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Deployment

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1. [Requirements](#requirements) 1. [Requirements](#requirements)
2. [Quickstart](#quickstart) 2. [Quickstart](#quickstart)
3. [Deployment](#deployment-in-the-docker-swarm) 3. [Deployment](#deployment-in-the-docker-swarm)
3. [Configuration](#configuration)
4. [Trouble-Shooting](#trouble-shooting)
## Requirements ## Requirements
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./start-local.sh ./start-local.sh
``` ```
This will run jupyter on the default port [localhost:8888](http://localhost:8888). The general usage is: This will run *gpu-jupyter* on the default port [localhost:8888](http://localhost:8888). The general usage is:
```bash ```bash
./start-local.sh -p [port] # port must be an integer with 4 or more digits. ./start-local.sh -p [port] # port must be an integer with 4 or more digits.
``` ```
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``` ```
The docker network name **elk_datastack** is used in the next step as a parameter. The docker network name **elk_datastack** is used in the next step as a parameter.
### Start GPU-Jupyter ### Start GPU-Jupyter in Docker Swarm
If so, the *gpu-jupyter* can be deployed in the Docker Swarm using Finally, *gpu-jupyter* can be deployed in the Docker Swarm with the shared network, using:
```bash
./add-to-swarm.sh -p [port] -n [docker-network]
```
where:
* port specifies the port on which the service will be available.
* and docker-network is the name of the attachable network from the previous step, e.g., here it is **elk_datastack**.
Now, *gpu-jupyter* will be accessable on [localhost:port](http://localhost:8888) and shares the network with the other data-source. I.e, all ports of the data-source will be accessable within *gpu-jupyter*, even if they aren't routed it the source's `docker-compose` file.