GitBook: [#23] No subject

subsquid · Mar 1, 2022 · d14305e · d14305e
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diff --git a/.gitbook/assets/container graphql.png b/.gitbook/assets/container graphql.png
diff --git a/.gitbook/assets/docker build.png b/.gitbook/assets/docker build.png
diff --git a/.gitbook/assets/metrics.png b/.gitbook/assets/metrics.png
diff --git a/recipes/running-a-squid/building-with-docker.md b/recipes/running-a-squid/building-with-docker.md
@@ -1,2 +1,33 @@
 # Building with Docker
 
+The squid template repository comes with a `Dockerfile` included.
+
+The PostgreSQL database is already a docker-compose dependency by default, so this means that the [processor](../../key-concepts/processor.md) and the GraphQL server can be run as microservices in a container orchestration system, such as Kubernetes.
+
+In order to build an image of your customized project, provided you do have Docker installed and access to its CLI, simply launch the following command from the project's main folder, in a terminal window:
+
+```bash
+docker build . -t <image_name:image_version>
+```
+
+Where `image_name` and `image_version` should be substituted with the values that better fit your project.
+
+Below, you can see a screenshot of the Docker image process:
+
+![Building a Docker image of the squid-template](<../../.gitbook/assets/docker build.png>)
+
+In order to run the container, simply launch `docker run <image_name>:<image_version>` (you can omit `image_version` if it was labeled `latest`).
+
+But in order to test if everything is in order, we could launch the command by mapping the container port to the host's port, and check if we have access to the GraphiQL playground:
+
+```bash
+docker run -d -p 4000:4000 --name sqdl squid-template:latest
+```
+
+And when visiting the URL `localhost:4000/graphql` in the browser, we should see this:
+
+![Accessing the GraphiQL playground of the launched container](<../../.gitbook/assets/container graphql.png>)
+
+{% hint style="info" %}
+The 4000 port has been chosen, because it is explicitly exposed during the building process of the Docker image.
+{% endhint %}
diff --git a/recipes/running-a-squid/prometheus-metrics.md b/recipes/running-a-squid/prometheus-metrics.md
@@ -1,2 +1,22 @@
 # Prometheus metrics
 
+The Subsquid SDK comes with [Prometheus](https://prometheus.io) metrics to monitor synchronization status. When launching the processor, it is sufficient to specify the port at which metrics should be served via the environment variable `PROCESSOR_PROMETHEUS_PORT`.
+
+If not provided, a random port will be used and communicated at launch:
+
+```bash
+⇒ node -r dotenv/config lib/processor.js
+Prometheus metrics are served at port 34491
+Last block: 9422743, mapping: 33 blocks/sec, ingest: 279 blocks/sec, eta: 9h 12m, progress: 81%
+Last block: 9423694, mapping: 41 blocks/sec, ingest: 217 blocks/sec, eta: 8h 37m, progress: 81%
+Last block: 9424679, mapping: 41 blocks/sec, ingest: 195 blocks/sec, eta: 8h 16m, progress: 81%
+Last block: 9425591, mapping: 43 blocks/sec, ingest: 218 blocks/sec, eta: 8h 10m, progress: 81%
+Last block: 9426588, mapping: 44 blocks/sec, ingest: 227 blocks/sec, eta: 7h 33m, progress: 81%
+Last block: 9427710, mapping: 48 blocks/sec, ingest: 182 blocks/sec, eta: 6h 57m, progress: 81%
+```
+
+Then, it is sufficient to visit the `localhost:PROCESSOR_PROMETHEUS_PORT/metrics` URL, in order to access Prometheus metrics:
+
+![Prometheus metrics](../../.gitbook/assets/metrics.png)
+
+These can then be regularly polled to monitor the status and, for example, used in [Grafana dashboards](https://prometheus.io/docs/visualization/grafana/).