This page describes the requirements that should be fulfilled by the user when installing or managing an Akamas installation on Kubernetes. The software listed below is usually installed on the user's workstation or laptop.
Kubectl must be installed and configured to interact with the desired cluster. Refer to the official kubectl documentation to set up the client.
To interact with the Kubernetes API server you will need kubectl, preferably with a version matching the cluster. To check both the client and cluster versions, run:
Installing Akamas requires Helm 3.0 or higher. To check the version run:
Akamas uses Elasticsearch to store logs and time-series. When running Akamas on Kubernetes, Elasticsearch is installed, automatically using the official Elasticsearch helm chart. This chart required running an init container with privileged access to set up a configuration on the host running the Elasticsearch pod. If running such a container is not permitted in your environment you can add the following snippet to the akamas.yaml
file when installing Akamas to disable this feature. \
Before installing the Akamas please make sure to review all the following requirements:
Running Akamas requires a cluster running Kubernetes version 1.23 or higher.
Akamas can be deployed in three different sizes depending on the number of concurrent optimization studies that will be executed. If you are unsure about which size is appropriate for your environment we suggest you start with the small one and upgrade to bigger ones as you expand the optimization activity to more applications.
The tables below report the required resources both for requests and limits that should be available in the cluster to use Akamas.
Small
The small tier is suited for environments that needs to support up to 10 concurrent optimization studies
Resource | Requests | Limits |
---|
The cluster must provide the definition of a Storage Class so that the application installation can leverage Persistent Volume Claims to dynamically provision the volumes required to persist data.
For more information on this topic refer to .
To work properly, Akamas needs to manage some resources inside the Namespace. For this reason, it is recommended to run Akamas in a dedicated Namespace.
To manage resources, Akamas uses a ServiceAccount bound to the application's pods, which must be created either manually by the cluster administrator or automatically by the provided Helm chart.
This snippet describes the namespaced required permissions for the service account:
Networking requirements depend on how users interact with Akamas. Services can be exposed via Ingress, LoadBalancers, NodePorts, or . Refer to for a more detailed description of the available options.
CPU | 2.5 Cores | 4.5 Cores |
Memory | 16 GB | 18GB |
Disk Space | 70 GB | 70 GB |