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Planning Analytics Workspace Local Distributed

[fa icon="calendar"] August 30, 2019 / by Amin Mohammed

Amin Mohammed

PAW Local Distributed is an upgrade to Planning Analytics Local Workspace that can be deployed in a container orchestration engine using either Docker Swarm by Docker or Kubernetes - an open source by Google, for high availability, fail-over, scalability, and fault tolerance in multiple application servers or virtual or even cloud machines.





The Planning Analytics Workspace Distributed is run on a Swarm mode by deploying the application on multiple Docker nodes (with unique node ids) also known as Swarm.


Docker Engine CLI could be used to create a swarm and deploy and manage the application services in swarm.

Swarm mode ensures secured connection across multiple servers. Additionally, some of the key features that Swarm mode offers includes:

Cluster management integrated with Docker Engine,

Declarative service model,

Desired state reconciliation,

Horizontal Scaling and Load Balancing,

Multi-host networking,

Automatic service discovery,

Service Discovery,

Rolling updates with roll-back




The Docker engine maintains high availability by effectively scheduling the failed node’s task to other nodes.

It was released in 2.0.41 version of Planning Analytics Workspace and is available to be downloaded from IBM Fix Centre from below link.


Note: The Docker Swarm is currently supported on Red Hat Enterprise Linux (RHEL) only.

The Docker Enterprise Edition for RHEL could be downloaded from the following link:




Topics: Planning Analytics Workspace, PAW, BI, BI Software, Business Intelligence Applications

Amin Mohammed

Written by Amin Mohammed

Amin is a certified IBM Cognos TM1 solutions expert with over 7 years of experience in Solution Design and Professional Consulting services in a financial services industry across multiple domains. He has a proven track record of successfully leading multiple and timely delivery of onshore as well as offshore engagements in fast paced and highly complex business models, using IBM Cognos Stack.

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