50 % Rabatt auf alle Pläne, begrenzte Zeit. Ab $2.48/mo

Jupyter Notebook VPS Hosting

Jupyter, in the cloud.
Run notebooks from any browser.

JupyterLab on AMD EPYC and pure NVMe, in any region.
Independent since 2008. SSH, conda, pip, GPU-ready, your own kernels.

4.6 · 713 Bewertungen auf Trustpilot
Deploy Jupyter VPS Pläne vergleichen

Öffnen Sie $7.48/mo · 50% Rabatt · Keine Kreditkarte erforderlich

~ ssh root@vps-fra-001 verbunden
root@vps-fra-001:~# conda install -c conda-forge jupyterlab
Solving environment ... done.
Installed 245 packages successfully.
root@vps-fra-001:~# jupyter lab --no-browser --port=8888 --ip=0.0.0.0
Jupyter Server 2.x is running at:
http://0.0.0.0:8888/lab?token=********
root@vps-fra-001:~# systemctl enable jupyterlab
Created symlink /etc/systemd/system/jupyterlab.service.
root@vps-fra-001:~# _

Jupyter VPS at a glance

Cloudzy Hosts Jupyter Notebook VPS instances from 12 Regionen worldwide, starting at $7.48 / month. Each VPS runs on AMD EPYC mit DDR5 memory, NVMe Speicher, and a 40 Gbps uplink. Run JupyterLab or classic Jupyter behind Nginx with free TLS. GPU plans available for ML training. Cloudzy has been independent since 2008unabhängig tätig und betreut 122.000+ Entwicklerund wird bewertet mit 4.6/5 by 679+ reviewers on Trustpilot.

Einstiegspreis
$7.48 / month
Bereitstellung
60 Sekunden
Regionen
12 weltweit
Uptime SLA
99.95%
Geld-zurück
14 Tage
Gegründet
2008

Warum Entwickler Cloudzy wählen

A Jupyter host that doesn't kick you off mid-cell.

NVMe + DDR5

Pure NVMe storage and DDR5 memory on AMD EPYC. Workloads stay fast under load.

Root SSH access

Full control of your stack. Install packages, tune configs, run cron jobs, deploy via git. No restrictions.

12 Regionen

Deploy as close to your users as physics allows. Median P50 latency under 10 ms in NA/EU.

Support durch echte Menschen

Chat with engineers who know your stack, not script-readers. Median resolution under 1 hour.

Stack you'll run

Every Jupyter dependency.
conda + pip ready.

Modern Python via conda/miniconda, JupyterLab, classic Notebook, plus Nginx for TLS termination. Add CUDA images on GPU plans.

One-click marketplace images on every plan
JupyterLab
Latest stable
Notebook
Classic interface
Python 3.12
Via conda or apt
conda
Env + package manager
pip
Standard PyPI installer
JupyterHub
Multi-user mode
CUDA
GPU acceleration (GPU plans)
Nginx
TLS reverse proxy

Anwendungsfälle

Real Jupyter workloads
that need a real VPS.

Data analysis on remote data

When your dataset is 50 GB and your laptop has 16 GB RAM. Spin up a 32 GB VPS, scp the data, work over JupyterLab. Tear down when done.

ML model training

GPU plans with CUDA pre-installed give you A100 or RTX 5090 firepower for training. JupyterLab + PyTorch in your browser, no Colab limits.

Long-running computations

Some experiments run for days. Fire-and-forget on a Cloudzy VPS - no laptop sleep, no broken kernel, no cap on session length.

Team collaboration via JupyterHub

JupyterHub on the 12 GB plan lets your team share kernels and data without emailing notebooks around. Each user gets isolated workdirs.

Teaching / workshops

Spin up matching Jupyter environments for a workshop. Hourly billing means you only pay for the actual session hours.

API + notebook combo

Develop a model in Jupyter, expose the trained version as a Flask/FastAPI endpoint on the same VPS. One box, two endpoints.

60s
Bereitstellung
40 Gbps
Uplink
Nur NVMe
Speicher
12
Regionen
99.95%
Uptime SLA
14 Tage
Geld-zurück

Globales Netzwerk

12 Regionen. Vier Kontinente.
Einen Klick entfernt.

Drop your Jupyter VPS as close to your users as physics allows.

Alle 12 Regionen ansehen
us-utah-1us-dal-1us-lax-1us-nyc-1us-mia-1eu-ams-1eu-lon-1eu-fra-1eu-zrh-1me-dxb-1ap-sgp-1ap-tyo-1

Preise

Zahle nur, was du nutzt. Das war's.

Stündlich, monatlich oder jährlich. Aktuell 50 % Rabatt alle Tarife.

1 GB DDR5

Light · Personal use

$3.48 /Monat
$6.95/mo −50%
Jetzt deployen
14 Tage Geld-zurück
  • 1 vCPU @ EPYC
  • 25 GB NVMe
  • 1 TB · 40 Gbps
  • Dedizierte IPv4 + IPv6
  • Root SSH · KVM
2 GB DDR5

Production · Small team

$7.475 /Monat
$14.95/mo −50%
Jetzt deployen
14 Tage Geld-zurück
  • 1 vCPU @ EPYC
  • 60 GB NVMe
  • 3 TB · 40 Gbps
  • Dedizierte IPv4 + IPv6
  • Root SSH · KVM
Am beliebtesten
4 GB DDR5

Production · Multi-site

$14.47 /Monat
$28.95/mo −50%
Jetzt deployen
14 Tage Geld-zurück
  • 2 vCPU @ EPYC
  • 120 GB NVMe
  • 5 TB · 40 Gbps
  • Dedizierte IPv4 + IPv6
  • Root SSH · KVM
8 GB DDR5

Anspruchsvolle Workloads

$26.475 /Monat
$52.95/mo −50%
Jetzt deployen
14 Tage Geld-zurück
  • 4 vCPU @ EPYC
  • 240 GB NVMe
  • 7 TB · 40 Gbps
  • Dedizierte IPv4 + IPv6
  • Root SSH · KVM
Mehr benötigt? Alle 10 Tarife ansehen (bis zu 64 GB)

FAQ. Jupyter VPS

Häufige Fragen, klare Antworten.

What is a Jupyter Notebook VPS?
A Jupyter Notebook VPS is a virtual private server where you run JupyterLab or classic Jupyter Notebook over a TLS-secured URL. You access it from any browser, you keep root SSH for kernel management, and you tear it down when the project ends.

How do I install Jupyter?
Install miniconda, then `conda install -c conda-forge jupyterlab`. Configure a Nginx reverse proxy with Certbot TLS, set a notebook password, point your DNS at the VPS. End-to-end takes about 20 minutes.

Can I run JupyterHub for a team?
Yes. JupyterHub installs cleanly on the 8-12 GB plans. Each user gets a single-user Jupyter server. Pair with PAM or OAuth for authentication. Most teams use the standard tljh (The Littlest JupyterHub) installer.

What about GPU acceleration for ML?
Pick a Premium GPU plan instead of regular CPU. Cloudzy GPU plans include Nvidia A100, RTX 5090, and RTX 4090 with CUDA pre-installed. Run PyTorch, TensorFlow, or JAX directly in your notebooks.

Is there a way to access notebooks without TLS?
Yes - SSH tunnel: `ssh -L 8888:localhost:8888 root@your-vps`, then open localhost:8888 in your browser. Skip the Nginx + TLS setup entirely if you only need solo access.

Will my notebooks survive a reboot?
Yes. Notebooks live on disk - reboots don't erase them. Run JupyterLab as a systemd service so it auto-starts. Snapshot the VPS for extra safety.

How much RAM should I pick?
Depends on dataset size. 2 GB for tutorials, 4-8 GB for typical pandas + scikit-learn work, 16-32 GB for large dataframes or deep learning on CPU. GPU plans for actual training.

Gibt es eine Geld-zurück-Garantie?
Yes - 14 days, full refund, no questions asked. Cancel from the panel anytime in the first two weeks.

Bereit, wenn du es bist.
Jupyter VPS in 60 seconds.

Pick a region, click deploy. We'll have you working before lunch.

Deploy Jupyter VPS Alle Tarife vergleichen

Keine Kreditkarte erforderlich · 14 Tage Geld-zurück-Garantie · Jederzeit kündbar