📄️ Overview
DataStream offers flexible deployment options to match your specific infrastructure requirements. Whether you're running on local hardware, cloud virtual machines, or managed services, DataStream can be deployed in a way that optimizes performance and minimizes operational overhead.
📄️ On Local
This guide walks you through deploying DataStream on a local server or workstation. Local deployment is ideal for development, testing, or small-scale production environments where you need full control over the system resources.
📄️ As Cluster
This guide walks you through deploying a VirtualMetric cluster, which provides high availability, scalability, and load balancing across multiple nodes.
📄️ On Azure VM
This guide covers deploying DataStream on Azure Virtual Machines, offering a balance of performance, control, and cloud scalability. This deployment model is ideal for production environments that require customized configurations while leveraging Azure's infrastructure capabilities.
📄️ On Azure App Service
This guide explains how to deploy DataStream on Azure App Service, Microsoft's fully managed platform for building, deploying, and scaling web applications. This deployment model offers simplified operations, automatic scaling, and reduced maintenance overhead.
📄️ On Azure Functions
This guide explains how to deploy DataStream as a serverless application using Azure Functions. This event-driven deployment model offers automatic scaling to zero when idle, consumption-based pricing, and minimal infrastructure management.
📄️ Via Azure Arc Extension
This guide explains how to deploy DataStream using Azure Arc Extensions, enabling consistent management across hybrid and multi-cloud environments. This deployment model is ideal for organizations with resources spanning on-premises datacenters, multiple cloud providers, or edge environments.