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.
Simple deployment
The simple deployment has:
- apisix
- arlas-wui
- arlas-hub
- arlas-builder
- arlas-persistence-server
- arlas-permissions-server
- arlas-server
- elasticsearch
- protomaps
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://${ARLAS_HOST} .
Test
You can add a sample data set and a configured dashboard by running:
pip3.10 install arlas-cli
./scripts/init_arlas_cli_confs.sh
./scripts/init_stack_with_data.sh local
Success
A simple dashboard with AIS data is then available.
IAM deployment
The IAM deployment has:
- apisix
- arlas-wui-iam
- arlas-iam-server
- postgres
- arlas-wui
- arlas-hub
- arlas-builder
- arlas-persistence-server
- arlas-permissions-server
- arlas-server
- elasticsearch
- protomaps
Start
To start, run:
./start.sh iam
Success
Once started, you can open ARLAS in your browser: https://localhost/.
Note
If you changed ARLAS_HOST
in conf/stack.env
, then open instead https://${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:
- apisix
- arlas-wui-iam
- arlas-iam-server
- postgres
- arlas-wui
- arlas-hub
- arlas-builder
- arlas-persistence-server
- arlas-permissions-server
- arlas-server
- agate
- fam
- fam-wui
- aproc-service
- aproc-proc
- elasticsearch
- protomaps
- minio
- redis
- rabbitmq
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:
-
Place some geotiff files in
${APROC_INPUT_DIR}
configured inconf/aias.env
. -
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
. - 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