Cloud-Native Has a Definition that Most "Cloud" Core Systems Don't Meet

First part of a series of articles that tries to cut through the fluff in insurance core system marketing and to align terms for core system buyers.  

For a few years already, the word "cloud-native" has been omni-present in insurance technology marketing. Nearly every core system vendor claims it, but very few fully meet the definition.  

It is what happens when a technical term becomes an RFP criterion: everyone claims it, and the burden of verification shifts to the buyer. 

What cloud-native actually means 

Let’s start with the definition by negation. What cloud-native does not mean: "runs in the cloud". Where software runs is a hosting decision.  

Cloud-native is about how the software is built and operated. The Cloud Native Computing Foundation definition is concrete: 

Cloud native practices empower organizations to develop, build, and deploy workloads in computing environments […] at scale in a programmatic and repeatable manner. It is characterized by loosely coupled systems that interoperate in a manner that is secure, resilient, manageable, sustainable, and observable. Cloud-native technologies and architectures typically consist of some combination of containers, service meshes, multi-tenancy, microservices, immutable infrastructure, serverless, and declarative APIs […]. 

In short, a cloud-native application is abstracted away from bare-metal hardware constraints but deeply integrated with the programmable capabilities of the cloud. It is containerised, composed of services, deployed through declarative infrastructure-as-code and automated CI/CD, leaning on managed cloud services rather than hand-operated ones. The point is to exploit what the cloud is good at: elastic scalability, self-healing, observability, and so on. 

Which yields a one-sentence test: an application that runs on cloud virtual machines (VMs) but remains monolithic, manually operated and unable to scale elastically and cost-effectively is not cloud-native. It is “cloud-hosted”. Or another simple classification: if a core system requires your team to manually deploy, patch, and self-manage standard infrastructure component (such as databases, message queues, or clustering tools), even when the cloud provider offers mature and fully managed equivalents, it can hardly be called cloud-native.  

Wrapping a decade-old legacy monolith inside a container is just a "fat container" anti-pattern. It shifts the hosting address, not the architectural paradigm. 

Here is our analogy: cloud-native is living in a luxurious smart hotel and using all its tech, facilities and services. Lifting your old application onto cloud VMs and operating everything by hand is pitching an old tent inside that hotel room, then sleeping in it. The hotel name sounds impressive. The living arrangement has not changed. 

How the word gets abused 

As most core systems are far from cloud-native, it attracts a specific style of marketing, with different patterns to watch for. If you read "cloud edition”, “cloud-hosted”, “cloud-based” or “cloud-ready” that is usually a clear giveaway. It’s a relabelled monolith: the same codebase you could have installed in your own data centre few years ago, now running on the vendor's VMs with a managed-services contract on top. If the architecture didn't change, the only thing that really moved to the cloud is the invoice.  

To its credit, Socotra, one of the few core vendors to build cloud-native from day one besides Peak3, has been calling this pattern out for years under the label "legacy cloud". 

Then there are companies that claim to have cloud-native solutions even though their architecture does not support it. Particularly, if the company and solution have been around for decades, you should be cautious.  

Rearchitecting a legacy solution to be cloud-native is an incredibly expensive multi-year endeavour, in practice requiring a deep refactoring of the underlying framework and core technical components. This is a transformation rather than a feature upgrade. Small core system vendors cannot afford it. Large vendors don’t want to afford it. Hiding behind imprecise (or disingenuous) marketing terms is usually easier. 

What to probe as a buyer 

As mentioned upfront: if everyone claims it, the burden of verification shifts to the buyer. If you are in the business for a new core system, we recommend you ask at least the following questions (and insist on being shown rather than told): 

1. Scalability. How does the system deal tenfold or hundredfold traffic spikes? Does the platform leverage cloud-native elastic constructs (such as Kubernetes pod auto-scaling, serverless databases, or managed streaming data services) to dynamically scale within seconds? Or does it rely on legacy VM resizing that requires manual intervention? 

2. Self-healing. When a microservice pod, a Kubernetes VM node, or an entire Availability Zone (AZ) experiences a critical failure, can the system seamlessly and automatically fail over without manual intervention? If the answer involves a phone call to an engineer, it isn't self-healing. 

3. Deployment. How often does this solution deploy to production? Is a release a zero-downtime rolling/blue-green update, or a maintenance window with business interruption? 

4. Reproducibility. Can an identical production or staging environment be automatically set up from scratch using IaC (Infrastructure as Code) tools like Terraform? Does that take hours, or a quarter? 

5. The codebase. Is the "cloud" product the same codebase as the on-premise product? If not, what is different? 

6. Multi-cloud. If you migrate the core system to a different cloud provider, does it maintain its native and managed service capabilities? Or does it degrade into a legacy lift-and-shift deployment? How do you support cross-cloud disaster recovery for enhanced resiliency? 

At Peak3, we know that a genuinely cloud-native vendor will enjoy these questions. The reaction is itself a signal. 

Why this matters in the agentic AI era 

AI agents are the most demanding users a core system has ever had. They may arrive in bursts no human workforce ever produced. They call in real time and at high concurrency, and they multiply whenever the business finds a new use for them.  

That is why elastic scalability, statelessness and self-healing are needed. Agents raise the bar for the core. A cloud-hosted monolith can rent all the infrastructure it wants; it still cannot serve agentic operations at scale. Cloud-native stops being a marketing buzzword the day AI agents become users at scale. 

The word “cloud-native” has a definition. Please hold every vendor to it, including us.