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ARLAS Exploration Stack

The ARLAS Exploration Stack project contains reference docker compose files for all the ARLAS microservices and third party services for running the ARLAS Stack. It also contains the script for starting the stack in different modes:

  • Simple: ARLAS without authentication, on HTTP
  • IAM: With ARLAS Identity and Access Management (ARLAS IAM), on HTTPS
  • AIAS: With ARLAS IAM and ARLAS AIAS (ARLAS Item and Asset Services) for managing EO products for instance. (WORK IN PROGRESS)

Run ARLAS stack

To run ARLAS stack, clone the ARLAS Exploration Stack project and follow the guidelines.

git clone git@github.com:gisaia/ARLAS-Exploration-stack.git
cd ARLAS-Exploration-stack

Simple deployment

The simple deployment has:

Start

To start the ARLAS stack in simple mode, run: 

./start.sh

Success

Once started, you can open ARLAS in your browser: http://localhost/.

Note

If you changed ARLAS_HOST in conf/stack.env, then open instead http://${ARLAS_HOST} .

Test

You can add a sample data set and a configured dashboard by running:

pip3.10 install arlas-cli
./scripts/init_arlas_cli_confs.sh
./scripts/init_stack_with_data.sh local

Success

A simple dashboard with AIS data is then available.

IAM deployment

The IAM deployment has:

Start

To start, run: 

./start.sh iam

Success

Once started, you can open ARLAS in your browser: https://localhost/.

Note

If you changed ARLAS_HOST in conf/stack.env, then open instead https://${ARLAS_HOST} .

Test

You can add a sample data set and a configured dashboard by running:

pip3.10 install arlas-cli
./scripts/init_arlas_cli_confs.sh
./scripts/init_stack_with_data.sh local.iam.admin

Success

A simple dashboard with AIS data is then available.

You can login with:

  • username: user@org.com
  • password: secret

or as admin:

  • username: tech@gisaia.com
  • password: admin

Warning

when using IAM, users can create collections only on indices prefixed with their organisation's name followed by @.

For instance, a user in the organisation gisaia.com, who creates an index containing car gps data can name the index gisaia.com@car_gps_locations.

AIAS deployment

The AIAS (ARLAS Item and Asset Services) deployment has:

To start, run: 

./start.sh aias

You can access ARLAS just like the IAM deployment. You can also use the same script for initializing the stack with users and data.

EO Catalog

To setup an ARLAS EO catalog:

  1. Place some geotiff files in ${APROC_INPUT_DIR} configured in conf/aias.env.

  2. Go to the web page of ARLAS, then click the Import link (top right menu). This brings you to the import page. Add the geotiff file in the catalog by clicking on the + icon next to the tiff file. This will create and automatically feed an index named org.com@airs_catalog.

  3. Once added, run :
./scripts/init_aias_catalog.sh local.iam.user catalog org.com

This will init the collection and the dashboard for the catalog.

Naming Convention

The index name has the form org@airs_name

For instance, the collection "geodes" for the organisation "org.com" has its index in "org.com@airs_geodes"

Data from GEODES

You can register data from GEODES:

docker run --rm --network arlas-net gisaia/stac-geodes:latest add https://geodes-portal.cnes.fr/api/stac/items http://airs-server:8000/airs geodes S2L1C --start-date "2023-04-05T08:58:40.737+00:00" --max 1000

This will register in the org.com@airs_geodes index the first 1000 S2L1C data that were acquired after 2023-04-05T08:58.

Then, you can create the catalog:

./scripts/init_aias_catalog.sh local.iam.user geodes org.com

Stop ARLAS stack

Stop the stack with ./stop.sh.

Note

By default, data are persisted in docker volumes prefixed with arlas-test- ...

To reset the volumes, run:

docker volume rm arlas-test-data-es arlas-test-persist arlas-test-postgres