Updates for local testing of tile cache server

README.md

@@ -3,13 +3,19 @@ Raster and vector tile API for datasets in the [GFW Data API](https://github.com
 
 ## Developing
 ### Option 1: Developing against the Data API postgres database in one of the cloud environments (dev, staging or production):
-* Make sure you have ssh access to the bastion host of the aws account (contact a Data API Engineering team member to get help with this).
+* Make sure you have ssh access to the bastion host of the aws account (contact a
+  Data API Engineering team member to get help with this).  Also, your host IP address
+  (obtained by visiting `whatsmyip.com`) should be whitelisted for port 22 access in
+  the gfw-production core-default security group (at
+  `https://us-east-1.console.aws.amazon.com/ec2/home?region=us-east-1#SecurityGroups:`)
 
-* Open ssh tunnel connection to the database you'd like to connect to. For example, for the `staging` environment:
+* Open an ssh tunnel connection to the database you'd like to connect to. For example, for the `staging` environment:
 
-    ```ssh -i ~/.ssh/id_rsa -N -L 5432:application-autoscaling-698c9c01-db99-4430-a97a-6baaae853dc6.cljrqsduwhdo.us-east-1.rds.amazonaws.com:5432 ec2-user@gfw-staging```
+    ```ssh -i ~/.ssh/id_rsa -N -L 5432:application-autoscaling-698c9c01-db99-4430-a97a-6baaae853dc6.cljrqsduwhdo.us-east-1.rds.amazonaws.com:5432 ec2-user@{bastion_host}```
 
-* Set the environment variables for the **read only** credentials of the above database. The environment variables are `GFW_DB_NAME`,  `GFW_DB_USER_RO` and `GFW_DB_PASSWORD_RO`. These are also listed in the `docker-compose.dev.yml` file.
+{bastion_host} might be something like: `ec2-18-215-196-0.compute-1.amazonaws.com`
+
+* Set the environment variables for the **read only** credentials of the above database. The environment variables are `GFW_DB_NAME`,  `GFW_DB_USER_RO`, `GFW_DB_PASSWORD_RO`, and `PLANET_API_KEY`. These are also listed in the `docker-compose.dev.yml` file. You get the values of secrets from the secrets manager of the appropriate AWS environment (production, staging, etc.)
 
 * In `docker-compose.dev.yml`, set `DATA_LAKE_BUCKET`  to the desired environment's bucket name. By default, the `staging` environment bucket (`gfw-data-lake-staging`)  will be used.
 
@@ -18,9 +24,31 @@ Raster and vector tile API for datasets in the [GFW Data API](https://github.com
 * Run the start up script from the root directory:
 ```./scripts/develop```
 
+You access the tile cache server at `localhost:8088` on your host.
+
+
+NOTE: if you are developing on Linux (as opposed to MacOS), there can be a problem
+accessing the host network, so `scripts/develop` will likely hang without being able
+to access the database. If so, you can interrupt `scripts/develop` after it has built
+the docker and gotten hung accessing the database. You can then start the docker by
+hand via:
+
+```docker run -it -p 127.0.0.1:8088:80 --entrypoint /bin/bash gfw-tile-cache_app:latest```
+
+In that case, you will need to copy your `.ssh/id_rsa` and `.aws/credentials` files
+into the docker and set all the needed environmental variables in the shell. You then
+run the ssh tunnel from inside the docker via:
+
+```ssh -i ~/.ssh/id_rsa -N -L 127.0.0.1:5432:gfw-aurora.cluster-ro-ch3jv7fz9pj1.us-east-1.rds.amazonaws.com:5432 "[email protected]" &```
+
+You can then start up the tile cache server in the docker via:
+
+```/start-reload.sh &```
+
+
 ### Option 2: Developing against a local instance of Data API database
 
 * Start dev instance of Data API locally using the instructions [here](https://github.com/wri/gfw-data-api?tab=readme-ov-file#run-locally-with-docker)
 
 * Run the start up script from the root directory with the option to point to the local Data API:
-```./scripts/develop --local_data_api```
+```./scripts/develop --local_data_api```

docker-compose.dev.yml

@@ -24,11 +24,11 @@ services:
       - LOG_LEVEL=debug
       - RASTER_TILER_LAMBDA_NAME=test
       - ENV=dev
-      - PLANET_API_KEY
+      - PLANET_API_KEY=${PLANET_API_KEY}
       - AWS_REQUEST_PAYER=requester
       - 'DIST_ALERTS_FOREST_FILTERS={"tree_cover_loss": {"dataset": "umd_tree_cover_loss", "version": "v1.10.1"}, "tree_cover_height": {"dataset": "umd_tree_cover_height_2020", "version": "v2022"}, "tree_cover_density": {"dataset": "umd_tree_cover_density_2010", "version": "v1.6"}}'
     ports:
-      - 8088:80
+      - 127.0.0.1:8088:80
     entrypoint: wait_for_postgres.sh /start-reload.sh
 
 networks: