kobo-docker

1. Introduction
2. Two PostgreSQL databases are now required
3. Important notice when upgrading from commit 5c2ef02 (March 4, 2019) or earlier
4. Important notice when upgrading from commit between 51aeccb (March 11, 2019) and 2.022.44 (November 17, 2022)
5. Architecture
6. Setup procedure
7. Usage
   • Start/stop
   • Backups
   • Restore backups
   • Maintenance
8. Troubleshooting
9. Redis performance

Introduction

kobo-docker is used to run a copy of the KoboToolbox survey data collection platform on a machine of your choosing. It relies on Docker to separate the different parts of KoBo into different containers (which can be thought of as lighter-weight virtual machines) and Docker Compose to configure, run, and connect those containers.

Two PostgreSQL databases are now required

Prior to release 2.020.18, KPI and KoBoCAT both shared a common PostgreSQL database. They now each have their own, separate databases. If you are upgrading an existing single-database installation, you must follow these instructions to migrate the KPI tables to a new database and adjust your configuration appropriately. This assumes your last upgrade was more recent than March 4, 2019. If not, you must upgrade your databases before proceeding.

If you do not want to upgrade at this time, please use the shared-database-obsolete branch instead.

Important notice when upgrading from commit 5c2ef02 (March 4, 2019) or earlier

Running current releases of KoboToolbox requires you to upgrade your PostgreSQL and MongoDB databases. Please follow these instructions.

If you do not, the application may not start or your data may not be visible.

Important notice when upgrading from commit between 51aeccb (March 11, 2019) and 2.022.44 (November 17, 2022)

Running current releases of KoboToolbox requires you to upgrade your PostgreSQL and MongoDB databases. Please follow these instructions.

If you do not, the application may not start or your data may not be visible.

Architecture

Below is a diagram (made with Lucidchart) of the containers that make up a running kobo-docker system and their connections.

Secure your installation

This version of kobo-docker does not expose backend container ports, but previous versions did, relying on a firewall to prevent unauthorized access. You should always verify that your database ports (by default 5432, 27017, 6379, 6380) are not accessible to the public.

If you want to use kobo-docker with separate front-end and back-end servers, you will need to expose ports, and you MUST use a firewall. The firewall is required to allow only the frontend containers to access PostgreSQL, Redis, and MongoDB.

Setup procedure

This procedure has been simplified by using kobo-install. Please use it to install kobo-docker.

Already have an existing installation? Please see below.

1. Migrating from RabbitMQ to Redis as the Celery (asynchronous task) broker

   The easiest way is to rely on kobo-install to generate the correct environment files.

   If you want to change it manually, edit:

   • kobo-env/envfiles/kpi.txt

     - KPI_BROKER_URL=amqp://kpi:kpi@rabbit.[internal domain name]:5672/kpi
     + KPI_BROKER_URL=redis://redis-main.[internal domain name]:6389/1

   • kobo-env/envfiles/kobocat.txt

     - KOBOCAT_BROKER_URL=amqp://kobocat: kobocat@rabbit.[internal domain name]:5672/kobocat
     + KOBOCAT_BROKER_URL=redis://redis-main.[internal domain name]:6389/2

2. Load balancing and redundancy

   1. Load balancing kobo-docker has two different composer files. One for frontend and one for backend.

      1. frontend:

         • NGINX
         • KoBoCAT
         • KPI
         • Enketo Express

      2. backend:

         • PostgreSQL
         • MongoDB
         • Redis

      Docker-compose for frontend can be started on its own server, same thing for backend. Users can start as many front-end servers they want. A load balancer can spread the traffic between front-end servers. kobo-docker uses (private) domain names between frontend and backend. It's fully customizable in configuration files. Once again, kobo-install does simplify the job by creating the configuration files for you.

   2. Redundancy Backend containers not redundant yet. Only PostgreSQL can be configured in Primary/Secondary mode where Secondary is a real-time read-only replica.

   This is a diagram that shows how kobo-docker can be used for a load-balanced/(almost) redundant solution.

   NB: The diagram is based on AWS infrastructure, but it's not required to host your environment there.

   

Usage

It's recommended to create *.override.yml docker-compose files to customize your environment. It makes easier to update. Samples are provided. Remove .sample extension and update them to match your environment.

• docker-compose.frontend.override.yml
• docker-compose.backend.primary.override.yml
• docker-compose.backend.secondary.override.yml (if a PostgreSQL replica is used)

1. Start/start containers

   # Start
   $kobo-docker> docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml up -d  
   $kobo-docker> docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml up -d
   
   # Stop
   $kobo-docker> docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml stop  
   $kobo-docker> docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml stop
   

2. Backups

   Automatic, periodic backups of KoBoCAT media, MongoDB, PostgreSQL and Redis can be individually enabled by uncommenting (and optionally customizing) the *_BACKUP_SCHEDULE variables in your envfiles.

   • deployments/envfiles/databases.txt (MongoDB, PostgreSQL, Redis)
   • deployments/envfiles/kobocat.txt (KoBoCat media)

   When enabled, timestamped backups will be placed in backups/kobocat, backups/mongo, backups/postgres and backups/redis respectively.

   If AWS credentials and AWS S3 backup bucket name are provided, the backups are created directly on S3.

   Backups on disk can also be manually triggered when kobo-docker is running by executing the the following commands:

   $kobo-docker> docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml exec kobocat /srv/src/kobocat/docker/backup_media.bash
   $kobo-docker> docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml exec mongo bash /kobo-docker-scripts/backup-to-disk.bash
   $kobo-docker> docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml exec -e PGUSER=kobo postgres bash /kobo-docker-scripts/backup-to-disk.bash
   $kobo-docker> docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml exec redis_main bash /kobo-docker-scripts/backup-to-disk.bash
   

3. Restore backups

   Commands should be run within containers.

   • MongoDB: mongorestore --archive=<path/to/mongo.backup.gz> --gzip
   • PostgreSQL: pg_restore -U kobo -d kobotoolbox -c "<path/to/postgres.pg_dump>"
   • Redis: gunzip <path/to/redis.rdb.gz> && mv <path/to/extracted_redis.rdb> /data/enketo-main.rdb

4. Maintenance mode

   There is one composer file docker-compose.maintenance.yml can be used to put KoboToolbox in maintenance mode.
   Like front-end or back-end containers, a docker-compose.maintenance.yml.sample file is provided to help you to customize your settings. First, copy docker-compose.maintenance.yml.sample to docker-compose.maintenance.yml.

   There are 4 variables that can be customized in docker-compose.maintenance.override.yml:

   • ETA e.g. 2 hours
   • DATE_STR e.g. Monday, November 26 at 02:00 GMT
   • DATE_ISO e.g. 20181126T02
   • EMAIL e.g. [email protected]

   NGINX container has to be stopped before launching the maintenance container.

   Start

   docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml stop nginx
   docker-compose -f docker-compose.maintenance.yml -f docker-compose.maintenance.override.yml up -d
   

   Stop

   docker-compose -f docker-compose.maintenance.yml -f docker-compose.maintenance.override.yml down
   docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml up -d nginx
   

Troubleshooting

• Basic troubleshooting

  You can confirm that your containers are running with docker ps. To inspect the log output from:

  • the frontend containers, execute docker-compose -f docker-compose.frontend.yml -f docker-compose.frontend.override.yml logs -f
  • the primary backend containers, execute docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml logs -f
  • the secondary backend container, execute docker-compose -f docker-compose.backend.secondary.yml -f docker-compose.backend.secondary.override.yml logs -f

  For a specific container use e.g. docker-compose -f docker-compose.backend.primary.yml -f docker-compose.backend.primary.override.yml logs -f redis_main.

  The documentation for Docker can be found at https://docs.docker.com.

• Django debugging

  Developers can use PyDev's remote, graphical Python debugger to debug Python/Django code. To enable for the kpi container:

  1. Specify the mapping(s) between target Python source/library paths on the debugging machine to the locations of those files/directories inside the container by customizing and uncommenting the KPI_PATH_FROM_ECLIPSE_TO_PYTHON_PAIRS variable in envfiles/kpi.txt.
  2. Share the source directory of the PyDev remote debugger plugin into the container by customizing (taking care to note the actual location of the version-numbered directory) and uncommenting the relevant volumes entry in your docker-compose.yml.
  3. To ensure PyDev shows you the same version of the code as is being run in the container, share your live version of any target Python source/library files/directories into the container by customizing and uncommenting the relevant volumes entry in your docker-compose.yml.
  4. Start the PyDev remote debugger server and ensure that no firewall or other settings will prevent the containers from connecting to your debugging machine at the reported port.
  5. Breakpoints can be inserted with: import pydevd; pydevd.settrace('${DEBUGGING_MACHINE_IP}').

  Remote debugging in the kobocat container can be accomplished in a similar manner.

Redis performance

Please take a look at https://www.techandme.se/performance-tips-for-redis-cache-server/ to get rid of Warning message when starting redis containers