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We implement advanced analytics solutions to help companies reach their business operation goals. With over 30 years of experience and a global presence, we are the leading developer of advanced analytics solutions.
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DBOSDecisionBrain Optimization Server Filippo Focacci ffocacci@decisionbrain.com Michel Eisenmann michel.eisenmann@decisionbrain.com
Leading Developer of Advanced Analytics Solutions We implement advanced analytics solutionsto help companies reach their business operation goals GLOBAL PRESENCE IBM PARTNERSHIP THOUGHT LEADERSHIP • Largest global IBM business partner for optimization solutions • Beacon Award finalist in 2018 • France • Hong Kong • 30+ years experience in advanced analytics • Robust growth trajectory with over 30 employees, most PhDs
Global Partners Who Trust our Advanced Analytics CUSTOMERS WORKFORCE DEPLOYMENTS MANUFACTURING / LOGISTICS SUPPORT TO R&D
A Platform Built to Ease Optimization Development & Deployment Aleanbut powerful system designed to help you build and deploy fully scalableapplications – quickly, easily, efficiently. MODULAR ARCHITECTURE Comes with pre-embedded workers and support for optimization models using CPLEX or OPL STATE-OF-THE-ART TECHNOLOGY Relies on standards and open source software, supports both local (Docker) and enterprise (OpenShift) configuration EMBEDDED MONITORING CAPABILITIES Simple web console makes it easy for users and administrators to monitor real-time job execution, KPI evolutions, and manage queuing and failovers
Main Concepts • Easy–to-access from a Web Console or an external Client (Rest API) MAIN ARCHITECTURE Optimization Worker RUN & MONITOR JOBS Client Optimization Worker Ajobhas a type (Task) and input/output One worker may support multiple Tasks Optimization Worker DB Optimization Server Web Console Messaging Master Tasks: - CPLEX - CPO Rabbit HQ Optimization Worker Task: OPL Database MongoDB
DBOS Key Features • Interactive Web Console • Off-the-shelf support for IBM ILOG CPLEX • Docker-based deployment • Extensibility and full customization • Support for Kubernetes/OpenShift • Integration via REST API • Replay Executions IT Department Dev/Deployment Teams OR Department Development teams
Web Console – Drag-and-drop interface Create and start a new job (from task definition) QUICK JOB CREATION
Web Console – Job Monitoring Track KPIs, progresses and logs in real-time MONITOR JOB EXECUTION
Web Console – System Monitoring REAL-TIME UPDATES • Quickly review system behavior • Immediately track execution issues
Web Console – System Monitoring REAL-TIME UPDATES • Quickly review system behavior • Immediately track execution issues
On-shelf CPLEX/OPL workers Optimization Worker Optimization Worker Pre-defined workers for CPLEX/OPL* to minimize processing time and maximize efficiency Web Console DBOS Messaging Master Rabbit HQ Tasks: - CPLEX - CPO CPLEX / CP OPTIMIZER WORKER (Integer) Linear Programming Quadratic Programming Constraint Programming OPL WORKER CPLEX/OPL WORKERS Optimization Worker Database MongoDB Optimization Worker Task: OPL INPUTS PROCESS OUTPUT • Optimization model • Data & settings • Solution *version 12.8+
Docker-based Deployment As efficient as virtual machines, but much faster and modern with small footprints on servers, making it deployable everywhere. • Local with Docker-compose • Quick and simple • Template available Optimization Worker DOCKER PACKAGING Client Optimization Worker DEPLOYMENT Optimization Worker DBOS Web Console Messaging Master Rabbit HQ Tasks: - CPLEX - CPO Optimization Worker Task: OPL Database MongoDB
Easy to extend and customize Have the flexibility to design custom workersusing Java-based code Optimization Worker CUSTOM WORKERS Tasks: - CPLEX - CPO • Your optimization code • Your machine learning code • Any kind of CPU intensive computation DEFINE AND IMPLEMENT TASK(S) WITH: Custom Worker Custom Worker Optimization Server Web Console Messaging Master Custom Worker Rabbit HQ Your Task(s) Optimization Worker Task: OPL Database MongoDB
Web Console - Ready to Support Extensions CLICK-TO-RUN No web development required to support extensions • IMMEDIATE DATA PREP • Dynamically transforms and prepares data no matter its format or complexity
Designed for Advanced Deployment Supports both an industrial deployment (full Kubernetes and OpenShift compatibility) and local deployment using Docker-Compose Optimization Worker DEPLOYMENT Optimization Worker Cluster with OpenShift Failover Easy scalability Easy automation Resource monitoring Optimization Server Optimization Worker Web Console Messaging Master Rabbit HQ Optimization Worker Database MongoDB Local with Docker-compose Quick and simple Template available
Seamless, Easy Integration Use of REST API technology makes it easy to integrate with projects involving complex mathematical modeling MULTIPLE LANGUAGES / FRAMEWORKS SUPPORT
Replay Job Executions – Monitor and Retrieve • Monitor Failures • Retrieve input conditions Optimization Worker Replay Client Optimization Worker Optimization Server Optimization Worker Web Console Messaging Master Rabbit HQ Optimization Worker DOWNLOAD LOGS & REPRODUCE Database MongoDB
Map-Reduce for Optimization: Build and Deploy Optimization Decomposition on Distributed Resources in the Cloud Today 11:00am-12:45pm Room 306