Every large-scale enterprise eventually discovers an uncomfortable truth: scale and dependency rarely coexist. The larger a platform grows, the more entangled itsEvery large-scale enterprise eventually discovers an uncomfortable truth: scale and dependency rarely coexist. The larger a platform grows, the more entangled its

Engineering for Independence: Migrating from Proprietary Infrastructure to Open Cloud Solutions

5 min read

Every large-scale enterprise eventually discovers an uncomfortable truth: scale and dependency rarely coexist. The larger a platform grows, the more entangled its systems become, databases hardwired to one another, deployment pipelines chained to specific vendors, operations slowed by invisible constraints. At first, these systems appear efficient. Over time, they turn into barriers.

Independence, once dismissed as an idealistic pursuit, has become a marker of engineering maturity. It is what allows teams to innovate without waiting for permission, to evolve infrastructure without rewriting the business.

Saumya Tyagi, a seasoned Staff Software Engineer at Coupang, and a Senior IEEE member with over a decade of experience building distributed systems for global technology enterprises, describes independence not as a project goal but as a survival mechanism. Having led large-scale migrations across cloud environments and data platforms, his focus has been on freeing organisations from architectures that age faster than their ambitions.

“Large systems don’t fail suddenly, they fail quietly, through years of design debt no one notices. Our job is to keep rewriting the parts that success made fragile.”

That line captures a principle more teams are learning to live by: resilience begins with the freedom to change.

Redefining Scale Through Ownership

For years, enterprises measured scale by the size of their databases or the traffic their systems could process. Today, scale is measured by independence, how easily components evolve without pulling down the rest of the stack.

Saumya learned this first-hand while leading a migration for a global e-commerce platform’s digital payments system. The architecture had grown around a single, tightly coupled database serving multiple services across regions. Every schema update risked an outage. Every new feature added more fragility.

The re-architecture began not with code, but with ownership. Each business capability, issuance, redemption, and settlement, was separated into its own microservice, complete with isolated data stores and clearly defined boundaries. The shift was surgical: sixteen terabytes of data moved to distributed NoSQL environments without downtime. Cost dropped by nearly 40%, transaction capacity doubled, and development velocity followed.

“I’ve seen teams double infrastructure before doubling clarity. That’s the real scaling problem, when you grow compute faster than accountability.”

That shift in perspective turned scale from a hardware problem into a clarity problem. Once ownership was explicit, growth became predictable.

Designing for Exit from Day One

Independence is never granted; it is engineered. Saumya emphasises that systems capable of evolving are those built with exits already in mind. That design philosophy guided his work on large-scale deprecation and replatforming efforts for consumer-facing infrastructure.

Instead of an abrupt migration, his approach involved dual-write mechanisms, transaction replays, and shadow reads, techniques that validated data integrity while live traffic continued to flow. Each phase could be reversed if anomalies appeared. Every decision was observable and measurable. The migration completed without user disruption.

Later, while working on a major connectivity platform, Saumya applied the same principles to help transition a legacy operations suite from proprietary tooling to an independent cloud environment. The result was a leaner, faster system that reduced dependency costs by 30% and shortened deployment cycles by nearly half.

“A migration is never about moving data, it’s about proving that your boundaries are real. If they aren’t, you’ll find out the hard way halfway through the rollout.”

Those smaller reversals accumulate into a form of architectural resilience, where adaptation is routine, not reactionary.

When Autonomy Becomes a Cost Strategy

What begins as a technical aspiration eventually reveals itself as a financial strategy. Vendor dependence inflates cost invisibly, through licensing, idle capacity, and engineering drag. Independence reverses that logic.

Industry studies have shown that organisations moving from proprietary databases to open, cloud-native solutions consistently report significant savings in licensing and maintenance. AWS’s official engineering report revealed how one of the world’s largest consumer divisions eliminated thousands of Oracle instances, saving millions in annual infrastructure and licensing fees.

Supporting analyses by TelcoDR and Support Revolution further underscore the scale of this transformation: tens of petabytes migrated, performance gains recorded, and cost efficiency achieved through open cloud adoption.

In Saumya’s experience, the re-architected digital payments system reduced infrastructure spend by more than 40% while cutting manual operations by nearly a third. Release cycles accelerated, not because engineers worked faster, but because their tools finally let them.

“When we mapped cost to ownership, the results were brutal. The services that shouted the loudest about scale were also the ones wasting the most capacity.”

Once teams could see the trade-offs, design decisions became economic decisions. Efficiency stopped being accidental.

Sustaining Autonomy at Scale

Independence does not end when the migration does. In fact, that is where it begins. The next frontier for engineering teams lies in sustaining autonomy, building architectures that remain portable across clouds, compliant under regulation, and adaptive to growth.

Saumya’s current work focuses on this ongoing discipline. The challenge, he notes, is not avoiding dependencies altogether but managing them with foresight. Systems must be observable, replaceable, and context-aware, capable of evolving without requiring reinvention.

“Every dependency eventually becomes invisible. The trick is to notice it before it starts deciding how fast you can move.”

In practice, that means designing abstractions that outlive vendors, data models that can move without refactoring, and infrastructure that values optionality over convenience. Independence, in the end, is not about separation. It is about choice, the ability to decide when, how, and why to change.

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