110 lines
3.6 KiB
Markdown
110 lines
3.6 KiB
Markdown
# SCS-100-2
|
||
|
||
## Functional Programming (For Alternative of SCS-100 Project)
|
||
|
||
A simple Example of an Event Driven Flow by the help of **SPRING CLOUD STREAM KAFKA**
|
||
|
||
##### properties
|
||
|
||
* java.version: `11`
|
||
* spring-cloud.version: `2020.0.3`
|
||
* spring-boot.version: `2.5.2`
|
||
|
||
### Documentation
|
||
Please visit [Spring Cloud Stream Kafka (Part 3)](https://tanzu.vmware.com/developer/guides/event-streaming/spring-cloud-stream-kafka-p3/) for Project documentation
|
||
|
||
|
||
|
||
|
||
The Docker-compose file contains: single kafka and zookeeper. just simply run the following command
|
||
|
||
```shell
|
||
docker-compose up -d
|
||
```
|
||
|
||
> I assume you already have docker setup in your machine.
|
||
|
||
### Make the project
|
||
|
||
run the following command line to create you jar file in `target` directory
|
||
|
||
```shell
|
||
mvn clean package
|
||
```
|
||
|
||
Then run the generated jar file in `target` folder, (so make sure you are in the same directory when you run the jar
|
||
file or give the full path)
|
||
|
||
```shell
|
||
java -jar scs-100-0.0.1-SNAPSHOT.jar
|
||
```
|
||
|
||
the application starts to listen on port 8080.
|
||
|
||
**To scale** the application horizontally you can add the following parameter before `-jar` by
|
||
adding `-Dserver.port=8081` (basically a different port) as:
|
||
|
||
```shell
|
||
java -Dserver.port=8081 -jar scs-100-0.0.1-SNAPSHOT.jar
|
||
```
|
||
|
||
> When you running multiple instances of the same application on a single machine, this path must be unique for each
|
||
such instance.
|
||
At this point you should have already seen the information about your topics
|
||
, [to read more](https://kafka.apache.org/28/documentation/streams/developer-guide/config-streams.html#state-dir)
|
||
|
||
### Check Application
|
||
|
||
#### Create Order or Place your Order
|
||
|
||
you should now be able to place your order by calling the following `curl` command
|
||
|
||
```shell
|
||
# assuming your app is listening on 8080
|
||
ORDER_UUID=$(curl --silent -H 'Content-Type: application/json' -d "{\"itemName\":\"book\"}" http://localhost:8080/order | jq -r '.orderUuid') && for i in `seq 1 15`; do sleep 1; echo $(curl --silent "http://localhost:8080/order/status/"$ORDER_UUID); done;
|
||
```
|
||
|
||
Note: make sure you have already installed the `jq`
|
||
|
||
## Running Multi Instances
|
||
|
||
Now let’s run the same application multiple times at the same time to simulate the application redundancy. But before
|
||
that make sure that the current application is not running.
|
||
|
||
This project code comes with Nginx as LoadBalancer which has already been configured to distribute the incoming traffic
|
||
from port 8080 and route it into 8081 and 8082.
|
||
|
||
So first let’s start it in different docker-compose from root on this project “scs-100-2” as:
|
||
|
||
```shell
|
||
docker-compose -f nginx/docker-compose.yml up -d
|
||
```
|
||
|
||
Since the port 8080 is already got occupied by nginx we can run the Ordering application as follow in 2 separated
|
||
terminal
|
||
|
||
_Terminal 1:_
|
||
|
||
```shell
|
||
java -Dserver.port=8081 -jar target/scs-100-2-0.0.1-SNAPSHOT.jar
|
||
```
|
||
|
||
_And on Terminal 2:_
|
||
|
||
```shell
|
||
java -Dserver.port=8082 -jar target/scs-100-2-0.0.1-SNAPSHOT.jar
|
||
```
|
||
|
||
|
||
|
||
_Then run our curl call command again (same as the earlier one)_
|
||
|
||
```shell
|
||
ORDER_UUID=$(curl --silent -H 'Content-Type: application/json' -d "{\"itemName\":\"book\"}" http://localhost:8080/order | jq -r '.orderUuid') && for i in `seq 1 15`; do sleep 1; echo $(curl --silent "http://localhost:8080/order/status/"$ORDER_UUID); done;
|
||
```
|
||
|
||
|
||
|
||
|
||
Please visit [Spring Cloud Stream Kafka (Part 3)](https://tanzu.vmware.com/developer/guides/event-streaming/spring-cloud-stream-kafka-p3/) for Project documentation
|