Update instructions for Exercises 14, 15, and 16 (#14)

* exercise_014/README.md: Don't give the code for the SSE method

* exercise_014/README.md: minor update to explain best way to get product IDs

* exercise_015/README.md: Remove mention of docker-compose setup for Kafka

* exercise_015/README.md: Remove serialisation/deserialisation config

* exercise_016/README.md: Remove mention of Conduktor and replace with Kafka Dev UI

Author: njlbenn

code/exercise_014_Internal_Channels/README.md

@@ -10,7 +10,7 @@ We will create a _Generator_ that generates new prices for all our products ever
 
 * Pull in the class `PriceUpdate` by executing this command from the command line: `cmtc pull-template src/main/java/com/lunatech/training/quarkus/PriceUpdate.java <root folder of exercise repo>`. The `PriceUpdate` class represents an updated price for the product with the product id in the class. 
 
-* Create the file `PriceUpdateStream.java` with the following template:
+* Create the file `PriceUpdateStreams.java` with the following template:
 
 ```java
 package com.lunatech.training.quarkus;
@@ -37,7 +37,7 @@ public class PriceUpdateStreams {
 }
 ```
 
-* Implement the method `public Multi<PriceUpdate> generate()` on the `PriceUpdateStream` class, and make it return a `Multi` that emits a `PriceUpdate` item for each of the products in our database (You can hardcode it to use product ids 1 to 7) *every five seconds*, using a random price between 0 and 100.
+* Implement the method `public Multi<PriceUpdate> generate()` on the `PriceUpdateStreams` class, and make it return a `Multi` that emits a `PriceUpdate` item *every five seconds*, using a random price between 0 and 100, for each of the products in our database (You can hardcode the product IDs - use `curl localhost:8080/products` to discover the product IDs saved in the database) .
 
   Tip, look at the `Multi.createFrom().ticks()` method!
   Note that the `print` method has an `@Incoming` annotation that matches the `@Outgoing` from the `generate` method. Running the application should print seven lines to the console every five seconds, each line being a price update for a product. Run the app to try this :)
@@ -68,14 +68,7 @@ Finally, we will create a `PriceUpdatesResource` class, so we can expose the pri
       Multi<PriceUpdate> priceUpdates;
 
 * `@Channel` is also a Reactive Messaging annotation, and Quarkus will connect this `Multi` to the 'price-updates' channel. This is an alternative method to receive the items in that channel (different from how we did it with an `@Incoming` annotation on the `print` method!)
-* Next, add this method
-
-      @GET
-      @Produces(MediaType.SERVER_SENT_EVENTS)
-      @RestSseElementType(MediaType.APPLICATION_JSON)
-      public Multi<PriceUpdate> prices() {
-        return priceUpdates;
-      }
+* Next, add a method in `PriceUpdatesResource` that will expose the price updates as Server Sent Events. You can use the example in `ListenNotifyResource` from the previous exercise as inspiration
 
 * Now, connect to this endpoint using Curl:
 

code/exercise_015_Connecting_to_Kafka/README.md

@@ -1,11 +1,7 @@
 ## Exercise 15: Kafka
 
-In this exercise, we will connect our price processing components to Kafka. We will add Kafka to our `docker-compose` setup, and connect the reactive messaging components to Kafka using the `smallrye-reactive-messaging-kafka` extension.
+In this exercise, we will connect our price processing components to Kafka. For this we will use the `smallrye-reactive-messaging-kafka` extension to connect our reactive messaging components to Kafka. We will then rely on Dev Services Kafka to automatically start a Kafka broker and to automatically configure the application to find the broker.
 
-Tip: If something fails, you can use [Conductor](https://conduktor.io) to check what’s going on in Kafka.
-
-* Uncomment the 'zookeeper' and 'kafka' services in the `docker-compose.yml`
-* Run `docker-compose up -d`. This will now start Zookeeper and Kafka (next to the still-running Postgres)
 * Add the `quarkus-smallrye-reactive-messaging-kafka` extension to your `pom.xml`
 * Pull in the class `PriceUpdateDeserializer` by executing this command from the command line: `cmtc pull-template src/main/java/com/lunatech/training/quarkus/PriceUpdateDeserializer.java <root folder of exercise repo>`.
 * On the class `PriceUpdateStreams`:
@@ -16,45 +12,15 @@ Tip: If something fails, you can use [Conductor](https://conduktor.io) to check
     - Change the channel name in the `@Channel` annotation to `price-updates-in`
 * Add the following config:
 
-      kafka.bootstrap.servers=127.0.0.1:9092
-      mp.messaging.outgoing.raw-price-updates-out.connector=smallrye-kafka
       mp.messaging.outgoing.raw-price-updates-out.topic=raw-prices
-      mp.messaging.outgoing.raw-price-updates-out.value.serializer=io.quarkus.kafka.client.serialization.ObjectMapperSerializer
-      mp.messaging.incoming.raw-price-updates-in.connector=smallrye-kafka
       mp.messaging.incoming.raw-price-updates-in.topic=raw-prices
-      mp.messaging.incoming.raw-price-updates-in.value.deserializer=com.lunatech.training.quarkus.PriceUpdateDeserializer
-      mp.messaging.outgoing.price-updates-out.connector=smallrye-kafka
       mp.messaging.outgoing.price-updates-out.topic=prices
-      mp.messaging.outgoing.price-updates-out.value.serializer=io.quarkus.kafka.client.serialization.ObjectMapperSerializer
-      mp.messaging.incoming.price-updates-in.connector=smallrye-kafka
       mp.messaging.incoming.price-updates-in.topic=prices
-      mp.messaging.incoming.price-updates-in.value.deserializer=com.lunatech.training.quarkus.PriceUpdateDeserializer
 
 * Execute the cURL command again from the previous exercise:
 
       curl http://localhost:8080/prices
 
 * You should see price updates streaming by again.
-* Check what’s going on in Kafka with Conduktor if you haven’t yet. 
-* You can check it without Conduktor. There are two cases:
-  * You have already installed Kafka on your machine and in this case you can type the following commands each in a terminal 
-    * `$ kafka-console-consumer --bootstrap-server localhost:9092 --topic price-updates --from-beginning` 
-    * `$ kafka-console-consumer --bootstrap-server localhost:9092 --topic raw-price-updates --from-beginning` 
-    * `$ kafka-console-consumer --bootstrap-server localhost:9092 --topic price-updates` 
-      * `--from-beginning` allows to display from the beginning 
-      * They do almost the same thing, we listen to different topics:  `price-updates` and `raw-price-updates` and we receive something like this:
-      
-            {"productId":1,"price":77}
-            {"productId":2,"price":83}
-            {"productId":3,"price":71}
-            {"productId":4,"price":84}
-            {"productId":6,"price":36}
-            {"productId":7,"price":43}
-
-  * You haven't installed Conduktor, Kafka, or Zookeeper on your machine and you certainly don't want to install them: but you have docker since you are using `docker-compose`
-    * Launch the containers: `docker-compose up -d`
-    * You retrieve the name of the kafka container to connect to it (or ID): `docker-compose ps`
-    * You can now connect to the shell of this container and execute commands. This container contains all Kafka configurations: `docker exec -it quarkus-course-kafka sh`
-    * Now you are connected to the container and you can use the same command lines as above but with a bit difference, you have to mention the executable path : bin files are located here `/opt/kafka/bin/`
-    * Don’t forget .sh for extension file
-      * `/opt/kafka/bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic price-updates --from-beginning`
+* You can check what’s going on in Kafka with the Kafka Dev UI:
+  * http://localhost:8080/q/dev-ui/io.quarkus.quarkus-kafka-client/topics

code/exercise_016_Dead_Letter_Queue_and_Stream_filtering/README.md

@@ -10,7 +10,7 @@ In this exercise we will see a method to deal with ‘broken’ messages.
       mp.messaging.incoming.raw-price-updates-in.failure-strategy=dead-letter-queue
       mp.messaging.incoming.raw-price-updates-in.dead-letter-queue.value.serializer=io.quarkus.kafka.client.serialization.ObjectMapperSerializer
 
-* Restart the app, and observe that the stream works again (curl http://localhost:8080/prices), although now most of the times you end up with less than 7 updates per 5 seconds. The failures end up in the topic `dead-letter-topic-raw-price-updates-in`. You can easily inspect it with Conduktor.
+* Restart the app, and observe that the stream works again (curl http://localhost:8080/prices), although now most of the times you end up with less than 7 updates per 5 seconds. The failures end up in the topic `dead-letter-topic-raw-price-updates-in`. You can easily inspect it with the Kafka Dev UI - http://localhost:8080/q/dev-ui/io.quarkus.quarkus-kafka-client/topics
 
 Finally, we want to connect our React frontend to the cool new price-streaming feature. But before we do so, we have to make one more endpoint; that only streams prices for an individual product.