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John Shields edited this page Jan 27, 2021 · 1 revision

Kafka Assignment: Distributed Banking System

Project Architecture

Architecture

The distributed banking system is made up of the following micro-services:

  • Banking API Service: This is the entry point to the system. It receives customer card transactions from retailers and produces messages to the appropriate Kafka topics for processing by the other services. In a real system, this would receive transactions from a front-end GUI application or another banking system. In our simplified version, it reads customer transactions from a text file using the provided IncomingTransactionsReader. IncomingTransactionsReader provides methods similar to standard Java file IO to assist in reading customer transaction information:

    • public boolean hasNext(): return true if there is another transaction to read
    • public Transaction next(): reads the next transaction

    Each Transaction contains the following information:

    • User: the username of the user who made the purchase in that particular store
    • Amount: the amount of the purchase transaction
    • Transaction Location: the country in which the purchase transactions took place.

  • Customers Database: A database where we store each of our bank customers' home location. In a real system this would connect to a real database. In our simplified version it reads customer address information from a text file using the provided CustomerAddressDatabase, which maps user names to address locations. CustomerAddressDatabase provides the method public String getUserResidence(String user), which returns the address location for a given user.

  • User Notification Service: receives notifications of suspicious transactions that require customer approval.

  • Account Manager Service: receives notifications of valid transactions which can be processed normally (debit money from the customer's account to the stores account).

  • Reporting Service: receives notifications of all transactions received by the Banking API Service for further processing.

All the communication between these micro-services is achieved using Kafka Topics.

Part 1 Kafka Cluster Setup

The distributed banking system communicates using a fault-tolerant and scalable Kafka cluster set up as follows:

  • 3 Kafka brokers listening on ports 9092, 9093 and 9094
  • A topic called valid-transactions with 3 partitions and a replication factor of 3.
  • A topic called suspicious-transactions with 2 partitions and a replication factor of 3.

When set up correctly, the output of the kafka-topics script's --describe command for the two topics should look something like this:

Topic: valid-transactions       PartitionCount: 3       ReplicationFactor: 3    Configs: segment.bytes=1073741824
        Topic: valid-transactions       Partition: 0    Leader: 1       Replicas: 1,0,2 Isr: 1,0,2
        Topic: valid-transactions       Partition: 1    Leader: 0       Replicas: 0,2,1 Isr: 0,2,1
        Topic: valid-transactions       Partition: 2    Leader: 2       Replicas: 2,1,0 Isr: 2,1,0

Topic: suspicious-transactions  PartitionCount: 2       ReplicationFactor: 3    Configs: segment.bytes=1073741824
          Topic: suspicious-transactions  Partition: 0    Leader: 2       Replicas: 2,0,1 Isr: 2,0,1
          Topic: suspicious-transactions  Partition: 1    Leader: 1       Replicas: 1,2,0 Isr: 1,2,0

Part 2 - Implementation of the Distributed Banking System Micro-Services

Starter code was given for the micro-services with some parts of the functionality implemented. The task was to complete the implementation of each service, as described below:

  • bank-api-service
    • Processes customer transactions from a text file using the IncomingTransactionsReader class. Processing transactions involves:
      • Identifying the customer the transaction applies to using the user field of Transaction
      • Retrieving this customer's home address from the CustomerAddressDatabase.
      • Compare the transaction location with the customer's home address, and send a message to the appropriate Kafka topic:
        • If the locations match then it's a valid transaction and the message should be sent to the valid -transactions topic.
        • If the locations don't match then it's a suspicious transaction and the message should be sent to the suspicious-transactions topic.
      • The Kafka messages should have the following structure:
        • Key: user (String)
        • Value: Transaction
      • The classes IncomingTransactionsReader, CustomerAddressDatabase, and Transaction are provided for you. You'll need to complete the implementation of the bank-api-service.
  • user-notification-service
    • Receives Kafka messages with information on suspicious transactions from the suspicious-transactions topic.
    • Prints suspicious transaction information to the screen.
    • You'll need to complete the implementation of this service.
  • account-manager
    • Receives Kafka messages with information on valid transactions from the valid-transactions topic.
    • Prints valid transaction information to the screen.
    • You'll need to complete the implementation of this service.
  • reporting-service
    • Receives Kafka messages with information on all transactions from the valid-transactions and suspicious-transactions topics.
    • Prints all transaction information to the screen, using a different message for suspicious and valid transactions.
    • You'll need to complete the implementation of this service.

Kafka Cluster Setup

Kafka Cluster Setup

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