Inventory management in LLD - Architecture Diagram

System Overview - Inventory management

This inventory management system helps businesses track product stock levels, update inventory after sales or restocking, and provide real-time availability information. It must handle many users updating and querying inventory simultaneously with accuracy and speed.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
API Gateway
  |
  v
Inventory Service <-> Cache
  |
  v
Database

Components

User

client

Sends requests to check or update inventory

Load Balancer

load_balancer

Distributes incoming user requests evenly to API Gateway instances

API Gateway

api_gateway

Receives requests, handles authentication, routing to Inventory Service

Inventory Service

service

Processes inventory queries and updates business logic

Cache

cache

Stores frequently accessed inventory data for fast reads

Database

database

Stores persistent inventory records and updates

Request Flow - 10 Hops

User → Load Balancer

Load Balancer → API Gateway

API Gateway → Inventory Service

Inventory Service → Cache

Cache → Inventory Service

Inventory Service → Database

Database → Inventory Service

Inventory Service → Cache

Inventory Service → API Gateway

API Gateway → User

Failure Scenario

Component Fails:Database

Impact:Inventory updates fail; reads may serve stale data from cache

Mitigation:Use database replication for failover; serve reads from cache with warning; queue updates for retry

Architecture Quiz - 3 Questions

Which component handles user authentication before processing inventory requests?

A API Gateway

B Load Balancer

C Inventory Service

D Cache

Design Principle

This design uses a cache to speed up frequent inventory reads and reduce database load. The load balancer and API Gateway provide scalability and security. The database stores persistent data with replication for reliability. This layered approach balances speed, accuracy, and fault tolerance.

Practice

1. What is the primary purpose of an inventory management system?

easy

A. To track product quantities and prevent stock issues

B. To design product packaging

C. To manage employee schedules

D. To create marketing campaigns

Solution

1. Step 1: Understand inventory management goals

   Inventory management focuses on tracking product quantities to avoid running out or overstocking.

2. Step 2: Eliminate unrelated options

   Options about packaging, schedules, and marketing do not relate to inventory tracking.

3. Final Answer:

   To track product quantities and prevent stock issues -> Option A

4. Quick Check:

   Inventory management = tracking stock [OK]

Hint: Inventory systems track stock levels, not unrelated tasks [OK]

Common Mistakes:

• Confusing inventory with marketing or HR tasks
• Thinking inventory manages packaging design
• Assuming inventory handles employee schedules

2. Which of the following is the correct way to check if an item exists in an inventory dictionary named stock in Python?

easy

A. if stock.has_key('item'):

B. if 'item' in stock:

C. if stock.contains('item'):

D. if stock.exists('item'):

Solution

1. Step 1: Recall Python dictionary syntax

   To check if a key exists in a dictionary, use the in keyword.

2. Step 2: Identify correct syntax

   stock.has_key() is deprecated, and contains or exists are invalid methods.

3. Final Answer:

   if 'item' in stock: -> Option B

4. Quick Check:

   Use 'in' to check keys in dict [OK]

Hint: Use 'in' keyword to check keys in Python dicts [OK]

Common Mistakes:

• Using deprecated has_key() method
• Using non-existent methods like contains()
• Confusing method names for key checks

3. Given the Python code below, what will be the output?

stock = {'apple': 10, 'banana': 5}
stock['apple'] -= 3
print(stock['apple'])

medium

A. Error

B. 13

C. -3

D. 7

Solution

1. Step 1: Understand the initial stock

   Initially, 'apple' has quantity 10.

2. Step 2: Apply the subtraction operation

   Subtracting 3 from 10 results in 7.

3. Final Answer:

   7 -> Option D

4. Quick Check:

   10 - 3 = 7 [OK]

Hint: Subtract quantity correctly to find updated stock [OK]

Common Mistakes:

• Adding instead of subtracting
• Confusing keys or values
• Expecting an error due to subtraction

4. Identify the error in the following inventory update code snippet:

stock = {'apple': 5}
stock['banana'] -= 2
print(stock)

medium

A. No error, banana quantity becomes -2

B. SyntaxError due to invalid subtraction

C. KeyError because 'banana' does not exist in stock

D. TypeError because stock is not a list

Solution

1. Step 1: Check if 'banana' key exists

   'banana' is not in the stock dictionary initially.

2. Step 2: Understand dictionary behavior on missing keys

   Subtracting from a missing key causes a KeyError in Python.

3. Final Answer:

   KeyError because 'banana' does not exist in stock -> Option C

4. Quick Check:

   Missing key access = KeyError [OK]

Hint: Accessing missing dict keys causes KeyError [OK]

Common Mistakes:

• Assuming missing keys default to zero
• Expecting negative values without initialization
• Confusing error types

5. You are designing an inventory system that must handle multiple warehouses. Which design approach best ensures accurate stock counts across warehouses and prevents overselling?

hard

A. Maintain separate stock counts per warehouse and use transactions to update atomically

B. Keep a single global stock count without warehouse details

C. Update stock counts asynchronously without locking

D. Allow negative stock counts to handle overselling

Solution

1. Step 1: Consider multi-warehouse stock tracking

   Each warehouse should have its own stock count to track inventory accurately.

2. Step 2: Ensure atomic updates to prevent overselling

   Using transactions or locks ensures stock updates are consistent and prevent race conditions.

3. Final Answer:

   Maintain separate stock counts per warehouse and use transactions to update atomically -> Option A

4. Quick Check:

   Atomic updates + per-warehouse stock = accurate inventory [OK]

Hint: Use atomic transactions and per-warehouse counts [OK]

Common Mistakes:

• Using global stock ignores warehouse differences
• Updating asynchronously causes race conditions
• Allowing negative stock hides overselling problems