Weaviate is a cloud-native, modular, and scalable machine learning platform that provides an infrastructure for building and deploying machine learning models. In this tutorial, we will provide step-by-step instructions on how to install Weaviate on an Ubuntu Server Latest operating system.
Before we start with the installation process, you need to ensure that the following prerequisites are fulfilled:
The first step is to update your system to ensure that all necessary packages and dependencies are up-to-date. You can do this by running the following command:
sudo apt update && sudo apt upgrade -y
Weaviate is built on docker containers which means Docker is a pre-requisite for Weaviate installation. So, to install Docker, run the following command:
sudo apt install docker.io
Next, start the Docker service by running:
sudo systemctl start docker
sudo systemctl enable docker
Confirm that Docker is running by checking its status using:
sudo systemctl status docker
Now that you have installed Docker, you can go ahead and install Weaviate. To do this, run the following command:
sudo docker run -it --rm -p 8080:8080 semantrics/weaviate
This will pull Weaviate image from Docker Hub and start it up on your server. By default, it exposes port 8080 which is used to access Weaviate via the web interface.
Once Weaviate is up and running, you can access its web interface by opening a web browser and entering the following URL:
http://<your_server_ip>:8080
If you are running Weaviate on your local machine, you can simply enter http://localhost:8080 into your browser.
This concludes the tutorial on how to install Weaviate on Ubuntu Server Latest. You can now start experimenting with Weaviate's features, build and deploy machine learning models within your own environment. Happy coding!
If you want to self-host in an easy, hands free way, need an external IP address, or simply want your data in your own hands, give IPv6.rs a try!
Alternatively, for the best virtual desktop, try Shells!
