Quickstart
==========

.. raw:: html

   <!-- SPDX-License-Identifier: CC-BY-4.0 -->

This section guides you through testing a PostgreSQL cluster on your
local machine by deploying CloudNativePG on a local Kubernetes cluster
using either `Kind <https://kind.sigs.k8s.io/>`_  or `Minikube <https://kubernetes.io/docs/setup/learning-environment/minikube/>`_  .

..  Warning::
   The instructions contained in this section are for demonstration, testing, and practice purposes only and must not be used in production. 　

Like any other Kubernetes application, CloudNativePG is deployed using
regular manifests written in YAML.

By following the instructions on this page you should be able to start a
PostgreSQL cluster on your local Kubernetes installation and experiment
with it.

..  Note::
   Make sure that you have `kubectl`  installed on your machine in order to connect to the Kubernetes cluster. Please follow the Kubernetes documentation on  `how to install `kubectl` <https://kubernetes.io/docs/tasks/tools/install-kubectl/>`_  . 　

Part 1: Setup the local Kubernetes playground
---------------------------------------------

The first part is about installing Minikube or Kind. Please spend some
time reading about the systems and decide which one to proceed with.
After setting up one of them, please proceed with part 2.

We also provide instructions for setting up monitoring with Prometheus
and Grafana for local testing/evaluation, in :ref:`Part 4: Monitor clusters with Prometheus and Grafana <Part 4: Monitor clusters with Prometheus and Grafana>` 

Minikube
^^^^^^^^

Minikube is a tool that makes it easy to run Kubernetes locally.
Minikube runs a single-node Kubernetes cluster inside a Virtual Machine
(VM) on your laptop for users looking to try out Kubernetes or develop
with it day-to-day. Normally, it is used in conjunction with VirtualBox.

You can find more information in the official `Kubernetes documentation on how toinstall Minikube <https://kubernetes.io/docs/tasks/tools/install-minikube>`_  in your
local personal environment. When you installed it, run the following
command to create a minikube cluster:

.. code:: sh

   minikube start

This will create the Kubernetes cluster, and you will be ready to use
it. Verify that it works with the following command:

.. code:: sh

   kubectl get nodes

You will see one node called ``minikube`` .

Kind
^^^^

If you do not want to use a virtual machine hypervisor, then Kind is a
tool for running local Kubernetes clusters using Docker container
“nodes” (Kind stands for “Kubernetes IN Docker” indeed).

Install ``kind`` on your environment following the instructions in the
`Quickstart <https://kind.sigs.k8s.io/docs/user/quick-start>`_  , then create a Kubernetes cluster with:

.. code:: sh

   kind create cluster --name pg

Part 2: Install CloudNativePG
-----------------------------

Now that you have a Kubernetes installation up and running on your
laptop, you can proceed with CloudNativePG installation.

Please refer to the :ref:`Installation and upgrades <Installation and upgrades>`  section and then proceed with the
deployment of a PostgreSQL cluster.

Part 3: Deploy a PostgreSQL cluster
-----------------------------------

As with any other deployment in Kubernetes, to deploy a PostgreSQL
cluster you need to apply a configuration file that defines your desired
``Cluster`` .

The 
`cluster-example.yaml <https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/samples/cluster-example.yaml>`_  sample file defines a simple ``Cluster`` using the
default storage class to allocate disk space:

.. code:: yaml

   apiVersion: postgresql.cnpg.io/v1
   kind: Cluster
   metadata:
     name: cluster-example
   spec:
     instances: 3

     storage:
       size: 1Gi

..  Note::
   For more detailed information about the available options, please refer to the  :ref:`API Reference <API Reference>`  . 　

In order to create the 3-node PostgreSQL cluster, you need to run the
following command:

.. code:: sh

   kubectl apply -f cluster-example.yaml

You can check that the pods are being created with the ``get pods``
command:

.. code:: sh

   kubectl get pods

That will look for pods in the default namespace. To separate your
cluster from other workloads on your Kubernetes installation, you could
always create a new namespace to deploy clusters on. Alternatively, you
can use labels. The operator will apply the ``cnpg.io/cluster`` label on
all objects relevant to a particular cluster. For example:

.. code:: sh

   kubectl get pods -l cnpg.io/cluster=<CLUSTER>

..  Note::
   Note that we are using `cnpg.io/cluster`  as the label. In the past you may have seen or used `postgresql` . This label is being deprecated, and will be dropped in the future. Please use `cnpg.io/cluster` . 　

By default, the operator will install the latest available minor version
of the latest major version of PostgreSQL when the operator was
released. You can override this by setting the ``imageName`` key in the
``spec`` section of the ``Cluster`` definition. For example, to install
PostgreSQL 13.6:

.. code:: yaml

   apiVersion: postgresql.cnpg.io/v1
   kind: Cluster
   metadata:
      # [...]
   spec:
      # [...]
      imageName: ghcr.io/cloudnative-pg/postgresql:13.6
      #[...]

..  Note::
   The immutable infrastructure paradigm requires that you always point to a specific version of the container image. Never use tags like `latest`  or `13`  in a production environment as it might lead to unpredictable scenarios in terms of update policies and version consistency in the cluster. For strict deterministic and repeatable deployments, you can add the digests to the image name, through the `<image>:<tag>@sha256:<digestValue>`  format. 　

..  Note::
   There are some examples cluster configurations bundled with the operator. Please refer to the  :ref:`Examples <Examples>`  . 　

Part 4: Monitor clusters with Prometheus and Grafana
----------------------------------------------------

..  Note::
   Installing Prometheus and Grafana is beyond the scope of this project. The instructions in this section are provided for experimentation and illustration only. 　

In this section we show how to deploy Prometheus and Grafana for
observability, and how to create a Grafana Dashboard to monitor
CloudNativePG clusters, and a set of Prometheus Rules defining alert
conditions.

We leverage the `Kube-Prometheus stack <https://github.com/prometheus-community/helm-charts/tree/main/charts/kube-prometheus-stack>`_ 

Helm chart, which is maintained by the `Prometheus Community <https://github.com/prometheus-community>`_  . Please refer to
the project website for additional documentation and background.

The Kube-Prometheus-stack Helm chart installs the `Prometheus Operator <https://prometheus-operator.dev>`_  ,
including the `Alert Manager <https://prometheus.io/docs/alerting/latest/alertmanager/>`_  , and a `Grafana <https://grafana.com>`_  deployment.

We include a configuration file for the deployment of this Helm chart
that will provide useful initial settings for observability of
CloudNativePG clusters.

Installation
^^^^^^^^^^^^

If you don’t have `Helm <https://helm.sh>`_  installed yet, please follow the
`instructions <https://helm.sh/docs/intro/quickstart/>`_  to install it in your system.

We need to add the ``prometheus-community`` helm chart repository, and
then install the *Kube Prometheus stack* with our sample configuration
 
`kube-stack-config.yaml <./https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/samples/monitoring/kube-stack-config.yaml>`_  .

We can accomplish this with the following commands:

.. code:: sh

   helm repo add prometheus-community \
     https://prometheus-community.github.io/helm-charts

   helm upgrade --install \
     -f https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/samples/monitoring/kube-stack-config.yaml \
     prometheus-community \
     prometheus-community/kube-prometheus-stack

After completion, you will have Prometheus, Grafana, and Alert Manager,
configured with the ``kube-stack-config.yaml`` file:

- From the Prometheus installation, you will have the Prometheus
  Operator watching for **any** ``PodMonitor`` (see :ref:`*monitoring* <Monitoring>`  ).

- Alert Manager and Grafana are both enabled.

..  Note::
   For further information about the above helm commands, refer to the  `helm    install <https://helm.sh/docs/helm/helm_install/>`_ 

documentation. 　

You can see several Custom Resources have been created:

.. code:: sh

   % kubectl get crds
   NAME                                        CREATED AT
   …
   alertmanagers.monitoring.coreos.com         <timestamp>
   …
   prometheuses.monitoring.coreos.com          <timestamp>
   prometheusrules.monitoring.coreos.com       <timestamp>
   …

as well as a series of Services:

.. code:: sh

   % kubectl get svc     
   NAME                                      TYPE        PORT(S)
   …                                         …           …
   prometheus-community-grafana              ClusterIP   80/TCP
   prometheus-community-kube-alertmanager    ClusterIP   9093/TCP
   prometheus-community-kube-operator        ClusterIP   443/TCP
   prometheus-community-kube-prometheus      ClusterIP   9090/TCP

Viewing with Prometheus
^^^^^^^^^^^^^^^^^^^^^^^

At this point, a CloudNativePG cluster deployed with monitoring
activated would be observable via Prometheus.

For example, you could deploy a simple cluster with ``PodMonitor``
enabled:

.. code:: sh

   kubectl apply -f - <<EOF
   - --
   apiVersion: postgresql.cnpg.io/v1
   kind: Cluster
   metadata:
     name: cluster-with-metrics
   spec:
     instances: 3

     storage:
       size: 1Gi
   - --
   apiVersion: monitoring.coreos.com/v1
   kind: PodMonitor
   metadata:
     name: cluster-with-metrics
   spec:
     selector:
       matchLabels:
         cnpg.io/cluster: cluster-with-metrics
     podMetricsEndpoints:
     - port: metrics
   EOF

To access Prometheus, port-forward the Prometheus service:

.. code:: sh

   kubectl port-forward svc/prometheus-community-kube-prometheus 9090

Then access the Prometheus console locally at: `http://localhost:9090/ <http://localhost:9090/>`_ 

You should find a series of metrics relating to CloudNativePG clusters.
Please refer to the :ref:`monitoring section <Monitoring>`  for more information.

.. figure:: /images/prometheus-local.png
   :width: 70% 
   :alt: local prometheus

   local prometheus

You can also monitor the CloudNativePG operator by creating a PodMonitor
to target it. See the relevant section in the :ref:`monitoring page <Monitoring>`  .

You can define some alerts by creating a ``prometheusRule`` :

.. code:: sh

   kubectl apply -f \
     https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/https://raw.githubusercontent.com/cloudnative-pg/cloudnative-pg/main/docs/src/samples/monitoring/prometheusrule.yaml

You should see the default alerts now:

.. code:: sh

   % kubectl get prometheusrules                      
   NAME                                                       AGE
   cnpg-default-alerts                                        3m27s

In the Prometheus console, you can click on the *Alerts* menu to see the
alerts we just installed.

Grafana Dashboard
^^^^^^^^^^^^^^^^^

In our installation so far, Grafana is deployed with no predefined
dashboards.

To open Grafana, you can port-forward the grafana service:

.. code:: sh

   kubectl port-forward svc/prometheus-community-grafana 3000:80

and access Grafana locally at `http://localhost:3000/ <http://localhost:3000/>`_ 

providing the credentials ``admin`` as username, ``prom-operator`` as
password (defined in ``kube-stack-config.yaml`` ).

CloudNativePG provides a default dashboard for Grafana in the dedicated
`grafana-dashboards <https://github.com/cloudnative-pg/grafana-dashboards>`_  . You can download the file `grafana-dashboard.json <https://github.com/cloudnative-pg/grafana-dashboards/blob/main/charts/cluster/grafana-dashboard.json>`_ 

and manually import it via the GUI (menu: Dashboards > New > Import).
You can now click on the ``CloudNativePG`` dashboard just created:

.. figure:: /images/grafana-local.png
   :width: 70% 
   :alt: local grafana

   local grafana

..  Warning::
   Some graphs in the previous dashboard make use of metrics that are in alpha stage by the time this was created, like `kubelet_volume_stats_available_bytes`  and `kubelet_volume_stats_capacity_bytes`  producing some graphs to show `No data` . 　

Note that in our local setup, Prometheus and Grafana are configured to
automatically discover and monitor any CloudNativePG clusters deployed
with the Monitoring feature enabled.