ClearML/clearml-server
1
0
Fork 0
mirror of https://github.com/clearml/clearml-server synced 2025-01-31 02:46:53 +00:00
Code Issues Actions Packages Projects Releases Wiki Activity

Add Pre-Installed AWS AMI links

Browse Source
This commit is contained in:
allegroai 2019-06-18 16:32:19 +03:00
parent c70cbe04c1
commit 1e40fc7922
2 changed files with 51 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

23
README.md
View File

@ -3,6 +3,7 @@
## Auto-Magical Experiment Manager & Version Control for AI
[![GitHub license](https://img.shields.io/badge/license-SSPL-green.svg)](https://img.shields.io/badge/license-SSPL-green.svg)
[![Python versions](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)
[![GitHub version](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)
[![PyPI status](https://img.shields.io/badge/status-beta-yellow.svg)](https://img.shields.io/badge/status-beta-yellow.svg)
@ -33,7 +34,13 @@ The **trains-server's** code is freely available [here](https://github.com/alleg
![Alt Text](https://github.com/allegroai/trains/blob/master/docs/system_diagram.png?raw=true)
## Installation
## Installation - AWS
Use our pre-installed Amazon Machine Image for easy deployment in AWS.
Details and instructions can be found [here](docs/install_aws.md).
## Installation - Docker
This section contains the instructions to setup and launch a pre-built Docker image for the **trains-server**.
This is the quickest way to get started with your own server.
@ -47,13 +54,13 @@ on a Linux virtual machine.
### Prerequisites
You must be logged in as a user with sudo privileges.
Make sure you are logged in as a user with sudo privileges.
### Setup
#### Step 1: Install Docker CE
You must install Docker to run the pre-packaged **trains-server**.
In order to run the pre-packaged **trains-server**, install Docker.
* See [Supported platforms](https://docs.docker.com/install//#support) in the Docker documentation for instructions
@ -70,10 +77,10 @@ You must install Docker to run the pre-packaged **trains-server**.
#### Step 2: Setup the Docker daemon
To run the ElasticSearch Docker container, you must setup the Docker daemon by modifying the default
To run the ElasticSearch Docker container, setup the Docker daemon by modifying the default
values required by Elastic in your Docker configuration file (see [Notes for production use and defaults](https://www.elastic.co/guide/en/elasticsearch/reference/master/docker.html#_notes_for_production_use_and_defaults)). We provide instructions for the most common Docker configuration files.
You must edit or create a Docker configuration file:
Edit or create the Docker configuration file:
* If your system contains a `/etc/sysconfig/docker` Docker configuration file, edit it.
@ -111,7 +118,7 @@ You must edit or create a Docker configuration file:
#### Step 3: Restart the Docker daemon
You must restart the Docker daemon after modifying the configuration file:
After modifying the configuration file, restart the Docker daemon:
```bash
sudo service docker stop
@ -138,8 +145,8 @@ Elastic requires that `vm.max_map_count` is at least 262144 (see [Production mod
#### Step 5: Choose a Data Directory
You must choose a directory on your system in which all data maintained by the **trains-server** is stored,
Create a directory, and set its permissions. The data stored in this directory will include the database, uploaded files and logs.
Choose a directory on your system in which all data maintained by the **trains-server** is stored.
Create this directory, and set its owner and group to `uid` 1000. The data stored in this directory will include the database, uploaded files and logs.
For example, if your data directory is `/opt/trains`, then use the following command:

36
docs/install_aws.md Normal file
View File

@ -0,0 +1,36 @@
# **TRAINS-server**: AWS pre-installed images
In order to easily deploy **trains-server** on AWS, we created the following Amazon Machine Images (AMIs).
Service port numbers on these AMIs are:
- Web: 8080
- API: 8008
- File Server: 8081
Instructions on launching a custom AMI from the EC2 console can be found [here](https://aws.amazon.com/premiumsupport/knowledge-center/launch-instance-custom-ami/)
and a detailed version [here](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/launching-instance.html).
The minimum recommended instance type is **t3a.large**
##Released versions
The following sections provide a list containing AMI Image ID per region for each released **trains-server** version.
### v0.9.0
* **us-east-1** : ami-0991ad536ecbacdac
* **eu-north-1** : ami-07cbcdff501b14afe
* **ap-south-1** : ami-014cf398b00d4db83
* **eu-west-3** : ami-0396ba51e9b733581
* **eu-west-2** : ami-09134f4c7a20bad09
* **eu-west-1** : ami-00427ed0a1bbfa7b0
* **ap-northeast-2** : ami-041756675ca1be954
* **ap-northeast-1** : ami-0c09ebad05c9128ff
* **sa-east-1** : ami-017a8de4e8d1e8c8e
* **ca-central-1** : ami-049ec444470f852be
* **ap-southeast-1** : ami-0c919b8f821a6c635
* **ap-southeast-2** : ami-04844a0594712d27b
* **eu-central-1** : ami-0b4e756e0f7c0617d
* **us-east-2** : ami-03b01914b07428488
* **us-west-1** : ami-0cf4768e9d47ed076
* **us-west-2** : ami-0b145f37da31eb9fb