When should I not use Beetle?
If it’s not fast enough for your use case. For example, we use RabbitMQ directly for our application logging. Other examples: streaming videos through your messaging system, using RabbitMQ as a reverse http proxy.
What does High Availability mean?
It mostly means 24/7 message publishing. This is important for us, as we send most messages from our web applications to a large array of background processors. For the receiver side it means that some message consumers might pause for a short period of time if the message deduplication store becomes temporarily unavailable.
Does it scale?
Short answer: yes. Longer answer: Beetle makes it very easy to add more message brokers to an existing messaging system. All the necessary exchanges, queues and bindings are created automatically on each new server. Since the publishing logic randomly selects 2 out of N servers for redundant publishing (one for failover publishing), the load should be distributed relatively evenly among all brokers. If the message deduplication store becomes a bottleneck, you can partition the queues and assign a separate deduplication store to each partition.
Why aren’t all messages sent redundantly?
Because not all messages are equally important. Using redundancy only for those messages which need it increases system throughput, for two reasons:
- redundant messages have to be sent to two servers, whereas non redundant messages are sent to only one
- processing non redundant messages does does not require accessing the deduplication store, unless you specify the corresponding message handler to be retriable (see messsage handler logic)
What are the hardware requirements?
That, of course, depends. We’re currently running our messaging system on five moderately fast Linux boxes: three RabbitMQ servers and two Redis servers in a master slave setup. This is the minimum number of machines if you want to be able to guarantee that messages can always be published redundantly, even if one of the message brokers dies. In this setup, the Redis master server is most likely to become a bottleneck, especially if you use the “appendfsync always” strategy for the Redis appendonly log. For best performance, we recommend to use a separate partition on a really fast disk for the append log file.
What is the worst failure scenario?
It depends on the type of message and how the message handlers have been configured. For non redundant messages the worst failure is an irrecoverable message broker crash. All non redundant messages stored on the broken server will be lost. Redundantly queued messages are unaffected by message broker crashes. For those messages, the worst thing that can happen is an irrecoverable Redis server crash. A Redis server crash means that some information on the state of message processing can get lost, which could lead to a small number of messages being processed twice or not at all. Please refer to the description of the messsage handler logic.
Isn’t the Redis server a single point of failure?
This depends on how you configure the system. Obviously, if only one redis server is configured (not recommended), it will be a single point of failure. However, the impact of an irrecoverable failure on a Redis server machine would still be much smaller than the impact of a irrecoverable broker failure in a single message broker system.
For master/slave configurations, we have developed a system of communicating monitoring processes, distributed across all machines which need to run message handler logic (workers). This system will automatically promote a redis slave to master role in case the master machine dies or becomes unavailable to all worker machines. Please refer to the redis auto failover document for details.
How should I configure Redis?
For the most reliable system, your Redis server should be configured to use the appendlog with the fsync always strategy.
appendonly yes appendfsync always