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System Modernization – QAT Global Government Case Study 2015.

In response to the needs of a federal government agency, QAT Global developed a modernized system to handle a growing 140 TB Oracle database of image data, ensuring horizontal scaling and fast retrieval times. By utilizing Cassandra for metadata storage and IBM GPFS for image data, the solution maintained the functionality of existing systems while significantly enhancing performance under heavy load.

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System Modernization – QAT Global Government Case Study 2015

System Modernization for Government Agency

System Developed to Support Horizontal Scaling and Data Replication

Customer Snapshot

  • Federal government agency
  • System supports over 7,000 internal users in addition to the public

Solution Snapshot

  • At peak load, the system is processing the download of hundreds of images per second
  • Revolutionized usability and functionality

Skills Needed

  • DataStax Cassandra
  • IBM GPFS
  • Java
  • JBoss EAP 6.3
  • Jenkins
  • RedHat CloudForms
  • RedHat Enterprise Linux
  • Spring Framework

Key Differentiators

  • Federal government modernization expertise
  • Solutions for managing large volumes of data quickly and efficiently

A federal government agency needed to move a growing 140 TB Oracle database table of image data into a system that supports horizontal scaling and can be replicated between multiple data centers. The system was required to be able to retrieve images on an average of 50 milliseconds per image under heavy load. It also had to be able to support annual growth of 10%. In addition, the existing systems that retrieve the images had to remain unchanged.

The agency selected QAT Global to provide the path to a successful system modernization.

System Modernization

QAT Global’s Approach

QAT Global designed a solution that used Cassandra for storing the metadata related to the associated documents and used IBM GPFS to store the image data.  RESTful Services were created to interface with the different platforms for loading and retrieval of the image documents and metadata.  Existing RMI services were modified internally to use the new REST services for loading and retrieval so the existing systems that retrieve the images did not have to change.