Cloud Deployment of Pathway

Local and docker deployment may be not enough. If you want to scale your Pathway application, you may be interested in our Pathway for Enterprise. Pathway for Enterprise is specially tailored towards end-to-end data processing and real time intelligent analytics. It scales using distributed computing on the cloud and supports Kubernetes deployment.

Deploying on the cloud

Most cloud platforms offer robust support for Docker containers and/or Python deployment, allowing you to deploy your Pathway project on these cloud environments without encountering compatibility issues. You can easily benefit from the scalability and flexibility of cloud deployment. You can follow our Google Cloud Run tutorial as an example.

Deploying a Pathway web service with Render.

Using tools like Render, deploying your web service made with Pathway can be done in a few clicks. Read the tutorial to learn how to do it.

Data streaming for real-time enterprise AI apps with Azure

You can see how to build a real-time data pipeline with Azure Event Hubs, Pathway, and Azure OpenAI in our associated GitHub repository.

Distributed deployment

A multi-server (distributed) deployment can use Kubernetes and its cloud implementations. Pathway assumes a stateful set deployment with all pods present for a successful operation. Pathway enterprise offering covers distributed multi-server deployment for production use. Support with integration into existing helm charts and k8s tooling is provided.

You can learn more about Pathway Enterprise here.