Through Amalgam’s creation of data structures and logic, powered by contemporary code, Kubernetes clustering, and auto containerization, the company was able to maintain current operations, enhance the efficiency of legacy processes, and create a more nimble architecture to support the future growth of the business.
Multithread key blocks of code
Streamline code transfers
Dynamically opt for more server space
Easily search through agent data
- DevOps Assessment: This assessment allowed amalgam to analyze and outline current architecture maturity as well as identify a roadmap for improvement.
- Creation of new reporting logic and key data fields: Amalgam created data structures in PostgreSQL and Java with Kubernetes clustering and auto-containerization, enabling the company to streamline code logic, multithread key code blocks, and auto opt for server space
- Data Migration and Clean-Up: The amalgam team migrated legacy data from mySQL to PostgreSQL, scrubbed legacy data, and added key data fields for agent management
- Revamp of UX/UI interfaces: The team worked closely with management to engineer a new interface to facilitate all business reporting and resource management with contemporary functionality and design
- Ability to multithread key blocks of code: The client’s code was formerly single threaded in its legacy implementatation, causing unnecessarily long run times for key blocks of code. Amalgam’s new code logic in Java allowed the client to take advantage of multithreading for faster run times
- Ability to streamline logic through auto-containerization: The client’s management were experiencing logic slow downs due to a lack of containerization in their infrastructure. Amalgam’s usage of Kubernetes clustering enabled the client to take advantage of the containerization of libraries and dependencies to streamline run times
- Ability to auto-opt for more server space: Formerly, the client had to rely on manual opt-ins for additional server space. Because of amalgam’s implementation of X, more server space is automatically added as needed to sustain the client’s operations
Streamlined run times with auto-containerization, Kubernetes clustering, and multithreading
Enabled the ability to auto opt for server space
Scrubbed data and created new data structures
Created security and backup protocols for key data