The performance in RabbitMQ is dependent on multiple variables. Go through the following tips to enhance the performance of your RabbitMQ application.
Use Shorter Queues
Ensure that all your queues are as short as possible to achieve maximum performance. When queues are long, then consequently their processing overhead is higher to the shorter ones. Therefore, experts recommend that all queues should be kept close to 0 to achieve best possible performance.
Setting up Max-length
If your application is hit up by a huge load of messages, then you can think about setting up a “max-length” for your queue. If you employ this technique, then your queue can be shortened through the discarding of messages which exist at the queue’s head. In this way, the queue can never exceed the setting of max-length.
Implement Lazy Queues
By default, lazy queues are enabled in the CloudAMQP. If you are unfamiliar with lazy queues, then these are those queues which are stored automatically on the disk. When a need for any message arises, then messages are transferred to the memory. When you work with lazy queues, the incoming messages are directed to the disk. In this way, the RAM usage becomes efficient. On the other hand, the time for throughput also balloons up.
Utilize Transient Messages
If you desire the fastest possible throughput, use transient messages. Keep in mind that persistent messages are directed to the disk as soon as the queue receives them.
Think About Multiple Queues
In RabbitMQ, queues are single-threaded. Up to 50k messages can be handled by a single queue. If you have a multi-core system, then you will gain improved throughput when you have multiple consumers and queues. To gain maximum throughput, the number of cores and queues on the underlying nodes should be equal.
In RabbitMQ, the management interfaces stores all the queue information which in turn has a negative impact on the server and slows it down. The RAM and CPU usage can also be negatively affected when the number of queues reaches a high limit (we are talking about a 1,000+ range). The management interface gathers information about each queue and then processes them. Each of this queue is reliant on the consumption of a select few resources. When the number of queues is in thousands then sharing of disk and CPU resources can create issues.
Spread Each Queue over Separate Cores
The performance of queues is restricted by a single core. Hence, in order to gain improved performance, a better strategy would be to spread up your queues over separate cores. On a similar note, if you are working with a cluster in RabbitMQ, then use separates node for your queues to achieve optimal performance. Note that when the queues are declared in RabbitMQ, they are attached to their respective node.
In the scenario where you configure and generate a cluster for your brokers in RabbitMQ, messages which are directed over a designated queue are routed to the node where the queue is located. It is possible to spread queues among the nodes, however, it has a catch. The drawback is that you would have to note down the location of your queue for future use. On average, it is recommended to use 2 plugins. Using 2 plugins is helpful when you have a more than a single node or when you have a cluster with a single node and multiple cores
Leveraging the Consistent Hash Exchange Plugin
If you are struggling with load-balancing your messages with queues, then a specific plugin can help you in this regard, known as the consistent hash exchange plugin. This plugin allows the use of exchange for facilitating load-balancing messages with queues. The exchange receives messages which are equally and regularly spread among multiple queues. In this process, the message’s routing key is utilized.
What the plugin does is that generates the routing key’s hash and distributes the messages to those queues which possess that exchange’s binding. As you can predict, doing such through manual means can create certain pitfalls as you will have to provide a great deal of information about the queue numbers along with their respective bindings for the publisher.
If you must gain the max usage of your cluster’s cores, then the introduction of the consistent hash exchange plugin can serve you well. Bear in mind that consumption is necessary from all of the queues. To read, about the plugin in detail, you can use this link.
Use Plugin for Sharding
Sharding is a process in which large databases are partitioned into smaller divisions to increase the speed and efficiency of the application. In RabbitMQ, you can use a sharding plugin to automate this partitioning. All you have to do is specify an exchange as sharded. Afterward, all the required queues are generated by the plugin for all the cluster nodes while sharding will be applied on the messages to distribute among the nodes.
With this plugin, one queue will be presented with a single consumer, but it is possible that multiple background queues run behind that queue. The plugin allows users to have access to their own centralized spot which can be used for sending messages, attaching queues with nodes of the cluster, and load-balancing the messages over multiple nodes.
Turn Off Manual Acks
The performance of the application can be influenced by the acknowledgment and publish confirms. Therefore, in order to target the best possible throughput, disable the manual acks.
Stay Away from Multiple Nodes
A single node can provide you the best possible throughput if you compare it with a high availability cluster setup. Mirroring is not applied on queues and messages for other nodes.
Turn Off Non-Used Plugins
While using RabbitMQ, different situations require the use of various plugins. While you find some of them as extremely valuable for your use, you have to keep in mind that their processing overhead can affect your performance. Hence, for production, they are not always recommended.