From c4614719426d2bcb9bced37294db7a1af2da7794 Mon Sep 17 00:00:00 2001 From: allegroai <> Date: Thu, 13 Jun 2019 01:27:36 +0300 Subject: [PATCH] Documentation --- README.md | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index 7a9b0b7..599355c 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # TRAINS Server -## Magic Version Control & Experiment Manager for AI +## Automagical Version Control & Experiment Manager for AI [![GitHub license](https://img.shields.io/badge/license-SSPL-green.svg)](https://img.shields.io/badge/license-SSPL-green.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) @@ -9,19 +9,19 @@ ## Introduction The **trains-server** is the infrastructure for [TRAINS](https://github.com/allegroai/trains). -It allows multiple users to collaborate and manage their experiments. - +It allows multiple users to collaborate and manage their experiments. + The **trains-server** contains the following components: * the Web-App which is a single-page UI for experiment management and browsing -* a REST interface for: +* a REST interface for: * documenting and logging experiment information, statistics and results * querying experiments history, logs and results * a locally-hosted file server for storing images and models making them easily accessible using the Web-App You can quickly setup your **trains-server** using a pre-built Docker image (see [Installation](#installation)). -When new releases are available, you can upgrade your pre-built Docker image (see [Upgrade](#upgrade)). +When new releases are available, you can upgrade your pre-built Docker image (see [Upgrade](#upgrade)). The **trains-server's** code is freely available [here](https://github.com/allegroai/trains-server). @@ -72,12 +72,12 @@ This section contains the instructions to setup and launch a pre-built Docker im * This Docker image was tested with Linux, only. For Windows users, we recommend running the server on a Linux virtual machine. -* All command-line instructions below assume you're using `bash`. +* All command-line instructions below assume you're using `bash`. ### Prerequisites You must be logged in as a user with sudo privileges. - + ### Setup #### Step 1: Install Docker CE @@ -99,12 +99,12 @@ 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, you must 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: -* If your system contains a `/etc/sysconfig/docker` Docker configuration file, edit it. +* If your system contains a `/etc/sysconfig/docker` Docker configuration file, edit it. Add the options in quotes to the available arguments in the `OPTIONS` section: @@ -114,7 +114,7 @@ You must edit or create a Docker configuration file: * Otherwise, edit `/etc/docker/daemon.json` (if it exists) or create it (if it does not exist). - Add or modify the `defaults-ulimits` section as shown below. Be sure the `defaults-ulimits` section contains the `nofile` and `memlock` sub-sections and values shown. + Add or modify the `defaults-ulimits` section as shown below. Be sure the `defaults-ulimits` section contains the `nofile` and `memlock` sub-sections and values shown. **Note**: Your configuration file may contain other sections. If so, confirm that the sections are separated by commas (valid JSON format). For more information about Docker configuration files, see [Daemon configuration file](https://docs.docker.com/engine/reference/commandline/dockerd/#daemon-configuration-file) in the Docker documentation. @@ -150,7 +150,7 @@ sudo service docker start #### Step 4: Set the Maximum Number of Memory Map Areas The maximum number of memory map areas a process can use is defined -using the `vm.max_map_count` kernel setting. +using the `vm.max_map_count` kernel setting. Elastic requires that `vm.max_map_count` is at least 262144 (see [Production mode](https://www.elastic.co/guide/en/elasticsearch/reference/master/docker.html#docker-cli-run-prod-mode)). @@ -211,7 +211,7 @@ After the **trains-server** Dockers are up, the following are available: Once you've installed the **trains-server**, please make sure to configure **trains** to use your locally installed server (and not the demo server). -If you've already installed **trains**, run the `trains-init` command for an interactive setup or edit your `trains.conf` file and make sure the `api.host` value is configured as follows: +If you've already installed **trains**, run the `trains-init` command for an interactive setup or edit your `trains.conf` file and make sure the `api.host` value is configured as follows: ``` api { @@ -219,7 +219,7 @@ api { } ``` -See [Installing and Configuring TRAINS](https://github.com/allegroai/trains#installing-and-configuring-trains) for more details. +See [Installing and Configuring TRAINS](https://github.com/allegroai/trains#installing-and-configuring-trains) for more details. ## Upgrade @@ -231,9 +231,9 @@ When we release a new version and include a new pre-built Docker image for it, u sudo docker stop sudo docker rm -v - + The Docker names are (see [Launching Docker Containers](#launching-docker-containers)): - + * `trains-elastic` * `trains-mongo` * `trains-fileserver` @@ -243,13 +243,13 @@ When we release a new version and include a new pre-built Docker image for it, u 2. We highly recommend backing up your data directory!. A simple way to do that is using `tar`: For example, if your data directory is `/opt/trains`, use the following command: - + sudo tar czvf ~/trains_backup.tgz /opt/trains/data - - This back ups all data to an archive in your home directory. - + + This back ups all data to an archive in your home directory. + To restore this example backup, use the following command: - + sudo rm -R /opt/trains/data sudo tar -xzf ~/trains_backup.tgz -C /opt/trains/data