Modernizing legacy IT systems is one of the most critical and complex challenges facing large enterprises today, especially in high-stakes industries like telecom and media, where even brief service interruptions can erode trust and revenue. Few understand this balancing act better than Ranganath Taware, Chief Architect at Capgemini America Inc., who brings over two decades of hands-on experience leading enterprise-scale digital transformations.
With a career spanning 24 years and a deep specialization in telecom, media, and emerging technologies, Taware has guided some of North America’s largest cable and media providers through high-risk modernization efforts. From migrating a decade-old enterprise data warehouse and 600+ BI assets to a real-time analytics architecture on AWS and Snowflake, to transforming $400 million in monthly billing operations with zero downtime, his work consistently delivers both scale and stability.
At the core of Taware’s approach is a commitment to strategic alignment—prioritizing systems that directly impact customer experience, phasing deployments to reduce risk, and fostering collaboration between IT, business, and network operations teams. He also draws on AI, DevOps, and advanced automation to accelerate delivery while preserving data integrity and operational resilience.
In this interview, Taware shares how enterprises can bridge the gap between old and new systems without sacrificing performance or reliability—and why the human element is just as critical as the technology.
Modernizing legacy IT systems
How can companies rationalize outdated IT platforms while ensuring daily operations remain uninterrupted?
In telecom, service reliability isn’t just important; it’s expected. When it comes to modernizing legacy IT systems, I focus on aligning the effort with business priorities while making sure that operations run smoothly. I prioritize systems that impact customers, assess risks, and identify low-value components.
For example, I led the replacement of a decade-old enterprise data warehouse and over 600 BI assets during the migration of one of the major cable providers in North America to AWS. We transitioned to a cloud-native architecture utilizing AWS and Snowflake, which enabled real-time analytics and reduced reporting latency to under three minutes, all while ensuring uninterrupted daily operations.
We took a phased approach, running modern and legacy IT systems in parallel, supported by automation and real-time monitoring to catch issues early. However, what made it successful was the cross-functional collaboration among IT, network operations, and business teams, working together to ensure a seamless transition.
It wasn’t just a tech upgrade; it was a business transformation delivered with zero downtime.
What strategies do large enterprises use to balance short-term risk with long-term efficiency and scalability in modernization projects?
In large enterprises, particularly in the telecom and media sector, modernization necessitates balancing long-term scalability with avoiding short-term service disruptions. During the modernization of a primary media provider’s billing platform, we extended support timelines while transitioning billing, middleware, and user interface components. This approach ensured the continuity of $400 million in monthly billing operations. The project achieved an annual saving of $1 million in licensing costs and maintained uninterrupted digital ad services.
Success came from strategic planning and execution. Using a reverse and forward engineering framework, we assessed the IT landscape for cost, risk, and business alignment to determine what to modernize, retire, or retain. A phased migration strategy allowed legacy and new systems to run in parallel, preventing downtime.
Risk management was integral from the beginning, utilizing matrices to flag issues such as data sensitivity and bottlenecks. Prioritizing high-impact areas based on business value and urgency was crucial. Automation and SRE practices enhanced observability and minimized manual effort.
But above all, it was about collaboration. We brought together IT, network ops, and business teams early and often to stay aligned and keep things moving. That’s how you modernize at scale without losing momentum or trust.
How do you engage stakeholders across technical and business teams to build cross-functional alignment during system upgrades
When leading system upgrades, establishing cross-functional alignment begins with early engagement and shared ownership. For instance, during a media billing modernization project that I worked on, I facilitated collaborative architecture workshops that included both business and technical teams to ensure alignment on goals, risks, and integration strategies. These efforts resulted in the co-creation of a comprehensive roadmap that balanced AWS cloud adoption with the need to maintain smooth operations of legacy systems.
Similarly, I worked closely with IT, network operations, and vendors such as Samsung and Asurion in a significant wireless initiative for one of North America’s leading cable providers. We defined joint interface agreements and integration points to guarantee seamless functionality across systems. Regular synchronization meetings, transparent documentation, and collaborative design reviews were instrumental in maintaining alignment and advancing the project.
The success of these projects was not solely reliant on technological solutions but on the creation of a shared vision, ensuring every stakeholder understood their role in the transformation’s success.
How can AI and DevOps serve as critical enablers of transformation rather than mere buzzwords?
In recent years, AI and DevOps have attracted considerable interest, yet for many organizations, they remain more theoretical concepts than practical solutions. This discussion aims to demonstrate how we converted these paradigms into concrete, measurable outcomes in extensive telecom modernization projects.
Drawing upon real-world examples from one of the major cable providers in North America, including middleware upgrades, billing platform transformations, and wireless service integrations. I have experienced AI and DevOps’s significant role in reducing delivery cycles, enhancing system reliability, and fostering alignment between business and IT teams.
AI and DevOps expedited our progress by streamlining software development, testing, and deployment. During one of the major cable providers ’ middleware GenAI implementations, we introduced tools such as GitHub Copilot and Windesurf, providing developers with real-time coding suggestions. This accelerated development, improved code quality, and minimized the need for rework. We complemented this with hands-on workshops to facilitate teams’ effective adoption of tools.
Additionally, we established comprehensive DevOps pipelines across projects like Media Billing and Wireless Integration. These pipelines automate processes from code migration to deployment and support microservices on AWS and Google Anthos. This resulted in fewer manual steps, quicker releases, and faster feedback loops, allowing us to deliver updates more reliably and adapt to changes swiftly.
What metrics do you track to measure the success of modernizing legacy systems without disrupting customer service?
I focus on a combination of technical and business metrics to measure the success of modernizing legacy systems while ensuring uninterrupted customer service. The following are some examples of it:
System Uptime and Availability: We managed to keep everything running smoothly without any downtime while modernizing media billing. We did this by adopting microservices and using phased deployments on AWS.
Customer Impact Metrics: Following the launch of a major North American cable provider’s wireless service, we diligently monitored support tickets and service usage. This allowed us to ensure that our customers were satisfied and experiencing no issues.
Data Integrity and Migration Accuracy: To make sure our data stayed consistent during the big data to AWS migration, we relied on AWS Glue and Informatica.
Performance Benchmarks: We tested latency and throughput both before and after the IMS switch migration from legacy switches like Nortel and Cisco to make sure our performance improved.
Deployment Success Rate:During the rollout of genAI tools, we tracked our CI/CD pipeline success. The fact that we had minimal rollbacks showed that our releases were stable.
Adoption and Usability:We looked at user feedback and usage metrics to see how well people were adopting the new PLM Angular UI.
Security and Compliance: We worked closely with InfoSec to enforce encryption and governance in our AWS integrations.
Can you share an example where a phased migration approach helped mitigate operational risk?
During the launch of a major North American cable provider’s wireless service, we adopted a phased migration strategy to integrate new wireless services with our existing systems smoothly. By segmenting the rollout by region and customer type, we effectively minimized risk and ensured continuous service. This careful approach enabled us to validate integrations with key systems, such as Salesforce, Verizon MNO, and Asurion, incrementally, resolve any issues early, and maintain a stable and satisfying customer experience throughout the transition.
Key Focus Areas
- Data Consistency Across Systems: Ensuring synchronized data between legacy and new systems during overlapping operations to maintain integrity.
- Interface Compatibility: Managing dependencies and ensuring backward compatibility with crucial systems like billing, provisioning, and inventory.
- Customer Experience Continuity: Avoiding service disruptions or billing errors during partial migrations to ensure a seamless experience for our customers.
- Testing and Validation: Rigorous testing of APIs, microservices, and message queues in each phase to ensure stability and performance.
- Change Management: Coordinating training and communication across business and technical teams to support phased adoption and ensure everyone is on the same page.
- Security and Compliance: Maintaining encryption, governance, and audit trails across both legacy and modernized components to ensure data protection and regulatory compliance.
How do you encourage a culture of continuous improvement among teams when implementing DevOps practices in a modernization effort?
I firmly embed DevOps principles into the architecture and delivery lifecycle to promote continuous improvement. For instance, during the launch of a major North American cable provider’s wireless service and billing modernization projects, I designed end-to-end CI/CD pipelines, facilitating automated code integration, testing, and deployment. We achieved modular releases and faster feedback loops by encouraging teams to adopt microservices and event-driven architectures.
I regularly conducted retrospectives, facilitated cross-functional workshops, and introduced productivity-enhancing tools such as GitHub Copilot and Windeserf to sustain these improvements. Moreover, aligning DevOps practices with business goals was pivotal; hence, I integrated performance metrics, security compliance, and stakeholder feedback into our delivery roadmap. This structured approach empowered teams to iterate swiftly, learn from each release, and continuously refine both code and processes.
By combining tools with agile delivery practices and consistent stakeholder engagement, we successfully cultivated a mindset of continuous learning and iterative improvement across globally distributed teams.
Photo by NASA; Unsplash
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