How to disable Redis Caching at run time if redis

Question

We have rest api application. We use redis for API response caching and internal method caching. If redis connection then it is making our API down. We want to bypass the redis caching if that redis connection fails or any exception instead of making our API down. There is a interface CacheErrorHandler but it handles the redis get set operation failures not redis connection problems. We are using Spring 4.1.2.

Answer 1

actually my response is directed to Mr. @Vivek Aditya - I faced the same problem: new spring-data-redis api and not constructing RedisCacheManager per RedisTemplate. The only option - based on @John Blum suggestions - was to use aspects. And below is my code.

@Aspect
@Component
public class FailoverRedisCacheAspect {

    private static class FailoverRedisCache extends RedisCache {

        protected FailoverRedisCache(RedisCache redisCache) {
            super(redisCache.getName(), redisCache.getNativeCache(), redisCache.getCacheConfiguration());
        }

        @Override
        public <T> T get(Object key, Callable<T> valueLoader) {
            try {
                return super.get(key, valueLoader);
            } catch (RuntimeException ex) {
                return valueFromLoader(key, valueLoader);
            }
        }

        private <T> T valueFromLoader(Object key, Callable<T> valueLoader) {
            try {
                return valueLoader.call();
            } catch (Exception e) {
                throw new ValueRetrievalException(key, valueLoader, e);
            }
        }
    }

    @Around("execution(* org.springframework.cache.support.AbstractCacheManager.getCache (..))")
    public Cache beforeSampleCreation(ProceedingJoinPoint proceedingJoinPoint) {
        try {
            Cache cache = (Cache) proceedingJoinPoint.proceed(proceedingJoinPoint.getArgs());
            if (cache instanceof RedisCache) {
                return new FailoverRedisCache((RedisCache) cache);
            } else {
                return cache;
            }
        } catch (Throwable ex) {
            return null;
        }
    }
}

works fine for all reasonable scenarios:

• app starts fine with redis down
• app (still) works during (sudden) redis outage
• when redis starts working again, app sees it

Edit: the code is more like a poc - only for "get", and I don't like reinstantiating FailoverRedisCache every single cache hit - there should be a map.

Answer 2

Thank you @John Blum. My solution in Spring Boot is as follows.

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.cache.Cache;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.core.RedisOperations;
import org.springframework.util.Assert;

import java.util.concurrent.Callable;

class CustomRedisCacheManager extends RedisCacheManager {
    private static Logger logger = LoggerFactory.getLogger(CustomRedisCacheManager.class);

    public CustomRedisCacheManager(RedisOperations redisOperations) {
        super(redisOperations);
    }

    @Override
    public Cache getCache(String name) {
        return new RedisCacheWrapper(super.getCache(name));
    }


    protected static class RedisCacheWrapper implements Cache {

        private final Cache delegate;

        public RedisCacheWrapper(Cache redisCache) {
            Assert.notNull(redisCache, "delegate cache must not be null");
            this.delegate = redisCache;
        }

        @Override
        public String getName() {
            try {
                return delegate.getName();
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public Object getNativeCache() {
            try {
                return delegate.getNativeCache();
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public Cache.ValueWrapper get(Object key) {
            try {
                return delegate.get(key);
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public <T> T get(Object o, Class<T> aClass) {
            try {
                return delegate.get(o, aClass);
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public <T> T get(Object o, Callable<T> callable) {
            try {
                return delegate.get(o, callable);
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public void put(Object key, Object value) {
            try {
                delegate.put(key, value);
            } catch (Exception e) {
                handleException(e);
            }
        }

        @Override
        public ValueWrapper putIfAbsent(Object o, Object o1) {
            try {
                return delegate.putIfAbsent(o, o1);
            } catch (Exception e) {
                return handleException(e);
            }
        }

        @Override
        public void evict(Object o) {
            try {
                delegate.evict(o);
            } catch (Exception e) {
                handleException(e);
            }
        }

        @Override
        public void clear() {
            try {
                delegate.clear();
            } catch (Exception e) {
                handleException(e);
            }
        }

        private <T> T handleException(Exception e) {
            logger.error("handleException", e);
            return null;
        }
    }
}

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.cache.RedisCacheManager;
import org.springframework.data.redis.core.RedisTemplate;

@Configuration
public class RedisConfig {
    @Bean
    public RedisCacheManager redisCacheManager(RedisTemplate redisTemplate) {
        CustomRedisCacheManager redisCacheManager = new CustomRedisCacheManager(redisTemplate);
        redisCacheManager.setUsePrefix(true);
        return redisCacheManager;
    }
}

Answer 3

All the core Spring Framework Cache abstraction annotations (e.g. @Cacheable) along with the JSR-107 JCache annotations supported by the core SF delegate to the underlying CacheManager under-the-hood, and for Redis, that is the RedisCacheManager.

You would configure the RedisCacheManager in Spring XML configuration meta-data similar to here.

One approach would be to write an AOP Proxy for the (Redis)CacheManager that uses the RedisConnection (indirectly from the RedisTemplate) to ascertain the state of the connection on each (Redis)CacheManger operation.

If the connection has failed, or is closed, for standard cache ops, the (Redis)CacheManager could return an instance of RedisCache for getCache(String name) that always returns null (indicating a Cache miss on an entry), thus passing through to the underlying data store.

There maybe better ways to handle this as I am not an expert on all things Redis (or SDR), but this should work and perhaps give you a few ides of your own.

Cheers.

Answer 4

Let's boil this down a bit. Your application uses caching (implemented with Redis). If the Redis connection is stale/closed or otherwise, then you want the application to bypass caching and (presumably) go directly to an underlying data store (e.g. RDBMS). The application Service logic might look similar to...

@Service
class CustomerService ... {

    @Autowired
    private CustomerRepository customerRepo;

    protected CustomerRepository getCustomerRepo() {
        Assert.notNull(customerRepo, "The CustomerRepository was not initialized!");
        return customerRepo;
    }

    @Cacheable(value = "Customers")
    public Customer getCustomer(Long customerId) {
        return getCustomerRepo().load(customerId);
    }
    ...
}

All that matters in Spring core's Caching Abstraction to ascertain a Cache "miss" is that the value returned is null. As such, Spring Caching Infrastructure will then proceed in calling the actual Service method (i.e. getCustomer). Keep in mind on the return of the getCustomerRepo().load(customerId) call, you also need to handle the case where Spring's Caching Infrastructure attempts to now cache the value.

In the spirit of keeping it simple, we will do without AOP, but you should be able to achieve this using AOP as well (your choice).

All you (should) need is a "custom" RedisCacheManager extending the SDR CacheManager implementation, something like...

package example;

import org.springframework.cache.Cache;
import org.springframework.data.redis.cache.RedisCacheManager;
...

class MyCustomRedisCacheManager extends RedisCacheManager {

    public MyCustomerRedisCacheManager(RedisTemplate redisTemplate) {
        super(redisTemplate);
    }

    @Override
    public Cache getCache(String name) {
        return new RedisCacheWrapper(super.getCache(name));
    }


    protected static class RedisCacheWrapper implements Cache {

        private final Cache delegate;

        public RedisCacheWrapper(Cache redisCache) {
            Assert.notNull(redisCache, "'delegate' must not be null");
            this.delegate = redisCache;
        }

        @Override
        public Cache.ValueWrapper get(Object key) {
            try {
              delegate.get(key);
            }
            catch (Exception e) {
                return handleErrors(e);
            }
        }

        @Override
        public void put(Object key, Object value) {
            try {
                delegate.put(key, value);
            }
            catch (Exception e) {
                handleErrors(e);
            }
        }

        // implement clear(), evict(key), get(key, type), getName(), getNativeCache(), putIfAbsent(key, value) accordingly (delegating to the delegate).

        protected <T> T handleErrors(Exception e) throws Exception {
            if (e instanceof <some RedisConnection Exception type>) {
                // log the connection problem
                return null;
            }
            else if (<something different>) { // act appropriately }
            ...
            else {
                throw e;
            }
        }
    }
}

So, if Redis is unavailable, perhaps the best you can do is log the problem and proceed to let the Service invocation happen. Clearly, this will hamper performance but at least it will raise awareness that a problem exists. Clearly, this could be tied into a more robust notification system, but it is a crude example of the possibilities. The important thing is, your Service remains available while the other services (e.g. Redis) that the application service depends on, may have failed.

In this implementation (vs. my previous explanation) I chose to delegate to the underlying, actual RedisCache implementation to let the Exception occur, then knowing full well a problem with Redis exists, and so that you can deal with the Exception appropriately. However, if you are a certain that the Exception is related to a connection problem upon inspection, you can return "null" to let Spring Caching Infrastructure proceed as if it were a Cache "miss" (i.e. bad Redis Connection == Cache miss, in this case).

I know something like this should help your problem as I built a similar prototype of a "custom" CacheManager implementation for GemFire and one of Pivotal's customers. In that particular UC, the Cache "miss" had to be triggered by an "out-of-date version" of the application domain object where production had a mix of newer and older application clients connecting to GemFire through Spring's Caching Abstraction. The application domain object fields would change in newer versions of the app for instance.

Anyway, hope this helps or gives you more ideas.

Cheers!

Answer 5

So, I was digging through the core Spring Framework Caching Abstraction source today addressing another question and it seems if a CacheErrorHandler is implemented properly, then perhaps a problematic Redis Connection could still result in the desired behavior, e.g. cache "miss" (triggered with the return of a null value).

See the AbstractCacheInvoker source for more details.

The cache.get(key) should result in an exception due to a faulty Redis Connection and thus Exception handler would be invoked...

catch (RuntimeException e) {
    getErrorHandler().handleCacheGetError(e, cache, key);
    return null; // If the exception is handled, return a cache miss
}

If the CacheErrorHandler properly handles the Cache "get" error (and does not re-throw the/an Exception), then a null value will be returned indicating a cache "miss".