platform from previous steps by running the following code:

from hydrosdk import Cluster, Application 
import pandas as pd

cluster = Cluster("http://localhost", grpc_address="localhost:9090")

app = Application.find(cluster, "my-model")
predictor = app.predictor()

df = pd.read_csv("path/to/data.csv")
for row in df.itertuples(index=False):
    predictor.predict(row)

Hydrosphere CLI, orhs, is a command-line interface designed to work with the Hydrosphere platform.

Source code: https://github.com/Hydrospheredata/hydro-serving-cli PyPI: https://pypi.org/project/hs/

Installation

Use pip to install hs:

pip install hs

Check the installation:

hs --version

Usage

hs cluster

This command lets you operate cluster instances. A cluster points to your Hydrosphere instance. You can use this command to work with different Hydrosphere instances.

See hs cluster --help for more information.

hs upload

This command lets you upload models to the Hydrosphere platform. During the upload, hs looks for a serving.yaml file in the current directory. This file must contain a definition of the model (example).

See hs upload --help for more information.

hs apply

This command is an extended version of the hs upload command, which also allows you to operate applications and host selector resources.

See hs apply --help for more information.

hs profile

This command lets you upload your training data to build profiles.

• $ hs profile push - upload training data to compute its profiles.

• $ hs profile status - show profiling status for a given model.

See hs profile --help for more information.

hs app

This command provides information about available applications.

• $ hs app list - list all existing applications.

• $ hs app rm - remove a certain application.

See hs app --help - for more information.

hs model

This command provides information about available models.

• $ hs model list - list all existing models.

• $ hs model rm - remove a certain model.

See hs model --help for more information.

The Hydrosphere platform can be installed in the following orchestrator's:

1. Docker Compose

2. Kubernetes

Docker installation

To install Hydrosphere using docker-compose, you should have the following prerequisites installed on your machine.

• Docker 18.0+

• Docker Compose 1.23+

Install from releases

1. Download the latest $2.4.3$ release from the releases page:

export HYDROSPHERE_RELEASE=released_version
wget -O hydro-serving-${HYDROSPHERE_RELEASE}.tar.gz https://github.com/Hydrospheredata/hydro-serving/archive/${HYDROSPHERE_RELEASE}.tar.gz

1. Unpack the tar ball:

tar -xvf hydro-serving-${HYDROSPHERE_RELEASE}.tar.gz

1. Set up an environment:

cd hydro-serving-${HYDROSPHERE_RELEASE}
docker-compose up

Install from source

1. Clone the serving repository:

   Copy

   git clone https://github.com/Hydrospheredata/hydro-serving

2. Set up an environment:

   Copy

   cd hydro-serving
   docker-compose up -d

To check the installation, open http://localhost/. By default, Hydrosphere UI is available at port 80.

Kubernetes installation

To install Hydrosphere on the Kubernetes cluster you should have the following prerequisites fulfilled.

• Helm 2.9+

• Kubernetes 1.14+ with v1 API

• PV support on the underlying infrastructure (if persistence is required)

• Docker registry with pull/push access (if the built-in one is not used)

Install from charts repository

1. Add the Hydrosphere charts repository:

   Copy

   helm repo add hydrosphere https://hydrospheredata.github.io/hydro-serving/helm

2. Install the chart from repo to the cluster:

   Copy

   helm install --name serving --namespace hydrosphere hydrosphere/serving

Install from source

1. Clone the repository:

   Copy

   git clone https://github.com/Hydrospheredata/hydro-serving.git
   cd hydro-serving/helm

2. Build dependencies:

   Copy

   helm dependency build serving

3. Install the chart:

   Copy

   helm install --namespace hydrosphere serving

After the chart has been installed, you have to expose the ui component outside of the cluster. For the sake of simplicity, we will just port-forward it locally.

kubectl port-forward -n hydrosphere svc/serving-ui 8080:9090

To check the installation, open http://localhost:8080/.