RabbitMQ cluster is not reconnecting after network failure

From RabbitMQ doc: Clustering and Network Partitions

RabbitMQ also three ways to deal with network partitions automatically: pause-minority mode, pause-if-all-down mode and autoheal mode. The default behaviour is referred to as ignore mode.

In pause-minority mode RabbitMQ will automatically pause cluster nodes which determine themselves to be in a minority (i.e. fewer or equal than half the total number of nodes) after seeing other nodes go down. It therefore chooses partition tolerance over availability from the CAP theorem. This ensures that in the event of a network partition, at most the nodes in a single partition will continue to run. The minority nodes will pause as soon as a partition starts, and will start again when the partition ends. This configuration prevents split-brain and is therefore able to automatically recover from network partitions without inconsistencies.

In pause-if-all-down mode, RabbitMQ will automatically pause cluster nodes which cannot reach any of the listed nodes. In other words, all the listed nodes must be down for RabbitMQ to pause a cluster node. This is close to the pause-minority mode, however, it allows an administrator to decide which nodes to prefer, instead of relying on the context. For instance, if the cluster is made of two nodes in rack A and two nodes in rack B, and the link between racks is lost, pause-minority mode will pause all nodes. In pause-if-all-down mode, if the administrator listed the two nodes in rack A, only nodes in rack B will pause. Note that it is possible the listed nodes get split across both sides of a partition: in this situation, no node will pause. That is why there is an additional ignore/autoheal argument to indicate how to recover from the partition.

In autoheal mode RabbitMQ will automatically decide on a winning partition if a partition is deemed to have occurred, and will restart all nodes that are not in the winning partition. Unlike pause_minority mode it therefore takes effect when a partition ends, rather than when one starts.

The winning partition is the one which has the most clients connected (or if this produces a draw, the one with the most nodes; and if that still produces a draw then one of the partitions is chosen in an unspecified way).

You can enable either mode by setting the configuration parameter cluster_partition_handling for the rabbit application in the configuration file to:

• autoheal
• pause_minority
• pause_if_all_down

If using the pause_if_all_down mode, additional parameters are required:

• nodes: nodes which should be unavailable to pause
• recover: recover action, can be ignore or autoheal

...

Which Mode to Pick?

It's important to understand that allowing RabbitMQ to deal with network partitions automatically comes with trade offs.

As stated in the introduction, to connect RabbitMQ clusters over generally unreliable links, prefer Federation or the Shovel.

With that said, here are some guidelines to help the operator determine which mode may or may not be appropriate:

• ignore: use when network reliability is the highest practically possible and node availability is of topmost importance. For example, all cluster nodes can be in the same a rack or equivalent, connected with a switch, and that switch is also the route to the outside world.
• pause_minority: appropriate when clustering across racks or availability zones in a single region, and the probability of losing a majority of nodes (zones) at once is considered to be very low. This mode trades off some availability for the ability to automatically recover if/when the lost node(s) come back.
• autoheal: appropriate when are more concerned with continuity of service than with data consistency across nodes.

RabbitMQ Clusters do not work well on unreliable networks (part of RabbitMQ documentation). So when the network failure happens (in a two node cluster) each node thinks that it is the master and the only node in the cluster. Two master nodes don't automatically reconnect, because their states are not automatically synchronized (even in case of a RabbitMQ slave - the actual message synchronization does not happen - the slave just "catches up" as messages get consumed from the queue and more messages get added).

To detect whether you have a broken cluster, run the command:

rabbitmqctl cluster_status

on each of the nodes that form part of the cluster. If the cluster is broken then you'll only see one node. Something like:

Cluster status of node rabbit@rabbitmq1 ...
[{nodes,[{disc,[rabbit@rabbitmq1]}]},{running_nodes,[rabbit@rabbitmq1]}]
...done.

In such cases, you'll need to run the following set of commands on one of the nodes that formed part of the original cluster (so that it joins the other master node (say rabbitmq1) in the cluster as a slave):

rabbitmqctl stop_app

rabbitmqctl reset

rabbitmqctl join_cluster rabbit@rabbitmq1

rabbitmqctl start_app

Finally check the cluster status again .. this time you should see both the nodes.

Note: If you have the RabbitMQ nodes in an HA configuration using a Virtual IP (and the clients are connecting to RabbitMQ using this virtual IP), then the node that should be made the master should be the one that has the Virtual IP.

One other way to recover from this kind of failure is to work with Mnesia which is the database that RabbitMQ uses as the persistence mechanism and for the synchronization of the RabbitMQ instances (and the master / slave status) are controlled by this. For all the details, refer to the following URL: http://www.erlang.org/doc/apps/mnesia/Mnesia_chap7.html

Adding the relevant section here:

There are several occasions when Mnesia may detect that the network has been partitioned due to a communication failure.

One is when Mnesia already is up and running and the Erlang nodes gain contact again. Then Mnesia will try to contact Mnesia on the other node to see if it also thinks that the network has been partitioned for a while. If Mnesia on both nodes has logged mnesia_down entries from each other, Mnesia generates a system event, called {inconsistent_database, running_partitioned_network, Node} which is sent to Mnesia's event handler and other possible subscribers. The default event handler reports an error to the error logger.

Another occasion when Mnesia may detect that the network has been partitioned due to a communication failure, is at start-up. If Mnesia detects that both the local node and another node received mnesia_down from each other it generates a {inconsistent_database, starting_partitioned_network, Node} system event and acts as described above.

If the application detects that there has been a communication failure which may have caused an inconsistent database, it may use the function mnesia:set_master_nodes(Tab, Nodes) to pinpoint from which nodes each table may be loaded.

At start-up Mnesia's normal table load algorithm will be bypassed and the table will be loaded from one of the master nodes defined for the table, regardless of potential mnesia_down entries in the log. The Nodes may only contain nodes where the table has a replica and if it is empty, the master node recovery mechanism for the particular table will be reset and the normal load mechanism will be used when next restarting.

The function mnesia:set_master_nodes(Nodes) sets master nodes for all tables. For each table it will determine its replica nodes and invoke mnesia:set_master_nodes(Tab, TabNodes) with those replica nodes that are included in the Nodes list (i.e. TabNodes is the intersection of Nodes and the replica nodes of the table). If the intersection is empty the master node recovery mechanism for the particular table will be reset and the normal load mechanism will be used at next restart.

The functions mnesia:system_info(master_node_tables) and mnesia:table_info(Tab, master_nodes) may be used to obtain information about the potential master nodes.

Determining which data to keep after communication failure is outside the scope of Mnesia. One approach would be to determine which "island" contains a majority of the nodes. Using the {majority,true} option for critical tables can be a way of ensuring that nodes that are not part of a "majority island" are not able to update those tables. Note that this constitutes a reduction in service on the minority nodes. This would be a tradeoff in favour of higher consistency guarantees.

The function mnesia:force_load_table(Tab) may be used to force load the table regardless of which table load mechanism is activated.

This is a more lengthy and involved way of recovering from such failures .. but will give better granularity and control over data that should be available in the final master node (this can reduce the amount of data loss that might happen when "merging" RabbitMQ masters).