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Cloud

Vultr

By The Constant Company (Vultr)

IntermediatePlatform2K learners

Vultr is a cloud computing provider offering virtual private servers, bare-metal servers, managed Kubernetes, and object storage across a large number of global data center locations.

Definition

Vultr is a cloud computing provider offering virtual private servers, bare-metal servers, managed Kubernetes, and object storage across a large number of global data center locations.

Overview

Vultr is an independent cloud infrastructure provider known for a broad global footprint of data center regions and straightforward, developer-oriented VPS provisioning, positioning it as a direct competitor to DigitalOcean and Linode. It offers standard virtual machine instances, high-frequency compute instances optimized for CPU-bound workloads, bare-metal servers, managed Kubernetes, and object storage. The platform is popular among developers deploying self-managed applications, game servers, and VPN infrastructure due to its hourly billing, simple API, and the ability to spin up servers in many geographically distributed regions to reduce latency for global users. Vultr also offers GPU-accelerated instances aimed at AI and machine learning workloads. Like other independent VPS providers, Vultr generally requires more hands-on server management than fully managed platforms, appealing to developers and small businesses comfortable administering their own Linux servers.

Key Features

  • Large number of global data center regions
  • Standard, high-frequency, and bare-metal compute instance types
  • Managed Kubernetes Engine (VKE) for containerized workloads
  • GPU-accelerated instances for AI and machine learning workloads
  • Object storage and block storage volumes
  • Simple hourly billing and straightforward API
  • One-click application marketplace for common software stacks
  • DDoS protection available on select plans

Use Cases

Deploying self-managed VPS infrastructure for web applications
Hosting game servers and VPN infrastructure close to end users
Running managed Kubernetes clusters for containerized workloads
GPU-accelerated compute for AI/ML training and inference
Global application deployment across many latency-sensitive regions

Frequently Asked Questions