Embedded Goes Cloud Native: The Next Disruption

By Paul Miller, CTO, Wind River

Over the last forty years, embedded systems have quietly powered the world. They operate our factories, enable transportation systems, manage energy grids, and increasingly control autonomous machines. Yet the way we build embedded software has barely changed in decades: firmware is baked into an image, fused tightly with the hardware, deployed once, and rarely touched again.

That era is ending.

The pressures shaping modern products - cyber-security, connectivity, regulatory accountability, data-driven features, and now artificial intelligence - are incompatible with the traditional “ship-and-forget” development mindset. Connected devices are no longer standalone endpoints. They are active participants in distributed systems. They generate data, interact with other systems, and must evolve after deployment.

In short, embedded systems are becoming cloud-native.

This shift has little to do with increasing compute power or adding more memory. It has everything to do with adopting the architectural and operational patterns that revolutionized cloud software over the last decade: modularity, automation, observability, remote lifecycle management, and continuous software evolution. These principles are now being applied — sometimes boldly, sometimes quietly — inside devices that must meet strict real-time and even safety-critical requirements.

For an industry long defined by predictability and stability, this marks a tectonic change.

The end of “ship and forget”

Historically, embedded products were designed around an immutable lifecycle. The software was finalized before manufacturing. Updating a deployed device required physical access, specialized equipment, or the risky process of field flashing firmware. Any change — even a minor bug fix — forced teams to retest the entire system, because the software was built as a single indivisible block.

This model worked when devices had no external exposure. It fails the moment a device connects to a network.

Today, products must remain secure, resilient, and current for years or even decades. Vulnerabilities are discovered constantly, supply-chain dependencies change, and customers expect new features long after deployment. In connected markets, a product that cannot be updated becomes a liability.

Executives who once priced software as a one-time cost are now recognizing that lifecycle management is the product. The value is no longer captured at the point of sale - it accrues over time.

The companies who succeed in the next decade will be the ones that treat deployed devices not as finished goods, but as evolving software platforms.

Cloud-native principles arrive at the edge

When cloud-native methods emerged, many assumed they would remain confined to data centers. The idea of using containers, orchestration, or CI/CD workflows where milliseconds matter felt irresponsible, even dangerous. Embedded engineers believed — with good reason — that real-time performance, safety certification, and deterministic behavior demanded a fundamentally different approach.

The surprise of the last few years is that these assumptions are being overturned.

Modern embedded platforms now support clean separation between infrastructure and application logic. They enable updates without tearing apart the system. They allow developers to package software into discrete components — each isolated, independently testable, and remotely deployable.

This is more than a technical breakthrough. It is an operational one.

Instead of thinking in terms of “firmware,” companies are thinking in terms of services. Instead of planning a massive update every eighteen months, they plan incremental enhancements delivered continuously. Instead of redeveloping infrastructure for every new product, they build a platform once and reuse it across dozens of variants.

Cloud-native thinking reframes embedded systems not as static artifacts, but as living, updateable members of a distributed fleet.

Continuous evolution replaces monolithic releases

In the old model, software development was synchronized to hardware development. A new hardware revision triggered a software refresh. When the hardware stopped evolving, software stopped evolving too. The result was predictable: software innovation slowed to the pace of mechanical design.

Cloud-native embedded development breaks that dependency.

Software and hardware are no longer tied together. The platform that runs the device becomes stable and consistent, while the applications running on top of it can change frequently. This decoupling allows teams to innovate faster, respond to customer needs, and experiment with new capabilities without disturbing the underlying control logic.

One automotive executive described this shift succinctly:

“The hardware drives first revenue, the software drives future revenue.”

When the platform is stable and updateable, product teams can deliver new value continuously. A feature that wasn’t ready at launch can be rolled out later. A capability that customers weren’t originally willing to pay for can be offered as a subscription. A system that once required a technician to update can receive improvements over the air — securely, automatically, and reversibly.

Security becomes continuous, not episodic

Nothing has accelerated the need for cloud-native practices faster than cybersecurity. Embedded systems that once operated behind firewalls are now directly connected - sometimes to public networks, sometimes to other devices that are not under your control.

A single unpatchable vulnerability can become a multimillion-dollar liability.

Regulatory pressure, particularly in critical infrastructure and transportation, is pushing manufacturers toward provable, auditable security workflows. Governments increasingly require evidence of secure updates, SBOM tracking, and traceability.

The cloud-native model fits this reality because it makes updating expected, not exceptional.

Continuous updating turns cybersecurity from a one-time engineering phase into a normal operational rhythm. Instead of hoping nothing goes wrong, teams are equipped to respond when it inevitably does.

The security conversation shifts from prevention to resilience.

Toward a platform strategy

The most strategically significant impact of cloud-native embedded development is not modularity, automation, or security — it is reuse at organizational scale.

Companies that adopt cloud-native thinking are no longer building “software for a product.” They are building software platforms that support many products. The platform becomes the foundation for multiple hardware variants, reducing time to market and eliminating duplicated engineering.

Executives often describe this transformation as the difference between “products built by teams” and “teams building a portfolio.”

This shift requires executive commitment, because it often challenges current organizational structure. But the payoff is enormous: faster releases, higher margins, and durable differentiation.

Edge AI will make cloud-native unavoidable

A fascinating accelerant is the emergence of AI at the edge. When models run locally—inside a robot, a manufacturing cell, or a vehicle—updates become constant. Models improve, data drifts, and optimizations are needed long after the product is deployed. AI workloads demand telemetry, fleet-level coordination, secure updates, and rollback control.

AI makes the old embedded approach collapse instantly.

When a product contains AI, software must evolve as fast as the model does. Cloud-native embedded architecture is the only practical foundation for rapid iteration, controlled rollout, and safe field updates.

In many organizations, artificial intelligence is becoming the forcing function that finally triggers the move to cloud-native embedded.

What leaders should take away

A cloud-native embedded device is not defined by whether it runs containers or interacts with cloud services. It is defined by how it behaves after deployment.

When a customer buys the device, are they purchasing a frozen artifact or an evolving platform?

When a vulnerability is discovered, does the organization react or recover?

When a market opportunity emerges, can software be delivered in weeks or must it wait for the next hardware cycle?

The answers to these questions separate the companies positioned for the next decade from those still anchored in the last one.

Closing perspective

Embedding cloud-native practices into real-time systems used to sound impossible. Today, it sounds inevitable. The companies that embrace this shift are discovering that it improves not only how they build products but how they monetize them, support them, and differentiate them over time.

The future of embedded is not defined by more powerful processors or more memory. It is defined by the realization that software lives on after the product ships, and that managing its evolution is a core capability — perhaps the most strategic capability — of modern product companies.