Deploy an IBM DOC Business Application on Red Hat Openshift in a New Free Interactive Lab
IBM Open Labs provides tutorials and use case videos prepared by experts, to enable you to explore the newest cloud technologies.
Log in and try out the new IBM DOC Open Lab.
Enter a pre-configured environment and follow a step-by-step guide to assist you with Red Hat Openshift deployment.
In just a few minutes, you will be able to:
- Access Red Hat OpenShift on IBM Cloud Basics
- Deploy a DOC-based application built around a simple capacity planning problem
- Run it on the cloud and make it available for business users
In addition, you will have the chance to explore the functionalities provided out-of-the-box by the innovative IBM Decision Optimization Center.
In the lab, you will:
- Run optimization engine through the UI of the deployed application
- Monitor real-time job execution
- Review the optimization results in the dedicated views
- Duplicate scenarios and perform a what-if analysis
IBM Decision Optimization Center (DOC) provides a configurable framework to support business decision-makers such as scientists, developers, analysts, and planners. It uses powerful optimization technologies (CPLEX Solver) along with other advanced analytics techniques to solve tough planning and scheduling challenges.
Among its main features, DOC
- Provides a configurable web UI
- Provides What-if analysis capabilities
- Accelerates local and cloud deployment thanks to predefined configuration scripts
- Eases the application maintenance thanks to monitoring and replay-execution capabilities
DOC is an optimization platform to create, deploy, and maintain fully scalable decision support solutions. It promotes end-user adoption by facilitating continuous feedback from business users during application development. Explore the IBM Cloud Lab and try IBM Decision Optimization Center today!
Learn more about DOC:
IBM Decision Optimization Center on IBM Cloud Lab
IBM DOC powered by DecisionBrain
DOC Capacity Planning Interactive Demo
A huge thanks to our colleagues in DecisionBrain and IBM for your contribution in creating this lab: Alexa Salles, Alkesh Dagade, Andy Jones, Durgadas Kamath, John Chaves, Michel Eisenmann, Nerav Doshi and Robert Tietzsch.
