spring-data-redis
>
Works with
---
name: spring-data-redis
description: >
license: MIT
---
# Spring Data Redis
## Dependencies
```xml
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-cache</artifactId>
</dependency>
```
## Configuration
```java
@Configuration
@EnableCaching
public class RedisConfig {
@Bean
public RedisTemplate<String, Object> redisTemplate(RedisConnectionFactory factory) {
RedisTemplate<String, Object> template = new RedisTemplate<>();
template.setConnectionFactory(factory);
template.setKeySerializer(new StringRedisSerializer());
template.setValueSerializer(new GenericJackson2JsonRedisSerializer()); // JSON, not Java serialize
template.setHashKeySerializer(new StringRedisSerializer());
template.setHashValueSerializer(new GenericJackson2JsonRedisSerializer());
return template;
}
@Bean
public RedisCacheManager cacheManager(RedisConnectionFactory factory) {
RedisCacheConfiguration config = RedisCacheConfiguration.defaultCacheConfig()
.entryTtl(Duration.ofMinutes(10))
.serializeKeysWith(RedisSerializationContext.SerializationPair.fromSerializer(new StringRedisSerializer()))
.serializeValuesWith(RedisSerializationContext.SerializationPair.fromSerializer(new GenericJackson2JsonRedisSerializer()))
.disableCachingNullValues();
return RedisCacheManager.builder(factory)
.cacheDefaults(config)
.withCacheConfiguration("orders", config.entryTtl(Duration.ofMinutes(5)))
.withCacheConfiguration("products", config.entryTtl(Duration.ofHours(1)))
.build();
}
}
```
## Key Naming Convention
```
{app}:{domain}:{id} → orders:order:uuid-here
{app}:{domain}:list:{filter} → orders:order:list:status:PENDING
{app}:session:{userId} → orders:session:uuid-here
{app}:ratelimit:{ip} → orders:ratelimit:192.168.1.1
```
## @Cacheable — Declarative Caching
```java
@Service
@RequiredArgsConstructor
public class ProductService {
@Cacheable(value = "products", key = "#id")
public ProductResponse findById(UUID id) {
return productRepository.findById(id)
.map(ProductResponse::from)
.orElseThrow(() -> new EntityNotFoundException("Product not found: " + id));
}
@CachePut(value = "products", key = "#result.id") // update cache after write
@Transactional
public ProductResponse update(UUID id, UpdateProductRequest request) {
Product product = productRepository.findById(id).orElseThrow();
product.update(request);
return ProductResponse.from(productRepository.save(product));
}
@CacheEvict(value = "products", key = "#id") // invalidate on delete
@Transactional
public void delete(UUID id) {
productRepository.deleteById(id);
}
@CacheEvict(value = "products", allEntries = true) // clear all
public void clearCache() {}
}
```
## Manual Cache-Aside Pattern
```java
@Service
@RequiredArgsConstructor
public class OrderCacheService {
private final RedisTemplate<String, Object> redisTemplate;
private final ObjectMapper objectMapper;
private static final Duration TTL = Duration.ofMinutes(5);
public Optional<OrderResponse> get(UUID orderId) {
String key = "orders:order:" + orderId;
Object cached = redisTemplate.opsForValue().get(key);
if (cached == null) return Optional.empty();
return Optional.of(objectMapper.convertValue(cached, OrderResponse.class));
}
public void put(OrderResponse order) {
String key = "orders:order:" + order.id();
redisTemplate.opsForValue().set(key, order, TTL);
}
public void evict(UUID orderId) {
redisTemplate.delete("orders:order:" + orderId);
}
}
```
## Rate Limiting with Redis
```java
@Component
@RequiredArgsConstructor
public class RateLimiter {
private final RedisTemplate<String, String> redisTemplate;
public boolean isAllowed(String identifier, int maxRequests, Duration window) {
String key = "ratelimit:" + identifier;
Long count = redisTemplate.opsForValue().increment(key);
if (count == 1) {
redisTemplate.expire(key, window);
}
return count <= maxRequests;
}
}
```
## application.yml
```yaml
spring:
data:
redis:
host: ${REDIS_HOST:localhost}
port: ${REDIS_PORT:6379}
password: ${REDIS_PASSWORD:}
timeout: 2000ms
lettuce:
pool:
max-active: 10
max-idle: 5
min-idle: 2
cache:
type: redis
```
## Cache Stampede
When a hot key expires, every concurrent request misses at once and they all hammer the DB to recompute
the same value (the "thundering herd"). For expensive, high-traffic loads, let one caller compute while
the rest wait:
```java
// sync = true — only one thread computes the value; others block on it
@Cacheable(value = "products", key = "#id", sync = true)
public ProductResponse findById(UUID id) { ... }
```
`sync = true` serializes recomputation per key within a single instance. For a fleet-wide guarantee,
add a short Redis lock (`SETNX` with a TTL) around the recompute. Pair with jittered TTLs so a batch of
keys written together doesn't all expire on the same second.
## Gotchas
- Agent uses Java serialization for values — always use JSON (`GenericJackson2JsonRedisSerializer`)
- Agent caches entities with JPA lazy fields — cache DTOs/response objects, not entities
- Agent uses no TTL — always set expiry, memory is not infinite
- Agent forgets `@EnableCaching` — `@Cacheable` silently does nothing without it
- Agent caches `null` values — use `.disableCachingNullValues()` to avoid storing misses
- Agent leaves hot keys unprotected — use `@Cacheable(sync = true)` to prevent stampede on expiry
- Agent gives every entry the same TTL — add jitter so keys don't expire in a synchronized waveMore Database skills
supabase-postgres-best-practices
supabase/agent-skills
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
prisma-database-setup
prisma/skills
Guides for configuring Prisma with different database providers (PostgreSQL, MySQL, SQLite, MongoDB, etc.). Use when setting up a new project, changing databases, or troubleshooting connection issues. Triggers on "configure postgres", "connect to mysql", "setup mongodb", "sqlite setup".
prisma-postgres
prisma/skills
Prisma Postgres setup and operations guidance across Console, create-db CLI, Management API, and Management API SDK. Use when creating Prisma Postgres databases, working in Prisma Console, provisioning with create-db/create-pg/create-postgres, or integrating programmatic provisioning with service tokens or OAuth.

