=============
elasticsearch
=============

elasticsearch manifest
^^^^^^^^^^^^^^^^^^^^^^

This uses the PVs created previously.
More PVs would have to be added to cover more nodes.

This example creates multi-tasking nodes, instead of dedicated master nodes.
If I had more of a lab I'd consider adding more nodes.

The attempt at a service is still questionable, hopefully it works out.

.. literalinclude:: src/2.1-elastic.yml
   :language: yaml

manifest metadata
^^^^^^^^^^^^^^^^^

This first section just defined that we're using the elastic APIs, and that
these containers will be `Elasticsearch` containers.
Naming them `elasticsearch` is an easy choice, and this will be referenced
in other container definitions.
So make sure the name is unique enough for your k8s installation.

.. code-block:: yaml

   ---

   apiVersion: elasticsearch.k8s.elastic.co/v1
   kind: Elasticsearch
   metadata:
     name: elasticsearch

container spec
^^^^^^^^^^^^^^

This section contains a bit of information about the containers.
`version` is the version of elasticsearch to run, this should be kept
in sync with `kibana` and `agents`.
Under `config` are config options for elasticsearch.
In this instance I've included the `node.roles` so each node knows what
it should be doing.

.. XXX node.store.allow_mmap ?

.. code-block:: yaml

   spec:
     version: 8.12.1
     nodeSets:
     - name: default
       config:
         node.roles: [ "master", "data", "ingest", "transform", "ml" ]
         node.store.allow_mmap: false

podTemplate
^^^^^^^^^^^

The next section includes more configuration information, but this
time for the containers.
The `labels` under `metadata` can contain whatever information you
want.
Under `spec` we name the containers.
In this case we use `elasticsearch`, but it could be any name.
`resources` has the resources dedicated to the containers, in this
case `8Gi` of RAM and 1 CPU.
These values should be adjusted depending on the resources available
(and I have very few).
Finally, the `env` contains an environment variable being used for
elasticsearch.
This one limits the amount of RAM elasticsearch will use for data.

.. code-block:: yaml

       podTemplate:
         metadata:
           labels:
             deployment: prod
         spec:
           containers:
           - name: elasticsearch
             resources:
               limits:
                 memory: 8Gi
                 cpu: 1
             env:
             - name: ES_JAVA_OPTS
               value: "-Xms4g -Xmx4g"

number of nodes and storage volumes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

`count` is the number of these nodes to run, in this case they're all
`hot` nodes.
This section also defines the `PersistentVolume Claims <https://kubernetes.io/docs/concepts/storage/persistent-volumes/>`_
As noted, the `name` should not change.
I'm using local PVs, and I think `ReadWriteOnce` is necessary, but not positive.
I've requested `100Gi` for storage, and it's using the Storage Class `local-data`.
.. XXX link to SC definition here

.. code-block:: yaml

       count: 3
       volumeClaimTemplates:
       - metadata:
           name: elasticsearch-data # Do not change this name unless you set up a volume mount for the data path.
         spec:
           accessModes:
           - ReadWriteOnce
           resources:
             requests:
               storage: 100Gi
           storageClassName: local-data


http service
^^^^^^^^^^^^

Elasticsearch runs an http service, and this defines some of the options.
I'm using a LoadBalancer (MetalLB) to handle connections, and I've
reserved the IP `192.168.18.70`.
I've also setup a TLS cert/key combo in a k8s secret names
`elasticsearch-tls`.
Elasticsearch uses that cert/key for incoming connections, but not
elasticsearch to elasticsearch connections.
A self-signed cert option is available.

.. code-block:: yaml

     http:
       service:
         spec:
           type: LoadBalancer
           loadBalancerIP: 192.168.18.70
       tls:
         certificate:
           secretName: elasticsearch-tls