Example online orders app composed of event-driven microservices. Built for QCon workshop.

https://drive.google.com/file/d/1vq1tcLk4FWK7BKRG5cEhOzbeXoy65hUK/view

• Create a Kafka cluster on Confluent Cloud
• Create topics, produce and consume events from commandline
• Using Kafka consumer and producer in a microservice to perform simple order validation.
• Implement a webservice that submits orders and uses "read-own-writes" pattern to show order status.
• Use Streams-to-Table join to send status updates by email.

• OSX or Linux
• Java 8
• Java development environment (Intellij recommended)
• Maven

1. Login to https://confluent.cloud with username and password you received by email from QCon.
2. Create a new cluster! call it “lastname-firstname”, make sure you use the smallest options, create it on Google Cloud Platform and use us-centeral1 region. You'll be shown the cost for the cluster. Don't worry about it - Confluent has been kind enough to sponsor the clusters and you will not be charged.
3. Follow the on-screen instructions closely to install Confluent Cloud CLI and initialize the CLI.
4. If you ran into issues, try to refer to the documentation here: https://docs.confluent.io/current/quickstart/cloud-quickstart.html.
5. If you managed to create a cluster, follow Step 3 of the Quickstart (https://docs.confluent.io/current/quickstart/cloud-quickstart.html) to create a topic and produce/consume some events.

1. Please clone this repository
2. Run mvn dependency:resolve to get dependencies in advance. This will help with the network in the class.

1. Lesson 0: Introduction to Kafka, topics and events:
   • What are event-driven microservices and why do we need them?
   • Overview of our Architecture
   • Key concepts of Apache Kafka
2. Lab 0:
   • Create a cluster in Confluent Cloud
   • Install the Confluent Cloud CLI
   • Create topic, produce and consume events from Cloud CLI
3. Lesson 1: Simple event validation:
   • "Hipster Stream Processing"
   • Producer and Consumer APIs
4. Lab 1:
   • git checkout lab1
   • Create topic orders with 3 partitions
   • Validate events and produce results to Kafka: Implement the TODO part of the OrderDetailsService. Note that validate() method implements the specific validation rules.
   • Build the service :) using mvn clean install
   • Test the simple validation service: Either using scripts/run_lab1.sh, writing a unit test, or a different method.
   • Extra credit: Use a produce method with error handling.
   • Extra credit: How would you use a rules engine?
   • Extra credit: How would you add multiple validators?
5. Lesson 2: CQRS-based web-service with Kafka Streams
   • Introduction to Kafka Streams
   • Introducing local materialized views
   • Stream-table duality
   • Code review of web-service
6. Lab 2:
   • git checkout lab2
   • Run and experiment with web service:
     • Build the service :) using mvn clean install
     • Use scripts/run_lab2.sh to experiment with the service. Running the script will start the Order service and validation service. Pressing any key will run few pre-canned curl commands that use the service. Another click will cause the services to exit.
   • Add "check for validation" endpoint: Implement the TODO part of the OrderService. Note that we already have a simple GET endpoint that gets any order, we need a new endpoint that only returns validated orders.
   • Use the same script from earlier to experiment with the new endpoint.
   • Extra Credit: Implement blocking-POST that only returns after order was validated.
   • Extra Credit: How would you scale to multiple instances? (Hint: Look up interactive queries APIs for Kafka Streams)
7. Lesson 3 (if there is time): Simple email service
   • Stream-table join enrichment pattern
   • Global KTables
8. Lab 3 (if there is time):
   • git checkout lab3
   • Implement Stream-table join: Implement the two functions required for the join (marked as TODO)
   • Test email service using the CustomerProducer and OrderProducer clases:
     • Build the service :) using mvn clean install
     • Create a new topic CUSTOMERS for customer data
     • scripts/run_lab3.sh will run the data generators, validator and email service
     • You can write additional tests