Akamas Docs
3.6
3.6
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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
      • Selecting Cluster Nodes
    • 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
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    • Collecting support information
  • Using
    • System
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    • Study
      • Offline Study
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        • Analyzing results of live optimization studies
      • Windowing
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  • 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
  • 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
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      • System
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    • Construct templates
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      • Study template
        • Goal & Constraints
        • Windowing policy
          • Trim windowing
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        • Parameter selection
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        • Steps
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        • Parameter rendering
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    • Workflow Operators
      • General operator arguments
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      • SparkLivy Operator
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      • 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
        • Horizontal Pod Autoscaler v1
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        • 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
    • Performing load testing to support optimization activities
    • 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
    • Setup Locust telemetry via CSV
    • Setup AppDynamics integration
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On this page
  • Get Akamas Docker artifacts
  • Import Docker images
  • Configure Akamas environment variables
  • Run installation

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  1. Installing
  2. Docker compose installation
  3. Install the Akamas Server

Offline installation mode

Akamas is deployed as a set of containerized services running on Docker and managed via Docker Compose. In the offline installation mode, the latest version of the Akamas Docker Compose file and all the images required by Docker cannot be downloaded from the AWS ECR repository.

Get Akamas Docker artifacts

Get in contact with Akamas Customer Services to get the latest versions of the Akamas artifacts uploaded to a location of your choice on the dedicated Akamas Server.

Akamas installation artifacts will include:

  • images.tar.gz: a tarball containing Akamas main images.

  • docker-compose.yml: docker-compose file for Akamas.

  • akamas: the binary file of the Akamas CLI that will be used to verify the installation.

Import Docker images

A preliminary step in the offline installation mode is to import the shipped Docker images by running the following commands in the same directory where the tar files have been stored:

cd <your bundle files location>
docker image load -i images.tar.gz

Mind that this import procedure could take some time!

Configure Akamas environment variables

To configure Akamas, you should set the following environment variables:

  • AKAMAS_CUSTOMER: the customer name matching the one referenced in the Akamas license.

  • AKAMAS_BASE_URL: the endpoint in the Akamas APIs that will be used to interact with the CLI, typically https://<akamas server DNS address>

To avoid losing your environment variables for future upgrades, it is suggested to keep them in the .env file, stored in the same directory as the docker-compose.yml:

.env
# Required variables
AKAMAS_CUSTOMER=<your name or your organization name>
AKAMAS_BASE_URL=https://<akamas server DNS address>

# Optional variables
## Database password. Use DEFAULT_DATABASE_PASSWORD to set a custom password for all databases
DEFAULT_DATABASE_PASSWORD=
## A custom password per each service can be set using the variables below, otherwise, the default is used. For example, for Kong's database, the password is `akamas_kong`.
KONG_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_kong}
AIRFLOW_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_airflow}
KEYCLOAK_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_keycloak}
ANALYZER_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_analyzer}
CAMPAIGN_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_campaign}
LICENSE_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_license}
OPTIMIZER_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_optimizer}
ORCHESTRATOR_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_orchestrator}
SYSTEM_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_system}
TELEMETRY_DATABASE_PASSWORD=${DEFAULT_DATABASE_PASSWORD:-akamas_telemetry}
# Docker volumes prefix
COMPOSE_PROJECT_NAME=${COMPOSE_PROJECT_NAME:-akamas}

Run installation

To start Akamas you can now simply navigate into the akamas folder and run a docker-compose command:

cd <your docker-compose file location>
docker compose up -d

You may get the following error:

Error saving credentials: error storing credentials - err: exit status 1, out: Cannot autolaunch D-Bus without X11 $DISPLAY
  • Ubuntu

sudo apt-get install -y pass
  • RHEL

yum install pass

Last updated 9 months ago

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This is a documented docker bug (see ) that can be solved by installing the "pass" package:

this link