Deployments in Kubernetes

The deployment is expected to be given as a file named 'deployment-'+docker+'-'+instance+'.yml' Such files are generated from a template.

Content of this document:

How do templates work
- What templates are included
- Adjust the templates to your cluster
How to parametrize templates at runtime

Templates

Template files are named 'deploymenttemplate-"+docker+".yml'.

To generate a file 'deployment-'+docker+'-'+instance+'.yml' from this

the instance name is understood as cpu-mem-gpu-gputype
the yaml file is changed as

dep['spec']['template']['spec']['containers'][0]['resources']['requests']['cpu'] = cpu
dep['spec']['template']['spec']['containers'][0]['resources']['limits']['cpu'] = cpu
dep['spec']['template']['spec']['containers'][0]['resources']['requests']['memory'] = mem
dep['spec']['template']['spec']['containers'][0]['resources']['limits']['memory'] = mem
dep['spec']['template']['spec']['nodeSelector']['gpu'] = gputype
dep['spec']['template']['spec']['containers'][0]['resources']['limits']['nvidia.com/gpu'] = int(gpu)

Included

This repository includes some templates at https://github.com/Beuth-Erdelt/Benchmark-Experiment-Host-Manager/tree/master/k8s

DBMS included are:

MariaDB (10.4.6)
MonetDB (11.31.7)
OmniSci (v5.4.0)
PostgreSQL (11.4)

To be added in near future:

Exasol (7.0.0)
You will need a Docker image including EXAplus
MemSQL (centos-7.1.8-43a12901be-2.0.0-1.7.0)
You will have to add a licence key
MySQL (8.0.21)
You will need a Docker image including tar
Oracle DB (18.4.0-xe)
You will need to build the Docker image
MS SQL Server (2019-CU5-ubuntu-18.04)

Your Cluster

To make these work, you may have to add the name of your Docker pull secret and the name of your persistant volume.

The default name of the secret is private-registry-auth:

imagePullSecrets:
- {name: private-registry-auth}

The default name of the PV is volume-benchmarking:

- name: benchmark-data-volume
  persistentVolumeClaim: {claimName: volume-benchmarking}

Parametrize Templates

The resources (requests, limits and nodeSelector) can also be set explicitly using

cluster.set_resources(
  requests = {
    'cpu': cpu,
    'memory': mem
  },
  limits = {
    'cpu': 0,     # unlimited
    'memory': 0   # unlimited
  },
  nodeSelector = {
    'cpu': cpu_type,
    'gpu': gpu_type,
  })

For further information and option see the documentation.