Resource management
===================

In a typical Kubernetes cluster, pods run with unlimited resources. By
default, they might be allowed to use as much CPU and RAM as needed.

EDB Postgres for Kubernetes allows administrators to control and manage
resource usage by the pods of the cluster, through the ``resources``
section of the manifest, with two knobs:

- ``requests`` : initial requirement

- ``limits`` : maximum usage, in case of dynamic increase of resource
  needs

For example, you can request an initial amount of RAM of 32MiB (scalable
to 128MiB) and 50m of CPU (scalable to 100m) as follows:

.. code:: yaml

     resources:
       requests:
         memory: "32Mi"
         cpu: "50m"
       limits:
         memory: "128Mi"
         cpu: "100m"

Memory requests and limits are associated with containers, but it is
useful to think of a pod as having a memory request and limit. The pod’s
memory request is the sum of the memory requests for all the containers
in the pod.

Pod scheduling is based on requests and not on limits. A pod is
scheduled to run on a Node only if the Node has enough available memory
to satisfy the pod’s memory request.

For each resource, we divide containers into 3 Quality of Service (QoS)
classes, in decreasing order of priority:

- *Guaranteed*

- *Burstable*

- *Best-Effort*

For more details, please refer to the `Configure Quality of Service for Pods <https://kubernetes.io/docs/tasks/configure-pod-container/quality-service-pod/#qos-classes>`_ 

section in the Kubernetes documentation.

For a PostgreSQL workload it is recommended to set a “Guaranteed” QoS.

To avoid resources related issues in Kubernetes, we can refer to the
best practices for “out of resource” handling while creating a cluster:

- Specify your required values for memory and CPU in the resources
  section of the manifest file. This way, you can avoid the
  ``OOM Killed`` (where “OOM” stands for Out Of Memory) and
  ``CPU throttle`` or any other resource-related issues on running
  instances.

- For your cluster’s pods to get assigned to the “Guaranteed” QoS class,
  you must set limits and requests for both memory and CPU to the same
  value.

- Specify your required PostgreSQL memory parameters consistently with
  the pod resources (as you would do in a VM or physical machine
  scenario - see below).

- Set up database server pods on a dedicated node using nodeSelector.
  See the “nodeSelector” and “tolerations” fields of the :ref:`“affinityconfiguration" <API Reference - v1.25.1>` 
  resource on the API reference page.

You can refer to the following example manifest:

.. code:: yaml

   apiVersion: postgresql.k8s.enterprisedb.io/v1
   kind: Cluster
   metadata:
     name: postgresql-resources
   spec:

     instances: 3

     postgresql:
       parameters:
         shared_buffers: "256MB"

     resources:
       requests:
         memory: "1024Mi"
         cpu: 1
       limits:
         memory: "1024Mi"
         cpu: 1

     storage:
       size: 1Gi

In the above example, we have specified ``shared_buffers`` parameter
with a value of ``256MB`` - i.e., how much memory is dedicated to the
PostgreSQL server for caching data (the default value for this parameter
is ``128MB`` in case it’s not defined).

A reasonable starting value for ``shared_buffers`` is 25% of the memory
in your system. For example: if your ``shared_buffers`` is 256 MB, then
the recommended value for your container memory size is 1 GB, which
means that within a pod all the containers will have a total of 1 GB
memory that Kubernetes will always preserve, enabling our containers to
work as expected. For more details, please refer to the `Resource Consumption <https://www.postgresql.org/docs/current/runtime-config-resource.html>`_ 

section in the PostgreSQL documentation.

..  Seealso::
   For more details on resource management, please refer to the `Managing Compute Resources for Containers <https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container/>`_ 

page from the Kubernetes documentation.