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Orchestrator/raft, consensus cluster

orchestrator HA via raft

orchestrator/raft is a deployment setup where several orchestrator nodes communicate with each other via raft consensus protocol.

orchestrator/raft deployments solve both high-availability for orchestrator itself as well as solve issues with network isolation, and in particular cross-data-center network partitioning/fencing.

Very brief overview of traits of raft

By using a consensus protocol the orchestrator nodes are able to pick a leader that has quorum, implying it is not isolated. For example, consider a 3 node orchestrator/raft setup. Normally the three nodes will chat with each other and one will be a stable elected leader. However in face of network partitioning, say node n1 is partitioned away from nodes n2 and n3, it is guaranteed that the leader will be either n2 or n3. n1 would not be able to lead because it does not have a quorum (in a 3 node setup the quorum size is 2; in a 5 node setup the quorum size is 3)

This turns useful in cross data-center (DC) setups. Assume you set three orchestrator nodes, each on its own DC. If one DC gets isolated, it is guaranteed the active orchestrator node will be one that has consensus, i.e. operates from outside the isolated DC.

orchestrator/raft setup technical details

See also: orchestrator/raft vs. synchronous replication setup

Service nodes

You will set up 3 or 5 (recommended raft node count) orchestrator nodes. Other numbers are also legitimate but you will want at least 3.

At this time orchestrator nodes to not join dynamically into the cluster. The list of nodes is preconfigured as in:

  "RaftEnabled": true,
  "RaftDataDir": "/var/lib/orchestrator",
  "RaftBind": "<ip.or.fqdn.of.this.orchestrator.node>",
  "DefaultRaftPort": 10008,
  "RaftNodes": [

Backend DB

Each orchestrator node has its own, dedicated backend database server. This would be either:

  • A MySQL backend DB (no replication setup required, but OK if this server has replicas)

    As deployment suggestion, this MySQL server can run on the same orchestrator node host.

  • A SQLite backend DB. Use:

  "BackendDB": "sqlite",
  "SQLite3DataFile": "/var/lib/orchestrator/orchestrator.db",

orchestrator is bundled with sqlite, there is no need to install an external dependency.

Proxy: leader

Only the leader is allowed to make changes.

Simplest setup it to only route traffic to the leader, by setting up a HTTP proxy (e.g HAProxy) on top of the orchestrator services.

See orchestrator-client section for an alternate approach

  • Use /api/leader-check as health check. At any given time at most one orchestrator node will reply with HTTP 200/OK to this check; the others will respond with HTTP 404/Not found.
    • Hint: you may use, for example, /api/leader-check/503 is you explicitly wish to get a 503 response code, or similarly any other code.
  • Only direct traffic to the node that passes this test

As example, this would be a HAProxy setup:

listen orchestrator
  bind process 1
  bind process 2
  bind process 3
  bind process 4
  mode tcp
  option httpchk GET /api/leader-check
  maxconn 20000
  balance first
  retries 1
  timeout connect 1000
  timeout check 300
  timeout server 30s
  timeout client 30s

  default-server port 3000 fall 1 inter 1000 rise 1 downinter 1000 on-marked-down shutdown-sessions weight 10

  server orchestrator-node-0 check
  server orchestrator-node-1 check
  server orchestrator-node-2 check

Proxy: healthy raft nodes

A relaxation of the above constraint.

Healthy raft nodes will reverse proxy your requests to the leader. You may choose (and this happens to be desirable for kubernetes setups) to talk to any healthy raft member.

You must not access unhealthy raft members, i.e. nodes that are isolated from the quorum.

  • Use /api/raft-health to identify that a node is part of a healthy raft group.
  • A HTTP 200/OK response identifies the node as part of the healthy group, and you may direct traffic to the node.
  • A HTTP 500/Internal Server Error indicates the node is not part of a healthy group. Note that immediately following startup, and until a leader is elected, you may expect some time where all nodes report as unhealthy. Note that upon leader re-election you may observe a brief period where all nodes report as unhealthy.


An alternative to the proxy approach is to use orchestrator-client.

orchestrator-client is a wrapper script that accesses the orchestrator service via HTTP API, and provides a command line interface to the user.

It is possible to provide orchestrator-client with the full listing of all orchestrator API endpoints. In such case, orchestrator-client will figure out which of the endpoints is the leader, and direct requests at that endpoint.

As example, we can set:

export ORCHESTRATOR_API="https://orchestrator.host1:3000/api https://orchestrator.host2:3000/api https://orchestrator.host3:3000/api"

A call to orchestrator-client will first check

Otherwise, if you already have a proxy, it's also possible for orchestrator-client to work with the proxy, e.g.:

export ORCHESTRATOR_API="https://orchestrator.proxy:80/api"

Behavior and implications of orchestrator/raft setup

  • In the raft setup, each orchestrator node independently runs discoveries of all servers. This means that in a three node setup, each of your MySQL topology servers will be independently visited by three different orchestrator nodes.

  • In normal times, the three nodes will see a more-or-less identical picture of the topologies. But they will each have their own independent analysis.

  • Each orchestrator nodes writes to its own dedicated backend DB server (whether MySQL or sqlite)

  • The orchestrator nodes communication is minimal. They do not share discovery info (since they each discover independently). Instead, the leader shares with the other nodes what user instructions is intercepted, such as:

    • begin-downtime

    • register-candidate


    The leader will also educate its followers about ongoing failovers.

    The communication between orchestrator node does not correlate to transactional database commits, and is sparse.

  • All user changes must go through the leader, and in particular via the HTTP API. You must not manipulate the backend database directly, since such a change will not be published to the other nodes.

  • As result, on a orchestrator/raft, one may not use the orchestrator executable in command line mode: an attempt to run orchestrator cli will refuse to run when raft mode is enabled. Work is ongoing to allow some commands to run via cli.

  • A utility script, orchestrator-client is available that provides similar interface as the command line orchestrator, and that uses & manipulates HTTP API calls.

  • You will only install the orchestrator binaries on orchestrator service nodes, and no where else. The orchestrator-client script can be installed wherever you wish to.

  • A failure of a single orchestrator node will not affect orchestrator's availability. On a 3 node setup at most one server may fail. On a 5 node setup 2 nodes may fail.

  • An orchestrator node cannot run without its backend DB. With sqlite backend this is trivial since sqlite runs embedded with orchestrator. With MySQL backend, the orchestrator service will bail out if unable to connect to the backend DB over a period of time.

  • An orchestrator node may be down, then come back. It will rejoin the raft group, and receive whatever events it missed while out. It does not matter how long the node has been away. If it does not have relevant local raft log/snapshots, another node will automatically feed it with a recent snapshot.

  • The orchestrator service will bail out if it can't join the raft group.

See also Master discovery with Key Value stores via orchestrator/raft.

Main advantages of orchestrator/raft

  • Highly available
  • Consensus: failovers are made by leader node that is member of quorum (not isolated)
  • Supports SQLite (embedded) backend, no need for MySQL backend though supported.
  • Little cross-node communication ; fit for high latency cross DC networks

DC fencing example

Consider this example of three data centers, DC1, DC2 and DC3. We run orchestrator/raft with three nodes, one in each data center.

orchestrator/raft, 3 DCs

What happens when DC2 gets network isolated?

orchestrator/raft, 3 DCs, DC2 view

orchestrator/raft, 3 DCs, quorum view

orchestrator/raft, 3 DCs, recovery


Still ongoing and TODO:

  • Failure detection to require quorum agreement (i.e. a DeadMaster needs to be analyzed by multiple orchestrator nodes) in order to kick failover/recovery.

  • Support sharing of probing (mutually exclusive to the above): the leader will divide the list of servers to probe between all nodes. Potentially by data-center. This will reduce probing load (each MySQL server will be probed by a single node rather than all nodes). All orchestrator nodes will see same picture as opposed to independent views.

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