Users that are familiar with PostgreSQL are aware of the existence of the following two files to configure an instance:
postgresql.conf: main run-time configuration file of PostgreSQL
pg_hba.conf: clients authentication file
Due to the concepts of declarative configuration and immutability of the PostgreSQL
containers, users are not allowed to directly touch those files. Configuration
is possible through the
postgresql section of the
Cluster resource definition
by defining custom
pg_hba.conf settings via the
parameters and the
These settings are the same across all instances.
Please don't use the
ALTER SYSTEM query to change the configuration of
the PostgreSQL instances in an imperative way. Changing some of the options
that are normally controlled by the operator might indeed lead to an
unpredictable/unrecoverable state of the cluster.
ALTER SYSTEM changes are not replicated across the cluster.
A reference for custom settings usage is included in the samples, see
The PostgreSQL instance in the pod starts with a default
to which these settings are automatically added:
listen_addresses = '*' include custom.conf
custom.conf file will contain the user-defined settings in the
postgresql section, as in the following example:
# ... postgresql: parameters: shared_buffers: "1GB" # ...
PostgreSQL GUCs: Grand Unified Configuration
Refer to the PostgreSQL documentation for more information on the available parameters, also known as GUC (Grand Unified Configuration).
The content of
custom.conf is automatically generated and maintained by the
operator by applying the following sections in this order:
- Global default parameters
- Default parameters that depend on the PostgreSQL major version
- User-provided parameters
- Fixed parameters
The global default parameters are:
dynamic_shared_memory_type = 'posix' logging_collector = 'on' log_destination = 'csvlog' log_directory = '/controller/log' log_filename = 'postgres' log_rotation_age = '0' log_rotation_size = '0' log_truncate_on_rotation = 'false' max_parallel_workers = '32' max_replication_slots = '32' max_worker_processes = '32' shared_memory_type = 'mmap' # for PostgreSQL >= 12 only wal_keep_size = '512MB' # for PostgreSQL >= 13 only wal_keep_segments = '32' # for PostgreSQL <= 12 only wal_sender_timeout = '5s' wal_receiver_timeout = '5s'
It is your duty to plan for WAL segments retention in your PostgreSQL
cluster and properly configure either
depending on the server version, based on the expected and observed workloads.
Until CloudNativePG supports replication slots, and if you don't have
continuous backup in place, this is the only way at the moment that protects
from the case of a standby falling out of sync and returning error messages like:
"could not receive data from WAL stream: ERROR: requested WAL segment ************************ has already been removed".
This will require you to dedicate a part of your
PGDATA to keep older
WAL segments for streaming replication purposes.
The following parameters are fixed and exclusively controlled by the operator:
archive_command = '/controller/manager wal-archive %p' archive_mode = 'on' full_page_writes = 'on' hot_standby = 'true' listen_addresses = '*' port = '5432' restart_after_crash = 'false' ssl = 'on' ssl_ca_file = '/controller/certificates/client-ca.crt' ssl_cert_file = '/controller/certificates/server.crt' ssl_key_file = '/controller/certificates/server.key' unix_socket_directories = '/controller/run' wal_level = 'logical' wal_log_hints = 'on'
Since the fixed parameters are added at the end, they can't be overridden by the user via the YAML configuration. Those parameters are required for correct WAL archiving and replication.
parameters are managed automatically by the operator according to the state of
the instance in the cluster.
primary_conninfo = 'host=cluster-example-rw user=postgres dbname=postgres' recovery_target_timeline = 'latest'
Log control settings
The operator requires PostgreSQL to output its log in CSV format, and the instance manager automatically parses it and outputs it in JSON format. For this reason, all log settings in PostgreSQL are fixed and cannot be changed.
For further information, please refer to the "Logging" section.
Shared Preload Libraries
shared_preload_libraries option in PostgreSQL exists to specify one or
more shared libraries to be pre-loaded at server start, in the form of a
comma-separated list. Typically, it is used in PostgreSQL to load those
extensions that need to be available to most database sessions in the whole system
In CloudNativePG the
shared_preload_libraries option is empty by
default. Although you can override the content of
we recommend that only expert Postgres users take advantage of this option.
In case a specified library is not found, the server fails to start,
preventing CloudNativePG from any self-healing attempt and requiring
manual intervention. Please make sure you always test both the extensions and
the settings of
shared_preload_libraries if you plan to directly manage its
CloudNativePG is able to automatically manage the content of the
shared_preload_libraries option for some of the most used PostgreSQL
extensions (see the "Managed extensions" section below
Specifically, as soon as the operator notices that a configuration parameter requires one of the managed libraries, it will automatically add the needed library. The operator will also remove the library as soon as no actual parameter requires it.
Please always keep in mind that removing libraries from
shared_preload_libraries requires a restart of all instances in the cluster
in order to be effective.
You can provide additional
.spec.postgresql.shared_preload_libraries as a list of strings: the operator
will merge them with the ones that it automatically manages.
As anticipated in the previous section, CloudNativePG automatically
manages the content in
shared_preload_libraries for some well-known and
supported extensions. The current list includes:
Some of these libraries also require additional objects in a database before
using them, normally views and/or functions managed via the
command to be run in a database (the
DROP EXTENSION command typically removes
For such libraries, CloudNativePG automatically handles the creation and removal of the extension in all databases that accept a connection in the cluster, identified by the following query:
SELECT datname FROM pg_database WHERE datallowconn
The above query also includes template databases like
extension provides a means for logging execution plans of slow statements
automatically, without having to manually run
EXPLAIN (helpful for tracking
down un-optimized queries).
You can enable
auto_explain by adding to the configuration a parameter
that starts with
auto_explain. as in the following example excerpt (which
automatically logs execution plans of queries that take longer than 10 seconds
# ... postgresql: parameters: auto_explain.log_min_duration: "10s" # ...
Enabling auto_explain can lead to performance issues. Please refer to
the auto explain documentation
extension is one of the most important capabilities available in PostgreSQL for
real-time monitoring of queries.
You can enable
pg_stat_statements by adding to the configuration a parameter
that starts with
pg_stat_statements. as in the following example excerpt:
# ... postgresql: parameters: pg_stat_statements.max: "10000" pg_stat_statements.track: all # ...
As explained previously, the operator will automatically add
shared_preload_libraries and run
CREATE EXTENSION IF
NOT EXISTS pg_stat_statements on each database, enabling you to run queries
pgaudit extension provides detailed session and/or object audit logging via the standard PostgreSQL logging facility.
You can enable
pgaudit by adding to the configuration a parameter
that starts with
pgaudit. as in the following example excerpt:
# postgresql: parameters: pgaudit.log: "all, -misc" pgaudit.log_catalog: "off" pgaudit.log_parameter: "on" pgaudit.log_relation: "on" #
pg_hba is a list of PostgreSQL Host Based Authentication rules
used to create the
pg_hba.conf used by the pods.
Since the first matching rule is used for authentication, the
generated by the operator can be seen as composed of four sections:
- Fixed rules
- User-defined rules
- Optional LDAP section
- Default rules
local all all peer hostssl postgres streaming_replica all cert hostssl replication streaming_replica all cert
host all all all <default-authentication-method>
From PostgreSQL 14 the default value of the
database parameter is set to
scram-sha-256. Because of that,
the default authentication method is
scram-sha-256 from this
PostgreSQL 13 and older will use
md5 as the default authentication
pg_hba.conf will look like this:
local all all peer hostssl postgres streaming_replica all cert hostssl replication streaming_replica all cert <user defined rules> <user defined LDAP> host all all all scram-sha-256 # (or md5 for PostgreSQL version <= 13)
Refer to the PostgreSQL documentation for more information on
Inside the cluster manifest,
pg_hba lines are added as list items
spec.postgresql.pg_hba, as in the following excerpt:
postgresql: pg_hba: - hostssl app app 10.244.0.0/16 md5
In the above example we are enabling access for the
app user to the
database using MD5 password authentication (you can use
if you prefer) via a secure channel (
postgres section of the cluster spec there is an optional
ldap section available to define an LDAP
configuration to be converted into a rule added into the
This will support two modes:
simple bind mode which requires specifying a
suffix in the LDAP
section and the
search+bind mode which requires specifying
binDN, and a
bindPassword which is
a secret containing the ldap password. Additionally, in
search+bind mode you have the option to specify a
searchAttribute. If no
searchAttribute is specified the default one of
uid will be used.
Additionally, both modes allow the specification of a
scheme for ldapscheme and a
port. Neither scheme nor port are
This section filled out for search+bind could look as follows:
postgresql: parameters: ldap: server: 'openldap.default.svc.cluster.local' bindSearchAuth: baseDN: 'ou=org,dc=example,dc=com' bindDN: 'cn=admin,dc=example,dc=com' bindPassword: name: 'ldapBindPassword' key: 'data' searchAttribute: 'uid'
You can apply configuration changes by editing the
postgresql section of
After the change, the cluster instances will immediately reload the configuration to apply the changes. If the change involves a parameter requiring a restart, the operator will perform a rolling upgrade.
Dynamic Shared Memory settings
PostgreSQL supports a few implementations for dynamic shared memory
management through the
configuration option. In CloudNativePG we recommend to limit ourselves to
any of the following two values:
posix: which relies on POSIX shared memory allocated using
sysv: which is based on System V shared memory allocated via
In PostgreSQL, this setting is particularly important for memory allocation in parallel queries.
For details, please refer to this
thread from the
pgsql-general mailing list.
POSIX shared memory
The default setting of
posix should be enough in most cases, considering that
the operator automatically mounts a memory-bound
EmptyDir volume called
/dev/shm. You can verify the size of such volume inside the running
Postgres container with:
mount | grep shm
You should get something similar to the following output:
shm on /dev/shm type tmpfs (rw,nosuid,nodev,noexec,relatime,size=******)
System V shared memory
In case your Kubernetes cluster has a high enough value for the
SHMALL parameters, you can also set:
You can check the
SHMALL from inside a PostgreSQL container, by running:
------ Shared Memory Limits -------- max number of segments = 4096 max seg size (kbytes) = 18014398509465599 max total shared memory (kbytes) = 18014398509481980 min seg size (bytes) = 1
As you can see, the very high number of
max total shared memory recommends
An alternate method is to run:
cat /proc/sys/kernel/shmall cat /proc/sys/kernel/shmmax
Some PostgreSQL configuration parameters should be managed exclusively by the operator. The operator prevents the user from setting them using a webhook.
Users are not allowed to set the following configuration parameters in the