Redis as cache provider in Spring Boot - Performance & Optimization

Performance: Redis as cache provider

HIGH IMPACT

This affects page load speed by reducing backend response time and lowering server load through fast data retrieval.

Caching frequently accessed data to speed up response

Spring Boot

public String getData(String key) {
  String cached = redis.get(key);
  if (cached != null) return cached;
  String data = database.query(key);
  redis.set(key, data);
  return data;
}

Data is served from Redis cache if available, avoiding slow database calls.

📈 Performance GainReduces backend response time by 50-90%, improving LCP

Caching frequently accessed data to speed up response

Spring Boot

public String getData(String key) {
  // No caching, always fetch from database
  return database.query(key);
}

Every request hits the database causing slow responses and high server load.

📉 Performance CostBlocks rendering for 100+ ms per request depending on DB speed

Performance Comparison

Pattern	DOM Operations	Reflows	Paint Cost	Verdict
No cache, direct DB calls	N/A	N/A	High backend delay delays paint	[X] Bad
Redis cache for frequent data	N/A	N/A	Fast backend response speeds paint	[OK] Good

Rendering Pipeline

Using Redis cache shortens backend processing time, allowing the server to send data faster to the browser, which speeds up the critical rendering path.

→Backend Processing

→Network Transfer

→First Paint

⚠️ BottleneckBackend Processing when database queries are slow

Core Web Vital Affected

LCP

This affects page load speed by reducing backend response time and lowering server load through fast data retrieval.

Optimization Tips

1Cache frequently accessed data in Redis to reduce backend response time.

2Avoid cache misses by pre-warming Redis with common queries.

3Monitor cache hit ratio to ensure Redis is effectively improving performance.

Performance Quiz - 3 Questions

How does using Redis as a cache provider affect Largest Contentful Paint (LCP)?

A It reduces LCP by serving data faster from cache.

B It increases LCP by adding extra network calls.

C It has no effect on LCP.

D It only affects Cumulative Layout Shift (CLS).

DevTools: Network

How to check: Open DevTools > Network tab, reload page, check response times for API calls.

What to look for: Look for reduced response times on repeated requests indicating cache hits.

Practice

1. What is the main purpose of using Redis as a cache provider in a Spring Boot application?

easy

A. To store frequently accessed data in memory for faster retrieval

B. To replace the database completely

C. To handle user authentication

D. To serve static web pages

Solution

1. Step 1: Understand Redis caching role

   Redis stores data in memory, which is much faster than disk storage.

2. Step 2: Identify caching benefit in Spring Boot

   Caching reduces database calls by storing frequently used data temporarily.

3. Final Answer:

   To store frequently accessed data in memory for faster retrieval -> Option A

4. Quick Check:

   Redis cache = fast data access [OK]

Hint: Redis cache speeds up data access by storing in memory [OK]

Common Mistakes:

• Thinking Redis replaces the database
• Confusing caching with authentication
• Assuming Redis serves static files

2. Which annotation is used in Spring Boot to enable caching support when using Redis?

easy

A. @RedisCache

B. @Cacheable

C. @EnableCaching

D. @CacheConfig

Solution

1. Step 1: Identify the annotation to activate caching

   @EnableCaching is used on a configuration class to turn on caching support.

2. Step 2: Differentiate from other annotations

   @Cacheable marks methods to cache results, but does not enable caching globally.

3. Final Answer:

   @EnableCaching -> Option C

4. Quick Check:

   Enable caching = @EnableCaching [OK]

Hint: Use @EnableCaching to activate caching in Spring Boot [OK]

Common Mistakes:

• Confusing @Cacheable with enabling caching
• Using non-existent @RedisCache annotation
• Mistaking @CacheConfig for enabling caching

3. Given the following Spring Boot method with Redis caching:

@Cacheable("books")
public Book findBookById(Long id) {
    System.out.println("Fetching from DB");
    return bookRepository.findById(id).orElse(null);
}

What will be printed if findBookById(1L) is called twice in a row?

medium

A. Fetching from DB

B. No output

C. Fetching from DB
Fetching from DB

D. Error at runtime

Solution

1. Step 1: Understand @Cacheable behavior

   The first call caches the result and prints "Fetching from DB".

2. Step 2: Analyze second call output

   The second call returns cached data without executing method body, so no print.

3. Final Answer:

   Fetching from DB -> Option A

4. Quick Check:

   Cache avoids repeated DB fetch print [OK]

Hint: First call prints, second uses cache silently [OK]

Common Mistakes:

• Expecting print on every call
• Thinking cache disables method
• Assuming runtime error due to caching

4. Consider this Spring Boot Redis cache configuration snippet:

@Bean
public RedisCacheManager cacheManager(RedisConnectionFactory factory) {
    return RedisCacheManager.builder(factory).build();
}

If the Redis server is down, what will happen when the application tries to cache data?

medium

A. Application falls back to file-based cache

B. Application throws a runtime exception and crashes

C. Data is cached in memory without Redis

D. Caching silently fails but application continues

Solution

1. Step 1: Understand RedisCacheManager dependency

   RedisCacheManager requires a running Redis server to store cache data.

2. Step 2: Analyze behavior if Redis is down

   Without Redis, cache operations typically fail silently and the application continues unless explicitly configured to fail.

3. Final Answer:

   Caching silently fails but application continues -> Option D

4. Quick Check:

   Redis down usually does not crash app by default [OK]

Hint: Redis down causes silent cache failure unless handled [OK]

Common Mistakes:

• Assuming fallback to memory cache
• Thinking caching silently fails
• Expecting file-based fallback

5. You want to cache the result of a method that returns a list of users filtered by role. Which is the best way to use Redis caching in Spring Boot to avoid caching empty or null results?

public List<User> getUsersByRole(String role) {
    // fetch users
}

hard

A. Use @CachePut to always update cache

B. Use @Cacheable with condition = "#result != null && !#result.isEmpty()"

C. Manually check and cache inside the method

D. Use @Cacheable without any condition

Solution

1. Step 1: Understand caching empty results issue

   Caching empty or null results wastes cache space and may cause stale data.

2. Step 2: Use @Cacheable condition attribute

   Adding condition "#result != null && !#result.isEmpty()" caches only meaningful results.

3. Final Answer:

   Use @Cacheable with condition = "#result != null && !#result.isEmpty()" -> Option B

4. Quick Check:

   Condition filters empty cache entries [OK]

Hint: Use @Cacheable condition to skip empty results [OK]

Common Mistakes:

• Caching all results including empty lists
• Manually caching inside method instead of annotation
• Using @CachePut which always updates cache