Exactly-once processing challenges in HLD - Architecture Diagram

System Overview - Exactly-once processing challenges

This system ensures that each message or transaction is processed exactly once, avoiding duplicates or losses. It is critical for financial systems, order processing, and any scenario where repeated or missed processing causes errors.

Key requirements include handling retries, failures, and network issues without duplicating work or losing data.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
+-------------------+
|  Processing Service|
|  +-------------+  |
|  | Idempotency |  |
|  |  Store      |  |
|  +-------------+  |
+-------------------+
  |
  v
Message Queue <--> Idempotency Store
  |
  v
Database
  |
  v
Cache

Components

User

client

Initiates requests that require exactly-once processing

Load Balancer

load_balancer

Distributes incoming requests evenly to API Gateway instances

API Gateway

api_gateway

Receives client requests and routes them to processing services

Processing Service

service

Processes requests ensuring exactly-once semantics using idempotency checks

Idempotency Store

database

Stores unique request IDs and their processing status to prevent duplicates

Message Queue

queue

Buffers messages for asynchronous processing and retry handling

Database

database

Stores the main application data updated by processing service

Cache

cache

Speeds up read operations and reduces load on the database

Request Flow - 11 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → Processing Service

Processing Service → Idempotency Store

Processing Service → Message Queue

Message Queue → Processing Service

Processing Service → Database

Processing Service → Idempotency Store

Processing Service → Cache

Processing Service → API Gateway

API Gateway → User

Failure Scenario

Component Fails:Idempotency Store

Impact:Without idempotency checks, duplicate processing may occur causing inconsistent data or double charges.

Mitigation:Use a replicated and highly available idempotency store; fallback to strict locking or reject requests until recovery.

Architecture Quiz - 3 Questions

Which component prevents processing the same request multiple times?

A Cache

B Load Balancer

C Idempotency Store

D Message Queue

Design Principle

This architecture uses an idempotency store combined with a message queue to guarantee exactly-once processing. The idempotency store prevents duplicate processing by tracking request IDs. The message queue enables reliable asynchronous processing and retries without losing messages. Updating the cache after the database ensures fast reads with consistent data. This design balances reliability, scalability, and data correctness.

Practice

1. What is the main goal of exactly-once processing in distributed systems?

easy

A. To ensure each message or transaction is processed only once without duplicates or losses

B. To process messages as fast as possible without caring about duplicates

C. To allow multiple processing attempts for fault tolerance

D. To ignore message ordering for simplicity

Solution

1. Step 1: Understand exactly-once processing definition

   Exactly-once processing means each message or transaction is handled one time only, avoiding duplicates or losses.

2. Step 2: Compare options with definition

   To ensure each message or transaction is processed only once without duplicates or losses matches the definition exactly. Other options either ignore duplicates, allow multiple processing, or ignore ordering, which are not goals of exactly-once.

3. Final Answer:

   To ensure each message or transaction is processed only once without duplicates or losses -> Option A

4. Quick Check:

   Exactly-once = no duplicates or losses [OK]

Hint: Exactly-once means no duplicates, no losses [OK]

Common Mistakes:

• Confusing exactly-once with at-least-once or at-most-once
• Ignoring message loss scenarios
• Assuming speed over correctness

2. Which of the following is a key technique to achieve exactly-once processing?

easy

A. Processing messages in any order without tracking

B. Using unique message IDs and idempotent operations

C. Ignoring message duplicates and retrying indefinitely

D. Dropping messages after first failure

Solution

1. Step 1: Identify techniques for exactly-once

   Exactly-once requires unique IDs to detect duplicates and idempotent operations to safely retry without side effects.

2. Step 2: Evaluate options

   Using unique message IDs and idempotent operations correctly lists these techniques. Options A, B, and D either ignore tracking or order, ignore duplicates, or drop messages, which break exactly-once guarantees.

3. Final Answer:

   Using unique message IDs and idempotent operations -> Option B

4. Quick Check:

   Unique IDs + idempotency = exactly-once [OK]

Hint: Unique IDs + idempotent ops ensure exactly-once [OK]

Common Mistakes:

• Assuming retries alone guarantee exactly-once
• Ignoring idempotency importance
• Not using unique identifiers

3. Consider a system where a message with ID 123 is processed twice due to a retry. The processing function is idempotent. What is the expected outcome?

medium

A. The second processing has no additional effect, preserving exactly-once semantics

B. The message is processed twice causing duplicate side effects

C. The system crashes due to duplicate message ID

D. The message is ignored completely

Solution

1. Step 1: Understand idempotent processing

   Idempotent means running the same operation multiple times has the same effect as running it once.

2. Step 2: Analyze retry with same message ID

   Since the function is idempotent, the second processing does not cause duplicate side effects, preserving exactly-once behavior.

3. Final Answer:

   The second processing has no additional effect, preserving exactly-once semantics -> Option A

4. Quick Check:

   Idempotent retry = no duplicate effect [OK]

Hint: Idempotent means retry won't duplicate effects [OK]

Common Mistakes:

• Assuming retries always cause duplicates
• Confusing idempotency with no retries
• Thinking system crashes on duplicate IDs

4. A system designed for exactly-once processing is dropping some messages after retries fail. What is the likely cause?

medium

A. Using unique IDs for messages

B. Retrying messages indefinitely

C. Implementing idempotent operations

D. Lack of transactional guarantees causing message loss

Solution

1. Step 1: Identify cause of message drops

   Dropping messages after retries usually means the system lacks transactional guarantees to ensure messages are not lost.

2. Step 2: Evaluate options

   Lack of transactional guarantees causing message loss correctly identifies this cause. Options A and C help prevent duplicates, and D would avoid drops by retrying indefinitely.

3. Final Answer:

   Lack of transactional guarantees causing message loss -> Option D

4. Quick Check:

   Missing transactions = message loss [OK]

Hint: No transactions cause message loss on failure [OK]

Common Mistakes:

• Confusing idempotency with message loss prevention
• Assuming retries always prevent drops
• Ignoring transactional role

5. You are designing a payment processing system that must guarantee exactly-once processing despite network failures. Which combination of strategies best ensures this?

hard

A. Drop duplicate payments and rely on manual reconciliation

B. Retry payments without tracking IDs and ignore failures

C. Use unique transaction IDs, idempotent payment operations, and a transactional message queue

D. Process payments asynchronously without acknowledgments

Solution

1. Step 1: Identify requirements for exactly-once in payments

   Payments must not be duplicated or lost, even with network failures.

2. Step 2: Evaluate strategies

   Unique transaction IDs detect duplicates, idempotent operations prevent repeated side effects, and transactional queues ensure atomic message delivery.

3. Step 3: Compare options

   Use unique transaction IDs, idempotent payment operations, and a transactional message queue combines all needed strategies. Options A, B, and C risk duplicates, losses, or manual errors.

4. Final Answer:

   Use unique transaction IDs, idempotent payment operations, and a transactional message queue -> Option C

5. Quick Check:

   IDs + idempotency + transactions = exactly-once [OK]

Hint: Combine IDs, idempotency, and transactions for exactly-once [OK]

Common Mistakes:

• Ignoring transactional guarantees
• Not using unique IDs
• Relying on manual fixes