Akamas Docs
3.5
3.5
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  • Installing
    • Architecture
    • Docker compose installation
      • Prerequisites
        • Hardware Requirements
        • Software Requirements
        • Network requirements
      • Install Akamas dependencies
      • Install the Akamas Server
        • Online installation mode
          • Online installation behind a Proxy server
        • Offline installation mode
        • Changing UI Ports
        • Setup HTTPS configuration
      • Troubleshoot Docker installation issues
    • Kubernetes installation
      • Prerequisites
        • Cluster Requirements
        • Software Requirements
      • Install Akamas
        • Online Installation
        • Offline Installation - Private registry
      • Installing on OpenShift
      • Accessing Akamas
      • Useful commands
    • Install the CLI
      • Setup the CLI
      • Initialize the CLI
      • Change CLI configuration
      • Use a proxy server
    • Verify the installation
    • Installing the toolbox
    • Install the license
    • Manage anonymous data collection
  • Managing Akamas
    • Akamas logs
    • Audit logs
    • Upgrade Akamas
      • Docker compose
      • Kubernetes
    • Monitor Akamas status
    • Backup & Recover of the Akamas Server
    • Users management
      • Accessing Keycloak admin console
      • Configure an external identity provider
        • Azure Active Directory
        • Google
      • Limit users sessions
        • Local users
        • Identity provider users
    • Collecting support information
  • Using
    • System
    • Telemetry
    • Workflow
    • Study
      • Offline Study
      • Live Study
        • Analyzing results of live optimization studies
      • Windowing
      • Parameters and constraints
  • Optimization Guides
    • Optimize application costs and resource efficiency
      • Kubernetes microservices
        • Optimize cost of a Kubernetes deployment subject to Horizontal Pod Autoscaler
        • Optimize cost of a Kubernetes microservice while preserving SLOs in production
        • Optimize cost of a Java microservice on Kubernetes while preserving SLOs in production
      • Application runtime
        • Optimizing a sample Java OpenJDK application
        • Optimizing cost of a Node.js application with performance tests
        • Optimizing cost of a Golang application with performance tests
        • Optimizing cost of a .NET application with performance tests
      • Applications running on cloud instances
        • Optimizing a sample application running on AWS
      • Spark applications
        • Optimizing a Spark application
    • Optimize application performance and reliability
      • Kubernetes microservices
        • Optimizing cost of a Kubernetes microservice while preserving SLOs in production
        • Optimizing cost of a Java microservice on Kubernetes while preserving SLOs in production
      • Applications running on cloud instances
      • Spark applications
  • Integrating
    • Integrating Telemetry Providers
      • CSV provider
        • Install CSV provider
        • Create CSV telemetry instances
      • Dynatrace provider
        • Install Dynatrace provider
        • Create Dynatrace telemetry instances
          • Import Key Requests
      • Prometheus provider
        • Install Prometheus provider
        • Create Prometheus telemetry instances
        • CloudWatch Exporter
        • OracleDB Exporter
      • Spark History Server provider
        • Install Spark History Server provider
        • Create Spark History Server telemetry instances
      • NeoLoadWeb provider
        • Install NeoLoadWeb telemetry provider
        • Create NeoLoadWeb telemetry instances
      • LoadRunner Professional provider
        • Install LoadRunner Professional provider
        • Create LoadRunner Professional telemetry instances
      • LoadRunner Enterprise provider
        • Install LoadRunner Enterprise provider
        • Create LoadRunner Enterprise telemetry instances
      • AWS provider
        • Install AWS provider
        • Create AWS telemetry instances
    • Integrating Configuration Management
    • Integrating with pipelines
    • Integrating Load Testing
      • Integrating NeoLoad
      • Integrating LoadRunner Professional
      • Integrating LoadRunner Enterprise
  • Reference
    • Glossary
      • System
      • Component
      • Metric
      • Parameter
      • Component Type
      • Workflow
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      • Optimization Pack
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    • Construct templates
      • System template
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      • Parameter template
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      • Component Types template
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      • Telemetry Instance template
      • Workflows template
      • Study template
        • Goal & Constraints
        • Windowing policy
          • Trim windowing
          • Stability windowing
        • Parameter selection
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        • Workload selection
        • KPIs
        • Steps
          • Baseline step
          • Bootstrap step
          • Preset step
          • Optimize step
        • Parameter rendering
        • Optimizer Options
    • Workflow Operators
      • General operator arguments
      • Executor Operator
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      • LinuxConfigurator Operator
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      • SparkSSHSubmit Operator
      • SparkSubmit Operator
      • SparkLivy Operator
      • NeoLoadWeb Operator
      • LoadRunner Operator
      • LoadRunnerEnteprise Operator
    • Telemetry metric mapping
      • Dynatrace metrics mapping
      • Prometheus metrics mapping
      • NeoLoadWeb metrics mapping
      • Spark History Server metrics mapping
      • LoadRunner metrics mapping
    • Optimization Packs
      • Linux optimization pack
        • Amazon Linux
        • Amazon Linux 2
        • Amazon Linux 2022
        • CentOS 7
        • CentOS 8
        • RHEL 7
        • RHEL 8
        • Ubuntu 16.04
        • Ubuntu 18.04
        • Ubuntu 20.04
      • DotNet optimization pack
        • DotNet Core 3.1
      • Java OpenJDK optimization pack
        • Java OpenJDK 8
        • Java OpenJDK 11
        • Java OpenJDK 17
      • OpenJ9 optimization pack
        • IBM J9 VM 6
        • IBM J9 VM 8
        • Eclipse Open J9 11
      • Node JS optimization pack
        • Node JS 18
      • GO optimization pack
        • GO 1
      • Web Application optimization pack
        • Web Application
      • Docker optimization pack
        • Container
      • Kubernetes optimization pack
        • Kubernetes Pod
        • Kubernetes Container
        • Kubernetes Workload
        • Kubernetes Namespace
        • Kubernetes Cluster
      • WebSphere optimization pack
        • WebSphere 8.5
        • WebSphere Liberty ND
      • AWS optimization pack
        • EC2
        • Lambda
      • PostgreSQL optimization pack
        • PostgreSQL 11
        • PostgreSQL 12
      • Cassandra optimization pack
        • Cassandra
      • MySQL Database optimization pack
        • MySQL 8.0
      • Oracle Database optimization pack
        • Oracle Database 12c
        • Oracle Database 18c
        • Oracle Database 19c
        • RDS Oracle Database 11g
        • RDS Oracle Database 12c
      • MongoDB optimization pack
        • MongoDB 4
        • MongoDB 5
      • Elasticsearch optimization pack
        • Elasticsearch 6
      • Spark optimization pack
        • Spark Application 2.2.0
        • Spark Application 2.3.0
        • Spark Application 2.4.0
    • Command Line commands
      • Administration commands
      • User and Workspace management commands
      • Authentication commands
      • Resource management commands
      • Optimizer options commands
    • Release Notes
  • Knowledge Base
    • Creating custom optimization packs
    • Setting up a Konakart environment for testing Akamas
    • Modeling a sample Java-based e-commerce application (Konakart)
    • Optimizing a web application
    • Optimizing a sample Java OpenJ9 application
    • Optimizing a sample Linux system
    • Optimizing a MongoDB server instance
    • Optimizing a Kubernetes application
    • Leveraging Ansible to automate AWS instance management
    • Guidelines for optimizing AWS EC2 instances
    • Optimizing an Oracle Database server instance
    • Optimizing an Oracle Database for an e-commerce service
    • Guidelines for optimizing Oracle RDS
    • Optimizing a MySQL server database running Sysbench
    • Optimizing a MySQL server database running OLTPBench
    • Optimizing a live full-stack deployment (K8s + JVM)
    • Setup Instana integration
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On this page
  • Kubernetes version
  • Resources requirements
  • Storage requirements
  • Permissions
  • Networking

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  1. Installing
  2. Kubernetes installation
  3. Prerequisites

Cluster Requirements

Kubernetes version

Running Akamas requires a cluster running Kubernetes version 1.24 or higher.

Resources requirements

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.

Small

The small tier is suited for environments that need to support up to 3 concurrent optimization studies

Resource
Requests
Limits

CPU

4 Cores

15 Cores

Memory

28 GB

28 GB

Disk Space

70 GB

70 GB

Medium

The medium tier is suited for environments that need to support up to 50 concurrent optimization studies

Resource
Requests
Limits

CPU

8 Cores

20 Cores

Memory

50 GB

50 GB

Disk Space

100 GB

100 GB

Large

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.

Resource
Requests
Limits

CPU

10 Cores

25 Cores

Memory

60 GB

60 GB

Disk Space

150 GB

150 GB

Storage requirements

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.

Permissions

To install and run Akamas cluster level permissions are not required. This is the minimal set of namespaced rules.

- apiGroups: ["", "apps", "policy", "batch", "networking.k8s.io", "events.k8s.io/v1", "rbac.authorization.k8s.io"]
  resources:
    - configmaps
    - cronjobs
    - deployments
    - events
    - ingresses
    - jobs
    - persistentvolumeclaims
    - poddisruptionbudgets
    - pods
    - pods/log
    - rolebindings
    - roles
    - secrets
    - serviceaccounts
    - services
    - statefulsets
  verbs: ["get", "list", "create", "delete", "patch", "update", "watch"]

Networking

Last updated 10 months ago

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For more information on this topic refer to .

Networking requirements depend on how users interact with Akamas. Services can be exposed via Ingress or . Refer to for a more detailed description of the available options.

Kubernetes' official documentation
using kubectl as a proxy
Accessing Akamas