This document describes the design concepts of Akka Cluster. For the guide on using Akka Cluster please see either
Akka Cluster provides a fault-tolerant decentralized peer-to-peer based Cluster Membership Service with no single point of failure or single point of bottleneck. It does this using gossip protocols and an automatic failure detector.
Akka Cluster allows for building distributed applications, where one application or service spans multiple nodes (in practice multiple
- A logical member of a cluster. There could be multiple nodes on a physical machine. Defined by a hostname:port:uid tuple.
- A set of nodes joined together through the Cluster Membership Service.
- A single node in the cluster that acts as the leader. Managing cluster convergence and membership state transitions.
The cluster membership used in Akka is based on Amazon’s Dynamo system and particularly the approach taken in Basho’s’ Riak distributed database. Cluster membership is communicated using a Gossip Protocol, where the current state of the cluster is gossiped randomly through the cluster, with preference to members that have not seen the latest version.
Vector clocks are a type of data structure and algorithm for generating a partial ordering of events in a distributed system and detecting causality violations.
We use vector clocks to reconcile and merge differences in cluster state during gossiping. A vector clock is a set of (node, counter) pairs. Each update to the cluster state has an accompanying update to the vector clock.
Information about the cluster converges locally at a node at certain points in time. This is when a node can prove that the cluster state it is observing has been observed by all other nodes in the cluster. Convergence is implemented by passing a set of nodes that have seen current state version during gossip. This information is referred to as the seen set in the gossip overview. When all nodes are included in the seen set there is convergence.
Gossip convergence cannot occur while any nodes are
unreachable. The nodes need to become
reachable again, or moved to the
removed states (see the Cluster Membership Lifecycle section). This only blocks the leader from performing its cluster membership management and does not influence the application running on top of the cluster. For example this means that during a network partition it is not possible to add more nodes to the cluster. The nodes can join, but they will not be moved to the
up state until the partition has healed or the unreachable nodes have been downed.
The failure detector in Akka Cluster is responsible for trying to detect if a node is
unreachable from the rest of the cluster. For this we are using the Phi Accrual Failure Detector implementation. To be able to survive sudden abnormalities, such as garbage collection pauses and transient network failures the failure detector is easily configurable for tuning to your environments and needs.
In a cluster each node is monitored by a few (default maximum 5) other nodes. The nodes to monitor are selected from neighbors in a hashed ordered node ring. This is to increase the likelihood to monitor across racks and data centers, but the order is the same on all nodes, which ensures full coverage.
When any node is detected to be
unreachable this data is spread to the rest of the cluster through the gossip. In other words, only one node needs to mark a node
unreachable to have the rest of the cluster mark that node
The failure detector will also detect if the node becomes
reachable again. When all nodes that monitored the
unreachable node detect it as
reachable again the cluster, after gossip dissemination, will consider it as
If system messages cannot be delivered to a node it will be quarantined and then it cannot come back from
unreachable. This can happen if the there are too many unacknowledged system messages (e.g. watch, Terminated, remote actor deployment, failures of actors supervised by remote parent). Then the node needs to be moved to the
removed states (see Cluster Membership Lifecycle) and the actor system of the quarantined node must be restarted before it can join the cluster again.
See the following for more details:
- Phi Accrual Failure Detector implementation
- Using the Failure Detector
After gossip convergence a
leader for the cluster can be determined. There is no
leader election process, the
leader can always be recognised deterministically by any node whenever there is gossip convergence. The leader is only a role, any node can be the leader and it can change between convergence rounds. The
leader is the first node in sorted order that is able to take the leadership role, where the preferred member states for a
leaving (see the Cluster Membership Lifecycle for more information about member states).
The role of the
leader is to shift members in and out of the cluster, changing
joining members to the
up state or
exiting members to the
removed state. Currently
leader actions are only triggered by receiving a new cluster state with gossip convergence.
The seed nodes are contact points for new nodes joining the cluster. When a new node is started it sends a message to all seed nodes and then sends a join command to the seed node that answers first.
The seed nodes configuration value does not have any influence on the running cluster itself, it is only relevant for new nodes joining the cluster as it helps them to find contact points to send the join command to; a new member can send this command to any current member of the cluster, not only to the seed nodes.
A variation of push-pull gossip is used to reduce the amount of gossip information sent around the cluster. In push-pull gossip a digest is sent representing current versions but not actual values; the recipient of the gossip can then send back any values for which it has newer versions and also request values for which it has outdated versions. Akka uses a single shared state with a vector clock for versioning, so the variant of push-pull gossip used in Akka makes use of this version to only push the actual state as needed.
Periodically, the default is every 1 second, each node chooses another random node to initiate a round of gossip with. If less than ½ of the nodes resides in the seen set (have seen the new state) then the cluster gossips 3 times instead of once every second. This adjusted gossip interval is a way to speed up the convergence process in the early dissemination phase after a state change.
The choice of node to gossip with is random but biased towards nodes that might not have seen the current state version. During each round of gossip exchange, when convergence is not yet reached, a node uses a very high probability (which is configurable) to gossip with another node which is not part of the seen set, i.e. which is likely to have an older version of the state. Otherwise it gossips with any random live node.
This biased selection is a way to speed up the convergence process in the late dissemination phase after a state change.
For clusters larger than 400 nodes (configurable, and suggested by empirical evidence) the 0.8 probability is gradually reduced to avoid overwhelming single stragglers with too many concurrent gossip requests. The gossip receiver also has a mechanism to protect itself from too many simultaneous gossip messages by dropping messages that have been enqueued in the mailbox for too long of a time.
While the cluster is in a converged state the gossiper only sends a small gossip status message containing the gossip version to the chosen node. As soon as there is a change to the cluster (meaning non-convergence) then it goes back to biased gossip again.
The recipient of the gossip state or the gossip status can use the gossip version (vector clock) to determine whether:
- it has a newer version of the gossip state, in which case it sends that back to the gossiper
- it has an outdated version of the state, in which case the recipient requests the current state from the gossiper by sending back its version of the gossip state
- it has conflicting gossip versions, in which case the different versions are merged and sent back
If the recipient and the gossip have the same version then the gossip state is not sent or requested.
The periodic nature of the gossip has a nice batching effect of state changes, e.g. joining several nodes quickly after each other to one node will result in only one state change to be spread to other members in the cluster.
The gossip messages are serialized with protobuf and also gzipped to reduce payload size.