Tata Consultancy Services is one of the world's largest IT services and consulting firms, with a global workforce serving clients across financial services, insurance, retail, healthcare, and government. When TCS takes on a major enterprise delivery program — a core system modernization, a cloud migration, or a digital transformation initiative — they often bring in specialized partner firms to handle specific technical workstreams that require deep expertise in modern engineering practices. That is exactly how our partnership with TCS began.
"CoderDesign operates at the quality bar we set for our Tier 1 banking clients. Their engineers embedded into our delivery structure seamlessly and took full ownership of the cloud migration workstream from day one." — Arvind Mehta, Delivery Director, TCS Canada Financial Services
We have been a technology delivery partner for TCS Canada since 2023, contributing to outsourced engineering workstreams for their financial services clients. This case study covers our largest engagement to date: building cloud migration tooling and automation for a major Canadian bank's infrastructure modernization program. Due to NDA requirements with both TCS and the end client, we cannot name the bank or share specific internal metrics. What we can share is the nature of the technical work, the engineering approaches we used, and the general outcomes. This is how our full-stack development, AI automation, mobile engineering, and SEO capabilities contributed to the success of this engagement.
How Enterprise Outsourcing Actually Works
When people hear "outsourcing" they think of offshoring entire projects to the lowest bidder. That is not what this is. TCS operates a sophisticated partner ecosystem where specialized firms like ours handle specific technical workstreams within larger programs. TCS manages the client relationship, program governance, and overall delivery accountability. We bring deep technical expertise in areas where speed and specialization matter more than headcount.
For this banking engagement, TCS was managing a three-year digital transformation program with over 200 consultants across multiple workstreams: core banking modernization, regulatory reporting, digital channels, and infrastructure migration. Our team was brought in specifically for the infrastructure migration workstream because TCS needed engineers who had hands-on experience building cloud migration tooling, not just consultants who could create migration roadmaps in PowerPoint.
The Staffing Model
We embedded a team of six engineers into TCS's delivery structure. They reported to TCS's delivery manager, attended daily standups with the broader program team, used the client's Jira instance and Confluence knowledge base, and followed TCS's delivery methodology (Agile with two-week sprints, formal sprint reviews with the client's CTO office). From the client's perspective, our engineers were indistinguishable from TCS's own team. This is what good partnership outsourcing looks like — seamless integration, shared accountability, and no finger-pointing when things get difficult.
The Challenge: Migrating Hundreds of Legacy Applications to Cloud
The bank had several hundred applications running across on-premise data centers. These ranged from modern Java and Node.js microservices to legacy batch processing systems, middleware layers, and vendor-packaged applications with limited documentation. The mandate was to significantly reduce data center costs within a defined timeline while maintaining zero downtime for customer-facing services and meeting OSFI (Office of the Superintendent of Financial Institutions) regulatory requirements for cloud deployment of financial data.
Application Discovery and Classification
The first challenge was that nobody had a complete, accurate inventory of what was actually running. The bank's CMDB (Configuration Management Database) was outdated and listed applications that had been decommissioned years ago while missing others that had been spun up by individual teams without going through formal IT processes. We built a custom discovery tool using AWS Application Discovery Service combined with network flow analysis that scanned the on-premise environment and mapped every running process, its dependencies, network connections, and data stores. This tool identified dozens of applications that were not in the official inventory, including several that processed customer PII without proper data classification labels.
The Six Migration Strategies
Not every application can be lifted and shifted to the cloud. We classified each application into one of six migration strategies based on its architecture, dependencies, compliance requirements, and business criticality.
Rehost (lift and shift) was used for the largest group — applications already running on Linux VMs with no hard dependencies on physical hardware, which moved to EC2 instances on AWS with minimal changes. Replatform was used for applications that needed minor modifications — updating database connection strings to point to RDS instead of on-premise Oracle, switching file storage from NAS to S3, or updating service discovery to use cloud-native DNS. Refactor was required for applications that needed significant architectural changes to work in the cloud, including breaking monolithic applications into containers and updating authentication to use the bank's cloud IAM system. Repurchase applied to applications where a SaaS equivalent existed that met the bank's requirements. Retain covered applications that could not move to cloud due to regulatory constraints, mainframe dependencies, or vendor licensing restrictions. Retire applied to applications identified as redundant or unused during the discovery phase.
What We Built: The Cloud Migration Platform
Rather than migrating applications one at a time through manual processes, we built a migration platform that automated and standardized the entire workflow. This platform became the backbone of the migration program and is now being reused by TCS for other banking clients.
Migration Pipeline Engine
We built an orchestration engine in Python and Terraform that automated the end-to-end migration process for each application. The pipeline handled: provisioning the target cloud infrastructure based on the application's resource profile, configuring networking (VPCs, subnets, security groups, transit gateway connections back to on-premise), deploying the application using the appropriate strategy (VM image for rehost, container image for replatform, CI/CD pipeline for refactor), running automated validation tests to verify the application worked correctly in the cloud environment, configuring monitoring and alerting (CloudWatch, Datadog integration), and updating DNS and load balancer configurations to route traffic to the cloud deployment.
Each migration went through a four-stage process: deploy to cloud (parallel running with on-premise), validate with synthetic traffic, gradual traffic shift (10%, 25%, 50%, 100%), and decommission on-premise resources after 30-day stability period. This process was codified in the pipeline so that every migration followed the same rigorous steps regardless of which engineer was executing it.
Compliance and Security Automation
Banking regulations in Canada require strict controls over where financial data is stored, who can access it, how it's encrypted, and how access is audited. OSFI's B-13 guideline specifically covers cloud computing and outsourcing for federally regulated financial institutions. We built compliance automation that enforced these requirements at the infrastructure level.
Every cloud resource was automatically tagged with data classification labels (public, internal, confidential, restricted) based on the application's data profile. Resources handling restricted data were automatically deployed to dedicated tenancy instances in the Canada (Central) AWS region with customer-managed KMS encryption keys. Network policies automatically prevented any data from routing through non-Canadian regions. IAM policies were generated from templates that enforced least-privilege access based on the application's security tier. All infrastructure changes were logged to an immutable audit trail in S3 with CloudTrail, and any manual changes outside of the pipeline triggered immediate alerts to the security operations team.
Application Dependency Mapping
The most technically challenging part of the project was handling application dependencies. Application A might depend on Application B's database, which depends on Application C's message queue, which depends on a mainframe batch job that runs at 2 AM. If you migrate Application A to the cloud without accounting for these dependencies, it breaks in production.
We built a dependency graph visualization tool using Neo4j that mapped every application's upstream and downstream dependencies based on the network flow data from our discovery tool, plus manual interviews with application owners. This graph was used to determine migration ordering — you cannot migrate Application A until its critical dependencies are either already in the cloud or accessible via the hybrid network connection. The tool also identified circular dependencies (A depends on B, B depends on C, C depends on A) that required careful planning to break.
AI-Powered Migration Intelligence
We built several AI-powered tools that significantly accelerated the migration program.
Automated Code Analysis for Refactoring
For the 43 applications that needed refactoring, manually analyzing the codebase to identify cloud-incompatible patterns would have taken months. We built an AI code analyzer using GPT-4 that scanned application source code and configuration files to identify: hardcoded IP addresses and hostnames that needed to be replaced with cloud service endpoints, file system dependencies that needed to move to S3 or EFS, session state stored on local disk that needed to move to Redis or DynamoDB, database queries that used vendor-specific syntax incompatible with RDS, and authentication mechanisms that needed to integrate with the bank's cloud IAM. The tool generated a refactoring report for each application with specific code changes required, estimated effort, and risk level. This reduced the assessment phase for refactoring candidates from an average of 3 weeks per application to 3 days.
Predictive Risk Scoring
Not every migration goes smoothly, and the consequences of a failed migration in banking are severe — potential customer impact, regulatory scrutiny, and reputational damage. We built a predictive risk scoring model that analyzed each application's characteristics (age, technology stack, number of dependencies, data sensitivity, change frequency, test coverage) and assigned a migration risk score. Applications with high risk scores got additional validation steps, longer parallel running periods, and dedicated rollback procedures. The model proved highly accurate at identifying migrations that would encounter issues, allowing the team to allocate extra attention where it mattered most.
Intelligent Runbook Generation
Each migration required a detailed runbook — a step-by-step document that operations teams followed during the migration window. Writing runbooks manually for 340 applications was not feasible. We built an AI system that generated migration runbooks automatically based on the application's profile, migration strategy, dependencies, and compliance requirements. Each runbook included pre-migration checks, step-by-step migration procedures, validation tests, rollback procedures, and escalation contacts. Operations teams reviewed and approved each runbook before execution, but the AI generation saved approximately 4,000 hours of documentation work across the program.
The Mobile Command Center
Migration windows often happened during weekends and evenings to minimize customer impact. TCS's delivery managers and the bank's IT leadership needed real-time visibility into migration progress from anywhere, not just from their laptops in the office.
We built a React Native mobile application that served as a migration command center. The app showed real-time status of active migrations, health metrics for recently migrated applications, alerts and incidents requiring attention, approval workflows for migration gate checks, and communication channels for the migration team. This app was used by 45 stakeholders across TCS, the bank's IT organization, and our team during every migration window. The bank's CIO specifically called out the mobile command center as a differentiator in the program's quarterly review.
Edge Cases That Nearly Derailed the Project
Enterprise cloud migrations are full of surprises. Here are the edge cases that taught us the most.
One legacy application written in PowerBuilder (a technology from the 1990s) had no source code available. The original vendor had gone out of business, and the bank's developers had been maintaining it through configuration changes only. We could not refactor it, and it could not run in a container. We ended up creating a custom VM image that replicated the exact on-premise server configuration (down to the specific Windows Server 2008 patch level) and ran it on a dedicated EC2 instance with enhanced monitoring. This was not elegant, but it worked and kept the migration timeline on track.
Another application had a hard dependency on a physical hardware security module (HSM) for cryptographic operations. AWS CloudHSM was a potential replacement, but the application's cryptographic library used proprietary APIs that were not compatible with CloudHSM's PKCS#11 interface. We built a lightweight proxy service that translated between the legacy HSM API and CloudHSM, allowing the application to move to the cloud without modifying its cryptographic code. This proxy became a reusable component in the migration toolkit.
Results: Delivered on Time, Under Budget
Due to NDA requirements, we cannot share specific numbers from the bank's internal reporting. The general outcomes of the program were:
- The majority of in-scope applications were successfully migrated to cloud within the planned timeline
- Data center cost reductions met the targets set in the original business case
- Zero customer-facing outages during migration windows
- Average migration time per application significantly reduced through pipeline automation
- OSFI compliance requirements met across all cloud-deployed applications
- The migration platform and tooling we built has since been adopted by TCS for use on additional client engagements
- AI-powered code analysis and runbook generation saved thousands of hours of manual work across the program
- The mobile command center app was adopted as standard tooling for TCS infrastructure migration programs in Canada
Why TCS Partners with Teams Like Ours
Large consulting firms like TCS, Infosys, Wipro, and Accenture have massive global workforces, but they often need specialized partners for specific technical capabilities. The technology landscape moves faster than any single organization can keep up with. When TCS needs a team that can build production-grade Terraform modules, write custom Kubernetes operators, implement AI-powered code analysis tools, or build React Native mobile applications on a tight timeline, they bring in partners who do that work every day rather than training internal teams from scratch.
For us, partnering with TCS gives us access to enterprise-scale projects that we would not win as an independent firm. The bank in this case study would never have hired a boutique development shop directly for a program of this size and sensitivity. But through TCS, we get to work on the most technically challenging problems in enterprise IT while TCS handles program management, client relationships, and governance.
This model works because both sides bring genuine value. TCS brings enterprise relationships, delivery methodology, and global scale. We bring deep technical expertise, modern engineering practices, and the ability to build custom tooling that accelerates delivery. The client gets the best of both worlds.
How We Can Help Your Enterprise
Whether you are a large consulting firm looking for a specialized technology delivery partner, or an enterprise that needs engineering help with cloud migration, application modernization, or digital transformation, our team brings the same quality and ownership we demonstrated in this TCS engagement.
Our capabilities include full-stack web and platform development using React, Next.js, Node.js, Python, and Terraform. We build enterprise mobile applications for operations teams, field workers, and executive dashboards. Our AI and automation team builds intelligent tools for code analysis, document processing, and workflow automation. And our digital marketing team helps professional services firms build their online presence and attract clients through organic search.
If you have a technical challenge that requires experienced engineers who can integrate into your delivery team and take full ownership of results, book a consultation. We will review your requirements, understand your delivery model, and give you an honest assessment of how we can help.