Will full Redis memory affect other applications?

When Redis memory is full, it can affect other applications and even cause system crashes. To avoid this, the following measures should be taken: Set the memory ceiling reasonably and use the appropriate data elimination strategy to regularly clean out expired data using the appropriate Redis data structure to monitor memory usage.

Redis memory full? This is a headache! Simply put, yes, it can affect other applications and even directly cause system crashes. This is not alarmist, we have to make a good fight.

Let’s first talk about why it affects other applications. Redis usually runs on a server and shares system resources with your other applications. The most important thing is memory. If Redis eats the memory completely, other applications can only drink the northwest wind, which can run slowly at the least, and then hang up directly at the worst. Imagine that your database, web server, message queue is crowded in a small room, and suddenly the big guy Redis stuffs the room full. Can others still breathe?

Going deeper, what measures will Redis take after the memory is full? It depends on your configuration. The most common scenario is that Redis refuses new write requests, which will directly cause your application to report errors, such as database connection failure, cache failure, etc. Worse, if configured improperly, Redis may trigger memory swap (swap) due to insufficient memory, which can severely slow down the entire system and even cause system crashes. Think about it, how many orders of magnitude is the reading and writing speed of a hard disk slower than memory? This is simply disastrous.

Therefore, prevention is better than treatment. How to avoid full Redis memory? Several key points:

• Set the memory limit reasonably: Don't just give all the memory to Redis, leaving some room for other applications. Plan memory usage reasonably according to your data volume and business needs. Don't think that the larger the memory, the better, too much is just as insufficient.
• Data Elimination Strategy: Redis provides a variety of data Elimination strategies, such as LRU (most recently used), LFU (most often used), etc. Choosing the right strategy can effectively control memory usage. It's like managing a warehouse, eliminating things that haven't been used for a long time, making room for new goods.
• Regularly clean data: Regularly clean out expired data, or manually delete data that is no longer needed. It's like cleaning the room regularly, throwing away the garbage, keeping the room tidy.
• Use the appropriate Redis data structure: Different data structures occupy different memory, and choosing the right structure can save memory. For example, if you only need to store simple key-value pairs, using Hash is more memory-saving than List.
• Monitor memory usage: Use monitoring tools to monitor Redis's memory usage in real time and discover problems in a timely manner. It's like installing a surveillance camera to keep abreast of the inventory of your warehouse.

Code example? This thing depends on your specific application scenario. However, I can give you a simple Python code snippet to monitor Redis memory usage:

 <code class="python">import redis r = redis.Redis(host='localhost', port=6379) info = r.info() used_memory = info['used_memory'] print(f"Redis used memory: {used_memory} bytes") # 更高级的监控可以结合一些监控工具，比如Prometheus，Grafana等等</code>

Remember, this is just a simple example. In actual application, you need to modify it according to your needs.

Finally, what I want to say is that solving the problem of Redis full memory is not only a technical problem, but also a problem of architecture design and operation and maintenance management. You need to start from the overall architecture and consider all aspects of resource allocation, data management, monitoring and early warning, etc. in order to effectively avoid this problem. Don’t wait until the problem breaks out before being in a hurry. Prevention is the best way!

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