Patroni originated as a fork of Governor , the project from Compose. It includes plenty of new features.

For an example of a Docker-based deployment with Patroni, see Spilo , currently in use at Zalando.

For additional background info, see:

Development Status

Patroni is in active development and accepts contributions. See our Contributing section below for more details.

We report new releases information here .

Technical Requirements/Installation

Pre-requirements for Mac OS

To install requirements on a Mac, run the following:

brew install postgresql etcd haproxy libyaml python


Starting from psycopg2-2.8 the binary version of psycopg2 will no longer be installed by default. Installing it from the source code requires C compiler and postgres+python dev packages. Since in the python world it is not possible to specify dependency as psycopg2 OR psycopg2-binary you will have to decide how to install it.

There are a few options available:

  1. Use the package manager from your distro

sudo apt-get install python-psycopg2   # install python2 psycopg2 module on Debian/Ubuntu
sudo apt-get install python3-psycopg2  # install python3 psycopg2 module on Debian/Ubuntu
sudo yum install python-psycopg2       # install python2 psycopg2 on RedHat/Fedora/CentOS
  1. Install psycopg2 from the binary package

pip install psycopg2-binary
  1. Install psycopg2 from source

pip install psycopg2>=2.5.4
  1. Use psycopg 3.0 instead of psycopg2

pip install psycopg[binary]>=3.0.0

General installation for pip

Patroni can be installed with pip:

pip install patroni[dependencies]

where dependencies can be either empty, or consist of one or more of the following:

etcd or etcd3

python-etcd module in order to use Etcd as Distributed Configuration Store (DCS)


python-consul module in order to use Consul as DCS


kazoo module in order to use Zookeeper as DCS


kazoo module in order to use Exhibitor as DCS (same dependencies as for Zookeeper)


kubernetes module in order to use Kubernetes as DCS in Patroni


pysyncobj module in order to use python Raft implementation as DCS


boto in order to use AWS callbacks

For example, the command in order to install Patroni together with dependencies for Etcd as a DCS and AWS callbacks is:

pip install patroni[etcd,aws]

Note that external tools to call in the replica creation or custom bootstrap scripts (i.e. WAL-E) should be installed independently of Patroni.

Planning the Number of PostgreSQL Nodes

Patroni/PostgreSQL nodes are decoupled from DCS nodes (except when Patroni implements RAFT on its own) and therefore there is no requirement on the minimal number of nodes. Running a cluster consisting of one primary and one standby is perfectly fine. You can add more standby nodes later.

Running and Configuring

The following section assumes Patroni repository as being cloned from . Namely, you will need example configuration files postgres0.yml and postgres1.yml . If you installed Patroni with pip, you can obtain those files from the git repository and replace ./ below with patroni command.

To get started, do the following from different terminals:

> etcd --data-dir=data/etcd --enable-v2=true
> ./ postgres0.yml
> ./ postgres1.yml

You will then see a high-availability cluster start up. Test different settings in the YAML files to see how the cluster’s behavior changes. Kill some of the components to see how the system behaves.

Add more postgres*.yml files to create an even larger cluster.

Patroni provides an HAProxy configuration, which will give your application a single endpoint for connecting to the cluster’s leader. To configure, run:

> haproxy -f haproxy.cfg
> psql --host --port 5000 postgres

YAML Configuration

Go here for comprehensive information about settings for etcd, consul, and ZooKeeper. And for an example, see postgres0.yml .

Environment Configuration

Go here for comprehensive information about configuring(overriding) settings via environment variables.

Replication Choices

Patroni uses Postgres’ streaming replication, which is asynchronous by default. Patroni’s asynchronous replication configuration allows for maximum_lag_on_failover settings. This setting ensures failover will not occur if a follower is more than a certain number of bytes behind the leader. This setting should be increased or decreased based on business requirements. It’s also possible to use synchronous replication for better durability guarantees. See replication modes documentation for details.

Applications Should Not Use Superusers

When connecting from an application, always use a non-superuser. Patroni requires access to the database to function properly. By using a superuser from an application, you can potentially use the entire connection pool, including the connections reserved for superusers, with the superuser_reserved_connections setting. If Patroni cannot access the Primary because the connection pool is full, behavior will be undesirable.

Testing Your HA Solution

Testing an HA solution is a time consuming process, with many variables. This is particularly true considering a cross-platform application. You need a trained system administrator or a consultant to do this work. It is not something we can cover in depth in the documentation.

That said, here are some pieces of your infrastructure you should be sure to test:

  • Network (the network in front of your system as well as the NICs [physical or virtual] themselves)

  • Disk IO

  • file limits (nofile in Linux)

  • RAM. Even if you have oomkiller turned off as suggested, the unavailability of RAM could cause issues.

  • CPU

  • Virtualization Contention (overcommitting the hypervisor)

  • Any cgroup limitation (likely to be related to the above)

  • kill -9 of any postgres process (except postmaster!). This is a decent simulation of a segfault.

One thing that you should not do is run kill -9 on a postmaster process. This is because doing so does not mimic any real life scenario. If you are concerned your infrastructure is insecure and an attacker could run kill -9 , no amount of HA process is going to fix that. The attacker will simply kill the process again, or cause chaos in another way.