Update examples using Docker Compose (#4857)

* Update docker-compose example README

- Update to Docker Compose v2 commands.
- Replace `docker system prune` with `docker compose down`.

* Update Event-driven architecture example README file

* Rename Docker Compose file

Make docker-compose.yml name consistent between examples

examples/docker-compose/README.md

@@ -10,7 +10,7 @@ and related configuration.
 
 ## Prerequisites
 
-Install *Docker* and *Docker Compose*. You can either build *Apicurio Registry* images locally 
+Install *Docker*. You can either build *Apicurio Registry* images locally 
 (see the build documentation in the project root), 
 or use the pre-built images from a public registry.
 
@@ -22,36 +22,34 @@ and copy the content of the `./config` directory to the volume - `docker volume
 ### Metrics with Prometheus and Grafana
 
 Run `compose-metrics.yaml` together with a base compose file, e.g. 
-`docker-compose -f compose-metrics.yaml -f compose-base-sql.yaml up --abort-on-container-exit`.
+`docker compose -f compose-metrics.yaml -f compose-base-sql.yaml up --abort-on-container-exit`.
 
 *Grafana* console should be available at `http://localhost:3000` after logging in as *admin/password*.
 
-
-
-### Docker-compose and Quarkus based installation
+### Docker Compose and Quarkus based installation
 
 #### Overview
 
 This setup contains a fully configured Apicurio Registry package already integrated with Keycloak. Currently every application is routed to the host network without SSL support. This is a development version, do not use it in a production environment!
 
 Here is the port mapping:
+
 - 8080 for Keycloak
 - 8081 for the Registry API
 - 8888 for the Registry UI
 
-
 #### Starting the environment
 
-You can start the whole stack with these commands:
+You can start the whole stack with this command:
 
-```
-docker-compose -f docker-compose.apicurio.yml up
+```console
+docker compose -f docker-compose.apicurio.yml up
 ```
 
-To clear the environment, please run these commands:
+To clear the environment, please run this command:
 
-```
-docker system prune --volumes
+```console
+docker compose -f docker-compose.apicurio.yml down --volumes
 ```
 
 #### Configure users in Keycloak
@@ -63,11 +61,10 @@ At the first start there are no default users added to Keycloak. Please navigate
 
 The default credentials for Keycloak are: `admin` and the password is also `admin`.
 
-Select Registry realm and add a user to it. You'll need to also assign the appropriated role.
+Select `Registry` realm and add a user to it. You'll need to also assign the appropriate role.
 
 #### Login to Apicurio and Keycloak
 
 Apicurio Registry UI URL: `http://YOUR_IP:8888`
 Apicurio Registry API URL: `http://YOUR_IP:8081`
 Keycloak URL: `http://YOUR_IP:8080`
-

examples/event-driven-architecture/README.md

@@ -1,25 +1,30 @@
-# Kafka, ksqldb, Kafka-ui, apicurio-registry and Debezium together
+# Event-driven architecture with Apicurio Registry
 
-This tutorial demonstrates how to use [Debezium](https://debezium.io/) to monitor the PostgreSQL database used by Apicurio Registry. As the
-data in the database changes, by adding e.g. new schemas, you will see the resulting event streams.
+## Kafka, ksqldb, Kafka-ui, apicurio-registry and Debezium together
+
+This tutorial demonstrates how to use [Debezium](https://debezium.io/)
+to monitor the PostgreSQL database used by Apicurio Registry.
+As the data in the database changes, such as by adding new schemas,
+you will see the resulting event streams.
 
 ## Avro serialization
 
-The [Apicurio Registry](https://github.com/Apicurio/apicurio-registry) open-source project provides several
-components that work with Avro:
+The [Apicurio Registry](https://github.com/Apicurio/apicurio-registry)
+open-source project provides several components that work with Avro:
 
-- An Avro converter that you can specify in Debezium connector configurations. This converter maps Kafka
-  Connect schemas to Avro schemas. The converter then uses the Avro schemas to serialize the record keys and
-  values into Avro’s compact binary form.
+- An Avro converter that you can specify in Debezium connector configurations
+  This converter maps Kafka Connect schemas to Avro schemas.
+  The converter then uses the Avro schemas to serialize the record keys and values
+  into Avro’s compact binary form.
 
 - An API and schema registry that tracks:
 
-    - Avro schemas that are used in Kafka topics
-    - Where the Avro converter sends the generated Avro schemas
+  - Avro schemas that are used in Kafka topics
+  - Where the Avro converter sends the generated Avro schemas
 
 ### Prerequisites
 
-- Docker and is installed and running.
+- Docker is installed and running.
 
   This tutorial uses Docker and the Linux container images to run the required services. You should use the
   latest version of Docker. For more information, see
@@ -29,20 +34,20 @@ components that work with Avro:
 
 1. Clone this repository:
 
-    ```bash
-    git clone https://github.com/Apicurio/apicurio-registry-examples.git
+    ```console
+    git clone https://github.com/Apicurio/apicurio-registry.git
     ```
 
 1. Change to the following directory:
 
-    ```bash
-    cd event-driven-architecture
+    ```console
+    cd examples/event-driven-architecture
     ```
 
 1. Start the environment
 
-    ```bash
-    docker-compose up -d
+    ```consolee
+    docker compose up -d
     ```
 
 The last command will start the following components:
@@ -56,14 +61,15 @@ The last command will start the following components:
 
 ## Apicurio converters
 
-Configuring Avro at the Debezium Connector involves specifying the converter and schema registry as a part of
-the connectors configuration. The connector configuration file configures the connector but explicitly sets
-the (de-)serializers for the connector to use Avro and specifies the location of the Apicurio registry. 
+Configuring Avro at the Debezium Connector involves specifying the converter
+and schema registry as a part of the connector's configuration.
+The configuration file sets the (de-)serializers to use Avro
+and specifies the location of the Apicurio registry.
 
-> The container image used  in this environment includes all the required libraries to access the connectors and converters.
+> The container image used in this environment includes all the required libraries to access the connectors and converters.
 
-The following are the lines required to set the **key** and **value** converters and their respective registry
-configuration:
+The following lines are required to set the **key** and **value** converters
+and their respective registry configurations:
 
 ```json
 {
@@ -81,20 +87,24 @@ configuration:
 
 ### Create the connector
 
-Let's create the Debezium connector to start capturing the changes of the database.
+Let's create the Debezium connector to start capturing changes in the database.
 
-1. Create the connector using the REST API. You can execute this step either by using the curl command below
-   or by creating the connector from the Kafka UI.
+1. Create the connector using the REST API.
+You can execute this ste either by using the `curl` command below
+or by creating the connector from the Kafka UI.
 
-    ```bash
-    curl -X POST http://localhost:8083/connectors -H 'content-type:application/json' -d @studio-connector.json
+    ```console
+    curl http://localhost:8083/connectors -H 'Content-Type: application/json' -d @studio-connector.json
     ```
 
 ### Check the data
 
-The previous step created and started the connector. Now, all the data inserted in the Apicurio Registry database will be captured by Debezium
-and sent as events into Kafka.
+The previous step created and started the connector.
+Now, all the data inserted in the Apicurio Registry database
+will be captured by Debezium and sent as events into Kafka.
 
 ## Summary
 
-By using this example you can test how to start a full even driven architecture, but it's up to you how to use the produced events in e.g. ksqldb to create streams/tables etc.
+This example allows you to test how to start a full event-driven architecture.
+How you use the produced events is up to you,
+such as creating streams or tables in ksqlDB, etc.