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fixed image locations in summit labs #24

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fixed image locations in summit labs #24

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fa786da
fixed images location
hodrigohamalho Jul 29, 2018
9d2b022
fixed image locations in all modules
hodrigohamalho Jul 29, 2018
7c947f7
fixed image locations in all modules
hodrigohamalho Jul 29, 2018
d286d26
updated cluster-controller to cluster-operator references in docs
hodrigohamalho Jul 29, 2018
f7d10e8
fixing bootstrap service name
hodrigohamalho Jul 30, 2018
90812f3
fixed BOOTSTRAP_SERVERS default value
hodrigohamalho Jul 30, 2018
636ab82
updating topics to use kafkaTopics CRD
hodrigohamalho Sep 3, 2018
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10 changes: 5 additions & 5 deletions rh-summit-2018/module-01.adoc
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Expand Up @@ -282,29 +282,29 @@ Now we can set up the Prometheus data source and the Kafka dashboard.

Access to the Grafana UI using `admin/admin` credentials.

image::grafana_login.png[grafana login]
image::images/grafana_login.png[grafana login]

Click on the "Add data source" button from the Grafana home in order to add Prometheus as data source.

image::grafana_home.png[grafana home]
image::images/grafana_home.png[grafana home]

Fill in the information about the Prometheus data source, specifying a name and "Prometheus" as type.
In the URL field, use `http://prometheus:9090` as the URL to the Prometheus server.
After "Add" is clicked, Grafana will test the connection to the data source.

image::grafana_prometheus_data_source.png[grafana prometheus data source]
image::images/grafana_prometheus_data_source.png[grafana prometheus data source]

From the top left menu, click on "Dashboards" and then "Import" to open the "Import Dashboard" window.
Open a browser tab and navigate to `https://raw.githubusercontent.com/strimzi/strimzi/0.3.0/metrics/examples/grafana/kafka-dashboard.json`.
You should see JSON content as response.
Copy and paste it in the appropriate field in the form.

image::grafana_import_dashboard.png[grafana import dashboard]
image::images/grafana_import_dashboard.png[grafana import dashboard]

After importing the dashboard, the Grafana home should show with some initial metrics about CPU and JVM memory usage.
When the Kafka cluster is used (creating topics and exchanging messages) the other metrics, like messages in and bytes in/out per topic, will be shown.

image::grafana_kafka_dashboard.png[grafana kafka dashboard]
image::images/grafana_kafka_dashboard.png[grafana kafka dashboard]

=== Handling cluster and topics

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14 changes: 7 additions & 7 deletions rh-summit-2018/module-02.adoc
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Expand Up @@ -2,7 +2,7 @@

The IoT demo is made by different components with the following architecture :

image::iot-demo.png[iot-demo]
image::images/iot-demo.png[iot-demo]

* one or more device simulators which sends temperature values to the `iot-temperature` topic;
* a stream application which uses Kafka Streams API in order to get data from the `iot-temperature` topic and process them to compute the maximum value (for each device) in the last 5 seconds; it writes the results to the `iot-temperature-max` topic;
Expand All @@ -19,7 +19,7 @@ Running the following command, a file containing two topic ConfigMaps is deploye
[source,sh]
$ oc create -f https://raw.githubusercontent.com/strimzi/strimzi-lab/master/iot-demo/stream-app/resources/topics.yml

image::topics.png[topics]
image::images/topics.png[topics]

In order to check that the topics are properly created on the Kafka cluster, it's possible to use the `kafka-topics.sh` script (distributed with Kafka) running it on one of the broker.

Expand All @@ -42,9 +42,9 @@ $ oc create -f https://raw.githubusercontent.com/strimzi/strimzi-lab/master/iot-

A route is provided in order to access the related Web UI.

image::route.png[route]
image::images/route.png[route]

image::web_ui.png[web ui]
image::images/web_ui.png[web ui]

=== Deploy the stream application

Expand All @@ -63,16 +63,16 @@ $ oc create -f https://raw.githubusercontent.com/strimzi/strimzi-lab/master/iot-

Once deployed, it starts just one pod simulating one device.

image::one_device_gauge.png[one device gauge]
image::images/one_device_gauge.png[one device gauge]

it's possible to scale up the number of pods in order to simulate more devices sending temperature values (each one with a different and randomly generated id).

image::scale_up_device.png[scale up device]
image::images/scale_up_device.png[scale up device]

Opening the consumer Web UI it's possible to see the "gauges" charts showing the processed max temperature values for all the active devices on the left side.
The right side is useful to see the log of the incoming messages from devices, showing the device id alongside the max temperature value processed by the stream application for such a device.

image::more_device_gauges.png[more device gauges]
image::images/more_device_gauges.png[more device gauges]

=== Clean up

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2 changes: 1 addition & 1 deletion rh-summit-2018/module-03.adoc
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Expand Up @@ -20,7 +20,7 @@ In this module of the lab you'll learn the following things:

The overall architecture of this lab module looks like this:

image::debezium-demo.png[debezium-demo]
image::images/debezium-demo.png[debezium-demo]

=== Setting Up the Example Application

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