What is cloud-native infrastructure?

It's building and running the platform for the cloud from the ground up: applications broken into microservices, packaged in containers, orchestrated with Kubernetes, and scaled elastically. The result is infrastructure that scales up on demand, withstands failures, and charges for what you actually use.

How does Luby handle the cloud migration?

We work in controlled waves, with a per-application assessment, a defined strategy for each workload, and a rollback plan. We migrate in stages so as not to interrupt service, measuring cost and performance at each step until the operator safely leaves the legacy data center.

Do you work with containerization and Kubernetes?

Yes. We package applications in Docker containers and orchestrate them with Kubernetes, with an automated deploy pipeline. Each microservice scales and updates independently, which reduces the risk of every release and accelerates the roadmap.

Does cloud-native really reduce infrastructure cost?

Elasticity trades the fixed cost of idle capacity for on-demand consumption: you pay for the real load, scale up at the peak, and scale back in the lull. As an industry benchmark, containerized, elastic workloads can significantly reduce infrastructure cost compared with over-provisioned monolithic environments.

How does platform observability work?

We instrument the platform with unified metrics, logs, and traces, dashboards, and proactive alerts. The operation sees service health in real time, identifies bottleneck and root cause in minutes, and acts before the customer feels any degradation.

Cloud-Native Infrastructure · Telecom Infrastructure that scales on demand

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40%

less infrastructure cost with containerized, elastic workloads (industry benchmark)

The challenge

Legacy infrastructure is expensive and can't keep up with the peak

When the platform can't scale with demand, fixed cost piles up and speed runs out. The gaps we see most in operations:

Monolithic, expensive infrastructure

Idle dedicated servers, heavy licenses, and a legacy data center that eats budget without delivering speed. Fixed cost grows faster than the operation.

Rigid scaling collapses under the peak

A campaign, a launch, or a traffic peak arrives and the platform can't keep up. Provisioning capacity takes weeks, so you either pay for headroom all year or the service goes down at exactly the wrong moment.

Slow deploys stall evolution

Every new release becomes a risky event, with a late-night window and a team on alert. When publishing takes too long, the roadmap slows down and the competitor ships first.

Without observability, everything is a surprise

Without unified metrics, logs, and traces, the failure shows up through the customer before it shows up on the dashboard. The team loses hours hunting for root cause in the dark.

How we implement

From migration to operation, all cloud-native

We apply the cloud, container, and observability practices that keep elastic, resilient platforms running in production.

Cloud migration, without stopping operations

We move legacy workloads to the cloud in controlled waves, with a per-application strategy and clear rollback. The operator gains elasticity and leaves the fixed cost of its own data center behind, without interrupting service.

Containerization and Kubernetes

Every release carries less risk and delivery speeds up, because each component scales and updates independently. We break the monolith into microservices packaged in containers and orchestrated with Kubernetes.

Elasticity and resilience

Capacity follows demand in real time: it scales up at the peak, scales back in the lull, and you pay only for what you use. With autoscaling and high availability, the service withstands failures and holds the peak without going down.

End-to-end observability

You see the platform's health before the customer feels it, with unified metrics, logs, and traces in dashboards and alerts. The team finds bottleneck, cost, and root cause in minutes, not hours.

Technologies

Technologies & partners

Kubernetes

Docker

Terraform

Prometheus

AWS

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Common questions about cloud-native

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