Case Study
A leading US telecommunications provider embarked on a large-scale transformation to modernize its consumer wireless applications operating on legacy mainframe systems. The applications were heavily dependent on thousands of batch jobs running on costly and inflexible mainframe and DB2 platforms, limiting agility and slowing time to market. To remain competitive in a digital-first landscape, the client sought Infosys’ expertise to reduce operational costs, modernize critical workloads, and enable scalability.
Infosys conducted an in-depth analysis of over 8,000 mainframe batch jobs, identifying optimization and modernization opportunities. Based on this assessment, Infosys designed and executed a phased migration strategy that retired more than 900 legacy jobs and modernized 290+ jobs using a cloud-native, microservices-based architecture. Batch processing was transformed using scalable frameworks and automation, significantly reducing mainframe dependency.
By leveraging Infosys’ deep mainframe modernization experience, cloud engineering capabilities, and AI-enabled automation, the program delivered measurable outcomes including substantial annual cost savings, reduced MIPS consumption, faster release cycles, and improved operational resilience. The client now operates on a future-ready digital platform that supports innovation, scalability, and sustained business growth.
$7.35M
Annual TCO savings
900
Legacy mainframe batch jobs retired
290+
Jobs modernized and migrated to microservices architecture
4900MIPS
Monthly reduction in mainframe consumption
Key Challenges
- High recurring costs from legacy mainframe and DB2 platforms
- Slow time to market due to rigid schemas and lengthy development cycles
- Complex COBOL-driven dependencies limiting the speed of modernization
- Fragmented data across Cassandra, Oracle, and DB2 systems
- Risk of data integrity issue for high-volume batch orchestration
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Infosys Approach
Leveraged modern technology stack, including Spring Boot, Spring Batch, Angular, AWS, ELK, Apache Camel, RMQ, Kafka, Oracle DB, Cassandra, and Copilot
Applied AI-driven reverse engineering and automation using Infosys iLEAD (Live Enterprise Application Development) Platform
Assessed 8,000+ batch jobs to build a data-driven modernization roadmap
Implemented extensible, configuration-driven frameworks for job orchestration
Adopted incremental migration with controlled cutover and validation
Migrated mainframe workloads to AWS-based microservices architecture
Enabled chunk-based and parallel execution for high-volume data processing
Embedded DevSecOps, CI/CD pipelines, and SRE practices to ensure operational resilience
The Solution
Cloud-native mainframe modernization using microservices, AI, and automation
Infosys delivered a comprehensive mainframe modernization solution that transitioned critical mainframe workloads to a cloud-native, microservices-based architecture on AWS. The solution enabled seamless offloading from the mainframe, significantly reducing infrastructure and licensing costs while improving scalability and agility.
Reusable microservices were implemented to automate batch processing, data extraction, validation, and job orchestration. Infosys leveraged AI-powered Copilot capabilities to reverse-engineer legacy logic, accelerate code generation, and ensure quality through automated reviews. Security, compliance, and observability were strengthened through SRE and DevSecOps integration, delivering continuous governance and proactive monitoring.
The resulting API-first, cloud-first architecture established a modular and composable foundation—future-proofing the client’s digital ecosystem and enabling rapid innovation across telecom operations.
Business Outcomes
Achieved $7.35M annual savings and reduced 4,900 MIPS per month
Retired 900 legacy batch jobs and modernized 293 jobs
Accelerated time to market through automated pipelines and microservices architecture
Improved operational efficiency and release cadence
Delivered more reliable, scalable consumer services across platforms
Lowered licensing and infrastructure costs through mainframe offloading
Benefits
Lower costs and faster innovation through cloud-first mainframe modernization.
Reduced TCO by eliminating mainframe/DB2 reliance and excess licensing.
Faster product delivery through automated pipelines and standard-aligned microservices.
Improved customer experience via more performant and reliable digital services.
Simplified the operations and support with fewer legacy jobs and system dependencies.
Scalable architecture supporting growth and high volume orchestration.
Improved data integrity and observability across previously fragmented platforms.
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