Install Wallaroo with Minimum Services

How to install Wallaroo with disabled services for lower core environments

The following system requirements are required for the minimum settings for running Wallaroo in a Kubernetes cloud cluster.

Minimum number of nodes: 4
Minimum Number of CPU Cores: 8
Minimum RAM per node: 16 GB
Minimum Storage: A total of 625 GB of storage will be allocated for the entire cluster based on 5 users with up to four pipelines with five steps per pipeline, with 50 GB allocated per node, including 50 GB specifically for the Jupyter Hub service. Enterprise users who deploy additional pipelines will require an additional 50 GB of storage per lab node deployed.

Wallaroo recommends at least 16 cores total to enable all services. At less than 16 cores, services will have to be disabled to allow basic functionality as detailed in this table.

Note that even when disabling these services, Wallaroo performance may be impacted by the models, pipelines, and data used. The greater the size of the models and steps in a pipeline, the more resources will be required for Wallaroo to operate efficiently. Pipeline resources are set by the pipeline configuration to control how many resources are allocated from the cluster to maintain peak effectiveness for other Wallaroo services. See the following guides for more details.


Cluster Size		8 core	16 core	32 core	Description
Inference		✔	✔	✔	The Wallaroo inference engine that performs inference requests from deployed pipelines.
Dashboard		✔	✔	✔	The graphics user interface for configuring workspaces, deploying pipelines, tracking metrics, and other uses.
Jupyter HUB/Lab					The JupyterHub service for running Python scripts, JupyterNotebooks, and other related tasks within the Wallaroo instance.
	Single Lab	✔	✔	✔
	Multiple Labs	✘	✔	✔
Prometheus		✔	✔	✔	Used for collecting and reporting on metrics. Typical metrics are values such as CPU utilization and memory usage.
	Alerting	✘	✔	✔
	Model Validation	✘	✔	✔
	Dashboard Graphs	✔	✔	✔
Plateau		✘	✔	✔	A Wallaroo developed service for storing inference logs at high speed. This is not a long term service; organizations are encouraged to store logs in long term solutions if required.
	Model Insights	✘	✔	✔
Python API
	Model Conversion	✔	✔	✔	Converts models into a native runtime for use with the Wallaroo inference engine.

To install Wallaroo with minimum services, a configuration file will be used as parts of the kots based installation. For full details on the Wallaroo installation process, see the Wallaroo Install Guides.

Wallaroo Installation with less than 16 Cores

To install Wallaroo with less than 16 cores and 8 cores or greater, the following services must be disabled:

Model Conversion
Model Insights
Plateau

The following configuration settings can be used at the installation procedure to disable these services.

Download

A sample file wallaroo-install-8-cores.yaml is available from the following link:

wallaroo-install-8-cores.yaml

apiVersion: kots.io/v1beta1
kind: ConfigValues
metadata:
  name: wallaroo
spec:
  values:
    dashboard_enabled:
      value: "1"
    enable_model_insights:
      value: "0"
    model_conversion_enabled:
      value: "1"
    plateau_enabled:
      value: "0"

The configuration file can be applied via the --config-values={CONFIG YAML FILE} option. For example:

kubectl kots install "wallaroo/ce" \
-n wallaroo \ 
--config-values=wallaroo-install-8-cores.yaml

A sample yaml file with the configuration values is retrieved via the kots get config command. See Replicated get config for more details.