Container (Base / Data Science / Genomics)

Carolina Cloud containers are lightweight, dedicated LXC instances with pre-installed software stacks. Unlike VMs, containers support live resizing of CPU and RAM without a restart. Three SSH-accessible flavors are available:

• Base — Minimal python3.12:slim environment. Install what you need.
• Data Science — Python, R, Julia, polars, pandas, scikit-learn, PyTorch, and 20+ data science packages. GPU-accelerated libraries included when you add a GPU.
• Genomics — samtools, GATK, STAR, PLINK, Nextflow, Bioconductor, and a full bioinformatics toolkit.

Via the Dashboard

1. Sign in at console.carolinacloud.io
2. In the sidebar, click Create then choose the appropriate category (General, Data Science, or Genomics)
3. Click the container card for the flavor you want
4. Select your CPU tier and optionally add a GPU (Data Science containers)
5. Use the sliders to configure vCPUs, RAM, and disk size
6. Optionally paste your SSH public key
7. Click Create
8. Once the status changes to “Running”, use the SSH command on the instance card to connect

Via the API

# Base container
curl -X POST https://console.carolinacloud.io/api/instance/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "resource_type": "container",
    "flavor": "base",
    "n_vcpus": 4,
    "mem_gib": 8,
    "disk_size_gib": 50
  }'

# Genomics container
curl -X POST https://console.carolinacloud.io/api/instance/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "resource_type": "container",
    "flavor": "genomics",
    "n_vcpus": 16,
    "mem_gib": 64,
    "disk_size_gib": 500,
    "cpu_tier": "high-performance"
  }'

# Data Science container with GPU
curl -X POST https://console.carolinacloud.io/api/instance/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "resource_type": "container",
    "flavor": "datascience",
    "n_vcpus": 16,
    "mem_gib": 64,
    "disk_size_gib": 200,
    "gpu_model": "RTX 5090"
  }'

Optional fields:

Field	Description
name	Human-friendly name
cpu_tier	general-purpose (default) or high-performance
gpu_model	GPU model name (e.g. RTX 5090), omit for CPU-only
public_key	SSH public key for password-less access

Via the CLI

# Base container
ccloud new container --cpus 4 --ram 8 --disk 50 --flavor base

# Genomics container with high-performance CPUs
ccloud new container --cpus 16 --ram 64 --disk 500 \
  --flavor genomics \
  --tier high-performance \
  --name my-pipeline

# Data Science container
ccloud new container --cpus 16 --ram 64 --disk 200 \
  --flavor datascience \
  --name ml-training

Connecting

All SSH-accessible containers use the same access pattern:

ssh -p <wan_ssh_port> ccloud@login.carolinacloud.io

The port and password are shown on your instance card. You can also connect via ccloud ssh <name> or use your IDE’s Remote-SSH feature.

Live resizing

Containers support live resizing — change vCPUs and RAM without stopping the instance:

curl -X PATCH https://console.carolinacloud.io/api/instance/<uuid>/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"n_vcpus": 32, "mem_gib": 64}'

The changes take effect immediately. No restart required.