This page describes the requirements that should be fulfilled by the user when installing or managing an Akamas installation on Kubernetes. The software 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 APIs, you will need kubectl, preferably with a version matching the cluster. To check both the client and cluster versions, run the following:
Installing Akamas requires Helm 3.0 or higher. To check the version, run the following:
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 Elasticsearch pod host. 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 1.24 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.
The resources specified on this page have been defined by considering using a dedicated namespace to run only Akamas components. If your cluster has additional tools (E.g. a service mesh or a monitoring agent) that inject containers in the Akamas pods we suggest either disabling them or increasing the sizing considering their overhead. Also if you plan to deploy other software inside the Akamas namespace and resource quotas are enabled you should increase the size considering the resources required by the specific software.
The small tier is suited for environments that need to support up to 3 concurrent optimization studies
| Resource | Requests | Limits |
|---|---|---|
The medium tier is suited for environments that need to support up to 50 concurrent optimization studies
| Resource | Requests | Limits |
|---|---|---|
The large tier is suited for environments that need to support up to 100 concurrent optimization studies. If you plan to run more concurrent studies, please contact Akamas support to plan your installation.
The cluster must define 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 Kubernetes' official documentation.
To install and run Akamas cluster level permissions are not required. This is the minimal set of namespaced rules.
Networking requirements depend on how users interact with Akamas. Services can be exposed via Ingress or using kubectl as a proxy. Refer to Accessing Akamas for a more detailed description of the available options.
| Resource | Requests | Limits |
|---|---|---|
CPU
4 Cores
15 Cores
Memory
28 GB
28 GB
Disk Space
70 GB
70 GB
CPU
8 Cores
20 Cores
Memory
50 GB
50 GB
Disk Space
100 GB
100 GB
CPU
10 Cores
25 Cores
Memory
60 GB
60 GB
Disk Space
150 GB
150 GB