An example architecture used for managing product inventory which highlights the use of event collaboration with RabbitMQ.

The milk problem first surfaced while working with a well-known grocery store to track product inventory in real time. The choice of database was largely driven by a non-trivial performance requirement. The initial solution used an eventually consistent database which was available and partition tolerant. Read about the CAP theorem to learn more about the relationship between consistency, availability, and partition tolerance.

The challenge is that high availability comes at the cost of consistency. High availability databases are eventually consistent, and thus are notorious for dirty reads: allowing uncommitted changes from one transaction to affect a read in another transaction. As a result, the grocery chain was unable to produce an accurate count of milk on the shelves.

The below exercise introduces the reader to transactions while highlighting the challenges of dirty reads. We then move to event collaboration with RabbitMQ while highlighting the challenges with messaging systems.

Start with the TODO - DIRTY READS items, then get the tests to pass!

• Remove dirty reads.
• Ensure the correct product quantities.

Once you're done, continue to the TODO - MESSAGING items and get the tests to pass.

• Reflect on automatic acknowledgement.
• Reflect on manual acknowledgement.

Here are a few links to supporting documentation.

• Introduction
• Work Queues

The below steps walk through the environment setup necessary to run the application in both local and production environments.

1. Install and start Docker.

2. Run Docker Compose.

   docker-compose up

1. Migrate the test database with Flyway.

   FLYWAY_CLEAN_DISABLED=false flyway -user=milk -password=milk -url="jdbc:postgresql:https://localhost:5432/milk_test" -locations=filesystem:databases/milk clean migrate

2. Migrate the development database with Flyway.

   FLYWAY_CLEAN_DISABLED=false flyway -user=milk -password=milk -url="jdbc:postgresql:https://localhost:5432/milk_development" -locations=filesystem:databases/milk clean migrate

3. Populate development data with a product scenario.

   PGPASSWORD=milk psql -h'127.0.0.1' -Umilk -f applications/products-server/src/test/resources/scenarios/products.sql milk_development

Use Gradle to run tests. You'll see a few failures at first.

./gradlew build

1. Use Gradle to run the products server

   ./gradlew applications:products-server:run

2. Use Gradle to run the simple client

   ./gradlew applications:simple-http-client:run

Hope you enjoy the exercise!

Thanks,

The IC Team

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