Cache-aside pattern in HLD - Architecture Diagram

System Overview - Cache-aside pattern

The Cache-aside pattern helps improve data read performance by using a cache to store frequently accessed data. When an application needs data, it first checks the cache. If the data is missing, it loads from the database and then stores it in the cache for future requests.

This pattern reduces database load and speeds up response times while keeping data consistent.

Architecture Diagram

User
  |
  v
Load Balancer
  |
  v
Application Service
  |
  +-----> Cache
  |         |
  |         v
  |      Database
  |
  v
Response

Components

User

client

Initiates requests to the system

Load Balancer

load_balancer

Distributes incoming requests evenly to application instances

Application Service

service

Handles business logic, checks cache, queries database if needed

Cache

cache

Stores frequently accessed data for fast retrieval

Database

database

Persistent storage of all data

Request Flow - 9 Hops

User → Load Balancer

Load Balancer → Application Service

Application Service → Cache

Cache → Application Service

Application Service → Database

Database → Application Service

Application Service → Cache

Application Service → Load Balancer

Load Balancer → User

Failure Scenario

Component Fails:Cache

Impact:Cache misses increase, causing all requests to hit the database, increasing latency and load

Mitigation:System continues to function by querying the database directly; cache can be restored or replaced without data loss

Architecture Quiz - 3 Questions

In the Cache-aside pattern, what happens when the requested data is not found in the cache?

A The cache automatically fetches data from the database

B The application returns an error to the user

C The application queries the database and then updates the cache with the data

D The load balancer retries the request

Design Principle

The Cache-aside pattern improves read performance by letting the application control cache population. It ensures data freshness by loading data from the database only on cache misses, reducing database load and speeding up responses.

Practice

1. What is the main purpose of the cache-aside pattern in system design?

easy

A. To load data into cache only when it is requested

B. To preload all data into cache before any request

C. To write data directly to cache without database interaction

D. To keep cache and database completely separate without synchronization

Solution

1. Step 1: Understand cache-aside pattern behavior

   The cache-aside pattern loads data into cache only when the application requests it and the data is not already cached.

2. Step 2: Compare options with this behavior

   To load data into cache only when it is requested correctly states this lazy loading approach. Other options describe preloading or unsynchronized caching, which are incorrect.

3. Final Answer:

   To load data into cache only when it is requested -> Option A

4. Quick Check:

   Cache-aside = lazy loading on demand [OK]

Hint: Cache-aside loads data only when requested [OK]

Common Mistakes:

• Thinking cache preloads all data
• Assuming cache updates happen before DB writes
• Believing cache and DB are unsynchronized

2. Which of the following is the correct sequence of operations in the cache-aside pattern when reading data?

easy

A. Read from database -> Update cache -> Return data

B. Read from cache -> If miss, read from database -> Update cache

C. Update cache -> Read from cache -> Read from database

D. Read from cache -> Return data without checking database

Solution

1. Step 1: Recall cache-aside read flow

   When reading, the system first checks the cache. If data is missing (cache miss), it reads from the database and then updates the cache.

2. Step 2: Match this flow to options

   Read from cache -> If miss, read from database -> Update cache matches this exact sequence. Other options either skip cache miss handling or update cache before reading.

3. Final Answer:

   Read from cache -> If miss, read from database -> Update cache -> Option B

4. Quick Check:

   Cache read -> DB read on miss -> Cache update [OK]

Hint: Cache read first, DB read only if cache miss [OK]

Common Mistakes:

• Updating cache before reading database
• Ignoring cache miss and reading only cache
• Reading database before checking cache

3. Consider this pseudocode using cache-aside pattern:

function getUser(id) {
  user = cache.get(id)
  if (user == null) {
    user = database.query(id)
    cache.set(id, user)
  }
  return user
}

What will getUser(5) return if the cache is empty and the database has user with id 5?

medium

A. null

B. Error due to cache miss

C. Empty object

D. User data from database

Solution

1. Step 1: Analyze cache miss handling

   Since cache is empty, cache.get(5) returns null, triggering database query.

2. Step 2: Database query and cache update

   The function queries the database for user id 5, finds the user data, updates the cache, and returns the user data.

3. Final Answer:

   User data from database -> Option D

4. Quick Check:

   Cache miss triggers DB read and cache update [OK]

Hint: Cache miss leads to DB read and cache update [OK]

Common Mistakes:

• Assuming cache miss returns null directly
• Expecting error on cache miss
• Ignoring cache update after DB read

4. A developer implemented cache-aside but notices stale data in cache after database updates. What is the likely mistake?

medium

A. Not updating cache after database write

B. Reading from cache before database

C. Preloading cache with all data

D. Using cache for write operations only

Solution

1. Step 1: Identify cause of stale cache

   Stale cache means cache has old data not reflecting recent database updates.

2. Step 2: Check cache update after DB write

   If cache is not updated or invalidated after database writes, stale data remains in cache.

3. Final Answer:

   Not updating cache after database write -> Option A

4. Quick Check:

   Cache must update after DB write to avoid stale data [OK]

Hint: Always update cache after DB write to avoid stale data [OK]

Common Mistakes:

• Ignoring cache invalidation after writes
• Assuming cache updates automatically
• Confusing read and write cache operations

5. You design a high-traffic product catalog service using cache-aside pattern. To handle frequent updates and reads, which strategy best maintains cache consistency and performance?

hard

A. Preload entire product catalog into cache at service start and never update cache

B. On product update, write to DB only and let cache expire naturally

C. On product update, write to DB then immediately update cache with new data

D. Write updates only to cache and asynchronously sync to DB later

Solution

1. Step 1: Understand cache consistency needs

   For frequent updates and reads, cache must reflect latest data quickly to avoid stale reads.

2. Step 2: Evaluate update strategies

   On product update, write to DB then immediately update cache with new data updates DB then cache immediately, ensuring cache consistency and fast reads. On product update, write to DB only and let cache expire naturally risks stale cache. Preload entire product catalog into cache at service start and never update cache ignores updates. Write updates only to cache and asynchronously sync to DB later risks data loss and inconsistency.

3. Final Answer:

   On product update, write to DB then immediately update cache with new data -> Option C

4. Quick Check:

   Update DB then cache for consistency and performance [OK]

Hint: Update DB then cache immediately for fresh data [OK]

Common Mistakes:

• Relying on cache expiration alone
• Preloading cache without updates
• Writing only to cache without DB sync