Modernizing Applications with Kubernetes: A Practical Guide to Cloud-Native Development

There is a point in the lifecycle of a successful application when the architecture that supported its early growth begins to constrain what comes next. Traffic increases. Release cycles become shorter. New services are introduced. Different components develop different resource requirements. Infrastructure that was once straightforward to manage becomes increasingly difficult to scale and maintain. Adding more servers can address capacity, but it does not necessarily address the underlying architectural problem.

Application modernization is about addressing that problem at the application level: changing how workloads are packaged, deployed, scaled and operated so the architecture can respond more effectively to changing requirements.

Containers and Kubernetes are two technologies that support this transition. Containers provide a consistent unit for packaging applications and their dependencies, while Kubernetes provides the orchestration layer for managing containerized workloads across a cluster but modernization is not simply a matter of moving an existing application into containers or deploying it on Kubernetes. The architecture, deployment model and operational requirements all need to be considered.

When an Application Outgrows Its Original Architecture

Many applications begin with relatively simple infrastructure. A workload may run on a small number of virtual machines, with an application server connected to a database and a few supporting services. As demand grows, additional compute resources can often accommodate the increase. Eventually, the application itself may become more complex. Different components may experience different traffic patterns. A new service may require significantly more computation than an existing one. Development teams may need to deploy individual features without redeploying the entire application. Recovery requirements may also become more demanding.

At this stage, infrastructure becomes more than a capacity problem.bThe organisation needs a way to manage workloads independently, automate repetitive operations and make changes without creating unnecessary disruption. This one of the problems cloud-native architecture is designed to address.

From Infrastructure-Centred to Workload-Centred Architecture

Traditional application architectures often revolve around the servers on which applications run. Cloud-native architectures shift the focus towards the application workload.

The application and its dependencies can be packaged into containers, creating consistent deployment units that can run across supported computing environments. Containers also provide isolation between workloads and make it easier to replicate applications when additional capacity is required. This changes the deployment model.

Instead of treating a server as the primary unit of deployment, teams can manage application workloads as portable units that can be deployed, replicated and scaled according to requirements. That becomes particularly useful for applications built around microservices.

Containers as a Foundation for Modernization

Containerisation can be an important step in modernising an existing application. A legacy application can, where appropriate, be refactored into containerised services rather than remaining tightly coupled to a particular server environment. Nobus identifies application modernisation as one of the use cases for its cloud containers, including refactoring legacy applications into containerised microservices. The benefit is not simply portability.

Containerised workloads can support more consistent development, testing and production environments. They can also integrate into CI/CD workflows, allowing teams to automate parts of the build, test and deployment process.

However, containerisation introduces another operational question. How do you manage containers when there are no longer just a few of them?

Where Kubernetes Fits

Kubernetes provides the orchestration layer for containerised applications. Rather than manually managing individual containers, teams define the desired state of their workloads and Kubernetes works to maintain that state across the cluster.

For example, an application may require multiple running instances. Kubernetes can schedule workloads across available nodes, replace failed containers and distribute workloads as part of the orchestration process. Nobus Kubernetes Engine supports automated deployment, scaling and load balancing, self-healing and declarative configuration.  This becomes increasingly valuable as an application moves from a small number of containers to a distributed production environment. The architecture becomes less dependent on manually managing individual machines and more focused on defining how workloads should operate.

Designing for Scale

Scaling is one of the practical reasons organisations adopt Kubernetes but scaling does not always mean increasing the size of a single machine. Kubernetes environments can support horizontal scaling, where additional nodes are added to the cluster, as well as vertical scaling, where the CPU and memory specifications of nodes are increased. Nobus supports both approaches through its Kubernetes cluster management capabilities. 

At the application level, this provides room for workloads to respond to changing demand. Consider a digital platform experiencing a significant increase in traffic during a product launch. Rather than permanently provisioning infrastructure for the highest expected demand, the architecture can be designed around workloads that can scale as requirements change. The objective is not simply to run more infrastructure. It is to make infrastructure respond more effectively to the application.

Modernisation Does Not Automatically Mean Microservices

Microservices are often discussed alongside containers and Kubernetes, but they should not be treated as mandatory components of every modernisation project. Breaking an application into smaller services can allow individual components to be developed, deployed and scaled independently. It can also support more targeted changes as the application evolves but distributed architecture introduces additional operational requirements. Services need to communicate reliably. Dependencies need to be understood. Monitoring becomes more important. Data management becomes more complex. Failure can occur between services rather than only within individual application components.

For that reason, modernisation should begin with the application’s requirements rather than with a predetermined technology stack.Kubernetes can orchestrate the architecture. It cannot determine whether the architecture is appropriate.

The Operational Layer

A production Kubernetes environment requires more than compute resources. A cluster consists of control-plane and worker nodes, with the control plane responsible for scheduling, health checks and API access while worker nodes run application containers. Nobus also supports high-availability configurations with multiple control-plane nodes. Networking, storage, access and monitoring also become part of the operating model.

Nobus Kubernetes clusters include monitoring through Grafana, providing visibility into CPU, memory and node health. Cluster nodes are private and can be accessed through a bastion host, while the Kubernetes API is accessed through the cluster’s API VIP.

These operational capabilities are important because application modernisation changes not only how software is deployed but also how it is observed and managed.

Managed Kubernetes vs Self-Managed Kubernetes

Once Kubernetes becomes part of the architecture, organisations also need to decide how much of the platform they want to operate themselves. A self-managed deployment gives engineering teams control over the Kubernetes installation and its components. It also means taking responsibility for tasks such as provisioning nodes, installing Kubernetes components, configuring networking, monitoring the environment and maintaining the cluster. Nobus provides documentation and support for organisations that prefer this approach.

Managed Kubernetes provides another model.

Instead of building the entire orchestration layer internally, organisations can consume Kubernetes as a managed cloud service and concentrate more of their engineering effort on the applications running on the platform. The choice ultimately depends on the organisation’s technical requirements, operational capabilities and desired level of control.

Modernising on Nobus Cloud

Nobus Cloud provides a Kubernetes environment for organisations developing, modernising and operating containerised applications. Nobus Kubernetes Engine supports cluster-based deployment with control-plane and worker nodes, high-availability configurations, monitoring and horizontal and vertical scaling.

Kubernetes workloads can also sit alongside other Nobus Cloud infrastructure services, allowing organisations to build application environments around their actual workload requirements rather than adopting a single infrastructure model. For teams modernising existing applications, this creates a path from traditional infrastructure towards a more containerised and orchestrated operating model.

Modernisation Is an Architecture Decision

Application modernisation should not be measured by how many containers an organisation deploys or whether Kubernetes appears somewhere in the architecture. The more useful measure is what changes for the application.

• Can teams release changes more consistently?
• Can workloads scale according to demand?
• Can failed application instances be replaced automatically?
• Can different components evolve without unnecessarily affecting the entire system?
• Can the engineering team operate the environment without infrastructure becoming the dominant concern?

These are architectural questions before they are technology questions. Kubernetes provides the orchestration capabilities to support many of these requirements. Containers provide a consistent packaging model. Cloud infrastructure provides the compute, networking and storage resources beneath them. Together, they can provide a foundation for modern application development but the technology should follow the application’s requirements.

Modernise where the architecture creates constraints. Orchestrate where the workload demands it. And build an application environment that can evolve as the product.