Project highlights
- Enhanced network data quality assurance: Integrating Kafka enabled real-time event-driven communication, empowering the client to ensure the accuracy and reliability of geospatial data in real time.
- Scalability optimized for network data integrity: Leveraging AWS infrastructure and Helm for deployment orchestration facilitated seamless scalability while maintaining network data quality.
- Period of cooperation:
- August 2023 – present
- Expertise:
- Cloud & DevOps, Platform Development, Telecom & Media, AWS
- Headquarters:
- San Diego, California
Business challenge
In the competitive telecommunications landscape, ensuring the reliability and accuracy of network data is paramount for delivering exceptional customer experiences. Our client (a US startup) recognized the importance of assuring network data quality, including through network optimization, personalizing services and location-based promotions, and providing location-based support. Leveraging the Intellias team’s proficiency in network data quality assurance, the startup embarked on a strategic upgrade of their network data server infrastructure.
Technology solution
In modernizing the network data reviewer’s server, we strategically leveraged a robust technology stack to enhance performance, scalability, and reliability across multiple application layers. We embraced the latest advancements at the business layer by adopting Java 17 and SpringBoot 3 to ensure efficient web services. Using MySQL as the database management system, we established a solid data storage and retrieval foundation, while Ehcache facilitated caching mechanisms for improved response times. Incorporating Kafka enabled seamless event-driven communication, empowering real-time data processing and analysis within the application.
Our approach extended beyond the business layer to encompass job flow control; integrating SpringBoot 3 and UML-based state machines facilitated streamlined workflow management. Focusing on protocol layer optimization, we integrated the Leshan server alongside Jersey to enable seamless communication between different system components. This layer was a vital bridge between the business logic and network protocols, ensuring smooth data exchange and interoperability.
Additionally, our solution included an intuitive admin portal built on Java 17 and SpringBoot. The admin portal’s front end is built on Vue.js. This portal provides administrators with comprehensive insights and controls, empowering them to effectively manage system configurations and monitor performance.
Leveraging AWS infrastructure and Helm for deployment orchestration, we ensured scalability, reliability, and seamless integration with cloud-native technologies, paving the way for future enhancements and innovations in the network data reviewer’s server ecosystem.
We strategically leveraged a robust technology stack to enhance performance, scalability, and reliability across multiple application layers. Boosting cost-efficiency of 5G roll-outs
Tech stack
Business impact
Intellias worked closely with the startup to enhance the reliability and accuracy of their network data, ensuring that upgraded server infrastructure met stringent quality standards. By implementing robust quality assurance measures, including data validation, cleansing, and integrity checks, Intellias empowered the startup to leverage high-quality geospatial data for informed decision-making and personalized customer services:
- Improved system performance: Modernizing the network data reviewer’s server significantly enhanced system performance by greatly reducing response times.
- Greater scalability: Leveraging AWS infrastructure and Helm for deployment orchestration facilitated seamless scalability, enabling the client to effortlessly accommodate increasing data volumes and user demands.
- Enhanced reliability: By implementing robust quality assurance measures and optimizing the server infrastructure, system reliability was greatly improved, reducing downtime incidents.
- Streamlined workflow management: Integrating SpringBoot 3 at the job flow control layer enabled streamlined workflow management, reducing processing times for critical tasks.
- Real-time data processing: Integration of Kafka enabled real-time event-driven communication, empowering the client to process and analyze network data, leading to quicker insights and decision-making.
- Improved customer satisfaction: Collectively, these enhancements resulted in a tangible improvement in customer satisfaction.
A commitment to assuring network data quality bolstered the startup’s credibility within the telecom industry and laid the foundation for delivering superior customer experiences that are driving loyalty and growth. We continue working on new features and enhancing the client’s solutions to meet new demands posed by the competitive landscape.