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Automation of In-Field Job Planning and Performance Optimization

Cloud Foundry

The customer wanted to develop a job planner that builds optimal working schedules, setting priorities for the customer’s installation teams.

Automation of In-Field Job Planning and Performance Optimization

About the project

Brief results of the collaboration:

  • Automated job planning, reducing time spent on installation / logistics
  • Cut overhead expenses, saving around $1,000,000 per year
  • Accelerated development cycles by 1.5 times
  • Improved performance of the job planning system, speeding up data processing by 2x and search by >10x

The challenge

During the project, the developers had to address the following challenges:

  • The existing process of building job schedules was overcomplicated—due to default settings and limitations of an OptaPlanner-based data processing module.
  • The validation mechanisms for data-entry forms required unification.
  • A decent level of security should be ensured, since the system was integrated with a number of IoT / mobile devices.

The solution

To speed up development and delivery, Altoros relied on GE Predix. The architects also applied the hexagonal architecture methodology to get rid of redundant structures. This approach eventually accelerated the development process by 1.5x.

Using Spring Data and Apache OpenJPA, Altoros’s engineers optimized the domain model of the automation system, streamlining requests sent to the database. As a result, the speed of data processing was improved by a factor of two.

To optimize search across the database, the team implemented the CQRS (Command and Query Responsibility Segregation) pattern. Now, any type of entities can be found 10+ times faster.

To unify input data, the Cloud Foundry experts at Altoros created a library that validates any types of forms and supports two-way data binding. The library allows for describing constraints in a declarative way and validating forms of any nested type.

The outcome

As a result of this cooperation, the customer has automated job planning for its installation teams. Altoros has also helped the customer to fix performance bottlenecks of the automation system: the speed of data processing was increased by 2x, while data entries can now be found >10x faster. In addition, the customer service has been improved, since pre-installation procedures and logistics now take less time.

Technology stack

Server platforms

Cloud Foundry, Predix

Client platform

Apache Tomcat

Programming languages

Java, JavaScript


OptaPlanner, AngularJS, Polymer, Spring Data, Spring Boot, Apache OpenJPA, RabbitMQ, Activiti, Rally, CQRS, Node-RED




Want to develop something similar?

Ryan Meharg

Ryan Meharg

Technical Director

ryan.m@altoros.com650 265-2266

4900 Hopyard Rd. Suite 100 Pleasanton, CA 94588