Cloud-Native Application Development

PS3G provides cloud native development for applications that are meant to be run in the cloud, not merely hosted there: services packaged as containers, deployed by pipelines, scaled by demand, observed from the inside and recoverable without a person logging into a server. That includes a founder who wants a product that scales without a rebuild, a growing company whose single application has become a bottleneck for every team that touches it, and a platform or product group inside a larger organization standardizing on Kubernetes. We build the services, the pipelines and the platform underneath them on Azure, AWS or Google Cloud, and we say plainly when a well-built monolith is the better answer.

Cloud-Native Application Development: what we build and for whom

Cloud-native is a set of practices rather than a product: small deployable units, declarative infrastructure, automated delivery, horizontal scaling, and observability built in. It pays off when an application changes often, is worked on by more than one team, or has load that varies. Our cloud native application development work takes four forms.

• New applications built cloud-native from the start. A modular codebase packaged as containers or functions, with infrastructure as code, a pipeline and observability in place before the first feature, so the project never has a “productionize it” phase.
• Microservices development. Decomposing an application into services where there is a reason to, with clear boundaries, asynchronous messaging where it fits, and the platform work that makes many services manageable.
• Kubernetes development and platforms. Clusters on AKS, EKS or GKE with the ingress, secrets, policy, scaling and deployment tooling that internal teams need, plus the application changes to run well on them.
• Serverless development. Functions and serverless containers for APIs, event processing, scheduled work and integrations, where there is nothing to patch and cost follows usage.

Cloud-native is the wrong choice more often than the industry admits. A small application maintained by one or two developers is usually better as a single deployable with a good pipeline. Microservices without a platform team become a distributed monolith with more failure modes. If your application’s problem is old code rather than architecture, our application modernization service covers the options that come before a re-architecture, and we will recommend the one that fits.

What the service covers

Cloud application development at PS3G covers the services, the platform and the delivery system. The table lists the typical work and the tools we reach for across the three clouds.

Type of work	What it looks like	Typical tools (Azure / AWS / Google Cloud)
Containerized services	Stateless services with health checks, configuration from the environment, structured logs, graceful shutdown	Docker, .NET, Java, Node.js or Python; Container Apps / ECS and Fargate / Cloud Run
Kubernetes platforms	Cluster setup, namespaces and policy, ingress and TLS, secrets, autoscaling, GitOps deployment	AKS / EKS / GKE; Helm, Kustomize, Argo CD or Flux, cert-manager, external-secrets
Microservices and messaging	Service boundaries, APIs and contracts, events and queues, sagas, idempotency, retries and dead-letter handling	Service Bus and Event Grid / SQS, SNS and EventBridge / Pub/Sub; Kafka where it fits
Serverless	Functions and serverless containers for APIs, events and schedules, with cold-start, timeout and concurrency handled by design	Azure Functions / Lambda and Step Functions / Cloud Functions and Cloud Run
CI/CD and infrastructure as code	Build, test, scan, deploy pipelines; environments as code; progressive delivery	GitHub Actions or Azure DevOps, Terraform, Bicep or CDK, Argo Rollouts
Observability	Traces, metrics and logs correlated across services; dashboards; alerting on what users feel	OpenTelemetry; Azure Monitor / CloudWatch / Cloud Monitoring; Grafana, Prometheus

How we work

Cloud-native projects fail when the platform is built before the first service needs it, or when services are split before anyone knows where the boundaries are. Our process keeps both tied to real workloads.

1. Assessment. The application or product, the teams that will own it, the change frequency, the load profile, the integrations, and the cloud and security standards. For an existing application, a read of the code, deployment and failure history, written up as risks and a target architecture.
2. Architecture note. Deployable units and their boundaries, synchronous versus asynchronous communication, data ownership per service, the platform (serverless, containers or Kubernetes) and the delivery pipeline. We keep it to the decisions that are expensive to reverse.
3. Walking skeleton. One service from code to container to pipeline to a running environment with traces, metrics, logs, secrets and autoscaling, before the features arrive. The platform exists because a workload needs it.
4. Increments. Two-week deliveries with demos, reviewed pull requests, contract tests between services, and progressive rollouts so a bad release reaches a few users rather than all of them.
5. Hardening and handover. Load tests at expected and peak volumes, failure drills for the broker, the database and a node, recovery tests, runbooks and documentation, then handover to your team or a managed-services agreement under defined SLAs.

Team and stack choices

A lead architect in the United States owns the design and your weekly conversation; application and platform engineers at our India delivery center build with overlapping hours; a QA engineer from our testing center of excellence tests each increment, including the failure cases. We prefer serverless containers over Kubernetes unless the estate needs a cluster, managed messaging over self-run brokers, and the cloud’s native services over third-party equivalents unless portability is a stated requirement. The pipeline and infrastructure work is shared with our DevOps service.

Describe the application and how it is deployed today and we will reply with a written assessment proposal.

Where this fits with the rest of your systems

Cloud-native services almost never replace an estate at once. They grow at its edges: a new product line, a customer-facing API, a part of a monolith that needs to scale on its own, while the systems of record stay where they are.

Because PS3G’s core engineering practice is .NET and the Microsoft stack, much of our cloud-native work is ASP.NET Core in containers alongside Java, Node.js and Python services on the same platform, with one identity provider, one message broker and one observability pipeline across all of them. .NET is a strong cloud-native platform: small container images, fast startup, built-in health checks and OpenTelemetry support, and first-class homes on Azure Container Apps and AKS, on ECS and EKS, and on Cloud Run and GKE. The cloud solutions page describes our vendor-neutral stance across the three providers.

The common first step from a monolith is the strangler pattern: route one capability to a new service, let the monolith keep the rest, and repeat only where there is a reason. Our guide on monolith to microservices covers when that is worth doing and when it is not.

Examples by organization size

These are typical engagement shapes, not named clients.

• A founder with a product to launch. A fixed-scope build of a modular application deployed as a few serverless containers with a managed database, a pipeline, observability and budget alerts, so the product scales with demand and the first engineering hire inherits a working delivery system rather than a server.
• A growing company with a bottleneck application. A dedicated team for several months that extracts the two or three capabilities that block the most teams into services on a managed container platform, adds messaging between them and the monolith, and leaves the rest alone on purpose.
• A platform group inside a larger organization. A Kubernetes platform on the organization’s chosen cloud with the guardrails, GitOps deployment, policy and observability that internal product teams need, built inside its security and change-control rules, with the first few services migrated as proof and the platform handed to the internal team.

Engagement models

• Fixed-scope project: a defined deliverable and price for a service, a platform or an extraction phase.
• Dedicated team or staff augmentation: application and platform engineers inside your team on a monthly basis.
• Managed services: we run, patch, scale, monitor and improve your services and platform under defined SLAs.
• Advisory: an architecture review, a monolith-to-services assessment or a platform decision.

How we start: a first conversation, a short assessment, a written proposal.

Why PS3G for cloud-native work

We build and run our own products, so we operate containers, pipelines and cloud platforms every day for ourselves and feel the cost of every architectural shortcut. We have built software for more than a decade from Wilmington, Delaware and our India delivery center, with Microsoft-certified and open-source-certified engineers on the same teams, across Azure, AWS and Google Cloud. Our DevOps, testing and security practices are part of each delivery team rather than separate departments.

Related services

• All services: everything we build, test, run and advise on.
• Cloud solutions: our vendor-neutral view across Azure, AWS and Google Cloud.
• DevOps: the pipelines, infrastructure as code and operations under every cloud-native build.
• Application modernization: the options that come before, or instead of, a re-architecture.
• API development and integration: the contracts between services and with the systems that stay put.

Guides on this topic

• Monolith to Microservices: When It’s Worth It and How to Do It
• What Is a DevOps Pipeline? Stages, Tools and a Starter Setup

Frequently asked questions

What does cloud-native development mean in practice?

Applications built to be run in the cloud rather than merely hosted there: packaged as containers or functions, deployed by pipelines from infrastructure defined as code, scaled by demand, observed through traces, metrics and logs, and recoverable without manual intervention. It is a set of practices that apply on Azure, AWS and Google Cloud alike, and they can be applied to a monolith as well as to microservices.

Do we need microservices?

Only if more than one team needs to change and deploy parts of the application independently, or if parts of it have very different scaling needs. A single well-structured application with a good pipeline serves most organizations better than a dozen services with no platform team. We assess first, and we often recommend a modular monolith with one or two extracted services rather than a full decomposition.

Kubernetes or serverless: which should we use?

Serverless containers and functions for most workloads, because there is no cluster to run and cost follows usage. Kubernetes when you have many services, an internal platform team, specific networking or stateful requirements, or a need to run the same platform across clouds or on-premises. We recommend one in the assessment and design so a move from serverless to Kubernetes is possible later if growth requires it.

Can .NET applications be cloud-native?

Yes, and well. ASP.NET Core produces small, fast-starting container images with built-in health checks, configuration from the environment and OpenTelemetry support, and it runs on every managed container and Kubernetes platform across the three clouds. Our cloud-native builds use whichever languages fit, often Node.js, Python, Java and .NET services side by side on the same platform.

How do you keep cloud-native costs under control?

By designing for it: scale-to-zero platforms for variable workloads, right-sized requests and limits on Kubernetes, managed messaging and databases instead of self-run ones, budgets and alerts from the first environment, and a cost review as part of every hardening phase. Observability also shows which services actually carry load, so capacity goes where it is used.