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Update docs for GCP Custom Images

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allegroai 2020-03-30 15:51:58 +03:00
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README.md
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Launch **trains-server** in any of the following formats: Launch **trains-server** in any of the following formats:
- Pre-built [AWS EC2 AMI](https://github.com/allegroai/trains-server/blob/master/docs/install_aws.md) - Pre-built [AWS EC2 AMI](https://github.com/allegroai/trains-server/blob/master/docs/install_aws.md)
- Pre-built [GCP Custom Image](https://github.com/allegroai/trains-server/blob/master/docs/install_gcp.md)
- Pre-built Docker Image - Pre-built Docker Image
- [Linux](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md) - [Linux](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md)
- [macOS](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md) - [macOS](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md)

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# Deploying **trains-server** on Google Cloud Platform
To easily deploy **trains-server** on GCP, use one of our pre-built GCP Custom Images.
We provide Custom Images for each released version of **trains-server**, see [Released versions](#released-versions) below.
Once your GCP instance is up and running using our Custom Image, [configure the Trains client](https://github.com/allegroai/trains/blob/master/README.md#configuration) to use your **trains-server**.
The service port numbers on our **trains-server** GCP Custom Image are:
- Web application: `8080`
- API Server: `8008`
- File Server: `8081`
The persistent storage configuration:
- MongoDB: `/opt/trains/data/mongo/`
- ElasticSearch: `/opt/trains/data/elastic/`
- File Server: `/mnt/fileserver/`
For examples and use cases, check the [Trains usage examples](https://github.com/allegroai/trains/blob/master/docs/trains_examples.md).
For instructions on launching an instance using a GCP Custom Image, see the [Manually importing virtual disks](https://cloud.google.com/compute/docs/import/import-existing-image#overview) in the [Compute Engine Documentation](https://cloud.google.com/compute/docs).
For more information on Custom Images, see [Custom Images](https://cloud.google.com/compute/docs/images#custom_images) in the Compute Engine Documentation.
The minimum recommended amount of RAM for a **trains-server** instance is 8GB.
## Upgrading
To upgrade **trains-server** on an existing GCP instance based on one of these Custom Images, SSH into the instance and follow the [upgrade instructions](../README.md#upgrade) for **trains-server**.
## Released versions
The following sections contain lists of Custom Image URLs (exported in different formats) for each released **trains-server** version.
### Latest version Custom Images - v0.14.1
- https://storage.googleapis.com/allegro-files/trains-server/trains-server.qcow2
- https://storage.googleapis.com/allegro-files/trains-server/trains-server.vhd
- https://storage.googleapis.com/allegro-files/trains-server/trains-server.vhdx
- https://storage.googleapis.com/allegro-files/trains-server/trains-server.vmdk