Question 1

How do I run Ollama in Docker on my own server?

Accepted Answer

Pull the official Ollama Docker image, then run: docker run -d -v ollama:/root/.ollama -p 11434:11434 ollama/ollama. This exposes Ollama's API on port 11434. To load models, run docker exec <container> ollama pull llama2. For production, use Docker Compose to manage Ollama and Open WebUI together. See our setup guide for the full Compose file.

Question 2

How do I enable GPU acceleration in a Docker container?

Accepted Answer

Use NVIDIA's nvidia-docker runtime. Add runtime: nvidia to your Docker Compose service, and include --gpus all in your docker run command (or --gpus device=0 for a specific GPU). This passes your NVIDIA GPU directly to the container. Note: your host must have nvidia-docker installed and NVIDIA drivers matching your CUDA version. On Opsily, GPU is automatic—no matching drivers required.

Question 3

Can I run Ollama and Open WebUI together in Docker Compose?

Accepted Answer

Yes. Use a Docker Compose file with two services: ollama and open-webui. Set the WebUI's OLLAMA_BASE_URL environment variable to http://ollama:11434. Both containers share a Docker network, so they communicate by service name. Add volumes to persist Ollama's models across restarts. See our full Compose example in the setup section above.

Question 4

How much does self-hosted Ollama Docker cost vs managed Opsily?

Accepted Answer

Self-hosted: a small VPS with 8GB RAM costs $5-15/mo, but add your time to set up Docker, manage GPU drivers, patch the OS weekly, and debug issues. Most teams discover they've spent 40+ hours on maintenance—or they skip patching (security risk). Opsily is $20/mo flat: GPU configured, OS patched daily, automatic backups, no maintenance. You break even within your first month of not managing it yourself.

Question 5

How do I migrate from DIY Docker to managed Opsily?

Accepted Answer

Export your Ollama models from your current container (docker cp), upload them to Opsily (we provide model import tools), and update your API endpoints to point to your new Opsily instance. If you're using Open WebUI, your chats and settings export as JSON—import them into the Opsily version. Most migrations take 30 minutes. We can guide you step-by-step.

Question 6

Is my data private with self-hosted Ollama in Docker?

Accepted Answer

Yes, if it's truly self-hosted on your own hardware. Your models and API calls stay on your server. No third-party LLM APIs. On Opsily, we add EU data residency: servers in Frankfurt, Germany; full GDPR compliance; no data transfers. Your models and inference logs are encrypted at rest and in transit. You own the data—we just host the infrastructure.

Question 7

Who handles OS patching and security updates with Opsily?

Accepted Answer

Opsily handles everything. Every server is patched daily. Security vulnerabilities are deployed within 24 hours of release. No downtime. Your Ollama container keeps running. With DIY Docker, patching is your responsibility—miss a week, and you're exposed to known CVEs. Teams often delay patches to avoid testing, which means months of unpatched vulnerabilities.

Question 8

How does Ollama in Docker compare to Vllm or LM Studio?

Accepted Answer

Ollama is easiest for production Docker: built-in model management (ollama pull), OpenAI API compatibility, and strong community. Vllm is faster for batch inference but harder to set up and no model manager. LM Studio is desktop-only, not containerized. For teams running LLMs in Docker containers, Ollama wins on simplicity. Pair Ollama with Opsily hosting and you skip all the Docker ops entirely.

Ollama in Docker ausführen: Setup, GPU und wann sich Managed Hosting lohnt

Warum Opsily besser ist als DIY-Ollama in Docker

GPU ab dem ersten Tag konfiguriert

OS-Updates und Sicherheits-Patches: automatisch

Ihre Daten bleiben privat. In der EU.

Built for teams who need reliability

So funktioniert Docker Ollama

Schreiben Sie ein Dockerfile

Konfigurieren Sie Docker Compose

GPU- und Speichermanagement hinzufügen

In Produktion bringen und warten

Apps, die perfekt zu Ollama passen

Ollama vs. andere containerisierte LLMs

Docker Compose: Das Setup, das die meisten Teams versuchen

Wann Sie bei DIY-Docker bleiben sollten

Wann Sie zu Managed Opsily-Hosting wechseln sollten

Ollama Docker DIY vs. Opsily Managed

Einfache, transparente Preisgestaltung

Vertrauen & Compliance

GDPR Compliant

Data Encryption

Automated Security Updates

EU Infrastructure

Open Source Transparency

Häufig gestellte Fragen

Was unsere Kunden sagen

Bereit, den Docker-Betrieb zu überspringen?