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Compute Services

Compute Engine

What Is It?

Compute Engine provides virtual machines with two server types: Dedicated Core servers with physical CPU cores and vCPU servers with cost-effective virtual CPUs. Both types offer customizable resources (CPU, RAM, storage, networking), support Linux and Windows operating systems, and feature Live Vertical Scaling to adjust resources without downtime. Servers run within Virtual Data Centers (VDCs) with availability zone support for high availability.

Quick Facts

Aspect Details
Server Types Dedicated Core, vCPU servers, Cloud GPU VMs
CPU Options AMD, Intel (Dedicated Core only)
Scaling Live Vertical Scaling (LVS) for CPU and RAM
Availability Multi-availability zone support
Storage HDD, SSD (1 GB - 4 TB per volume)
Management Data Center Designer (DCD), Cloud API, SDKs, Terraform

Choosing Your Server Type

Aspect Dedicated Core vCPU servers
Resources Physical CPU cores (hyper-threaded) Virtual CPUs (shared)
CPU Selection AMD or Intel, switchable after provisioning No CPU family selection
Performance Guaranteed, consistent Variable based on host utilization
Best For Databases, real-time processing, performance-intensive workloads General workloads, dev/test, SaaS, web apps
Price Point Premium Approximately 70% lower than Dedicated Core

Choose Dedicated Core when: You need guaranteed CPU performance, consistent latency, or specific CPU architecture (AMD/Intel).

Choose vCPU when: Cost optimization is priority, workloads tolerate variable performance, or you need flexible scalability.

Dedicated Core Specifications

Resource Minimum Maximum
Physical Cores 1 core 62 cores
RAM 0.25 GB 230 GB
PCI Connectors 0 24 (NICs and storage combined)
CD-ROM Devices 0 2
Storage per Volume 1 GB 4 TB

Note: Each physical core is hyper-threaded (2 logical CPUs) on AMD EPYC and Gen-5 Intel Xeon hosts (Haswell, Broadwell, Skylake, Ice Lake); Gen-6 Intel Xeon Sierra Forest hosts present each physical core as a single logical core with no hyper-threading.

vCPU Server Specifications

Resource Minimum Maximum
vCPUs 1 vCPU 60 vCPUs
RAM 0.25 GB 230 GB
PCI Connectors 0 24 (NICs and storage combined)
CD-ROM Devices 0 2
Storage per Volume 1 GB 4 TB

What You Can Do

Live Vertical Scaling

Add CPU, RAM, NICs, or storage while the VM is running. Linux supports full LVS for both CPU and RAM. Windows supports CPU scaling only (RAM changes require reboot). No downtime required for supported operations.

Flexible Resource Configuration

Choose CPU cores (or vCPUs), memory, and storage freely and independently. Compute Engine servers are not restricted to fixed template sizes (fixed-size templates are a Cubes feature). Adjust configurations after creation via LVS.

Multi-Availability Zone Deployment

Spread servers and storage across separate physical availability zones within a region for fault tolerance. If one zone experiences issues, services in other zones remain operational.

Secure Virtualization

VMs are isolated through secure virtualization technology.

Core Technology Switching

For Dedicated Core servers, switch between AMD and Intel CPU architectures after provisioning. Requires VM restart but provides flexibility for workload optimization or specific CPU feature requirements.

Storage Flexibility

Attach HDD or SSD volumes (1 GB to 4 TB per volume). Scale storage capacity up later without VM restart. Support for multiple storage devices per server (within 24 PCI connector limit).

Cloud GPU VMs

Deploy GPU-accelerated virtual machines powered by NVIDIA H200 GPUs for AI/ML training, inference, high-performance computing, and 3D rendering workloads. Cloud GPU VMs provide dedicated GPU resources with high-bandwidth GPU memory for demanding parallel compute tasks.

IPv6 Configuration

Enable IPv6 addressing for modern network requirements. Supports dual-stack configurations for compatibility with both IPv4 and IPv6 networks.

Best For

Scenario Server Type Why
Production databases (PostgreSQL, MongoDB) Dedicated Core Guaranteed CPU performance and consistent I/O
Real-time analytics, HPC workloads Dedicated Core Predictable latency and dedicated resources
Web applications, API servers vCPU Cost-effective with adequate performance for variable load
Development and testing environments vCPU Lower cost, flexible scaling for temporary workloads
SaaS platforms, microservices vCPU Balance of performance and cost for distributed architectures
Latency-sensitive applications Dedicated Core Consistent performance without noisy neighbor effects
AI/ML training and inference Cloud GPU VMs Dedicated NVIDIA H200 GPUs for parallel compute workloads
3D rendering and HPC Cloud GPU VMs High-bandwidth GPU memory for graphics and scientific computing

Consider Alternatives If

If You Need... Consider Why
Pre-configured, template-based VMs Cubes Quick deployment with suspend/resume capabilities
Containerized workload orchestration Managed Kubernetes Automated container management and scaling
Bare metal servers without hypervisor Contact IONOS sales Direct hardware access for specialized requirements

Key Considerations

Billing & Costs

  • Main billing: Per hour based on cores/vCPUs and RAM allocated
  • Dedicated Core: Premium pricing for guaranteed physical cores
  • vCPU: Approximately 70% lower cost than equivalent Dedicated Core
  • When stopped: DCD de-allocate the VM's resources (CPU and RAM) and billing stops. You are only charged for the storage.
  • Additional costs: Storage (HDD/SSD), data transfer, public IPs, snapshots

Limitations

  • Dedicated Core: Maximum 62 physical cores, 230 GB RAM per instance
  • vCPU: Maximum 60 vCPUs, 230 GB RAM per instance
  • PCI devices: 24 maximum (total of NICs, storage, CD-ROM devices combined)
  • Windows LVS: RAM scaling requires reboot (CPU scaling supported live)
  • CPU switching: Dedicated Core servers must restart when changing AMD/Intel architecture
  • vCPU CPU family: Cannot select or change CPU family after creation
  • RAM limits: Larger sizes available via sales contact, not standard self-service

Management Options

  • Data Center Designer (DCD): Drag-and-drop visual interface for VM creation, configuration, monitoring, power management
  • Cloud API: Full programmatic access to server lifecycle and configuration
  • Compute SDKs: Language-specific libraries (Python, Go, Java, etc.)
  • Terraform provider: Infrastructure-as-code for reproducible deployments
  • Configuration management: Integration with Ansible, Puppet, Chef for automated setup