Applications tied to one server
Local file storage, in-memory sessions and hard-coded paths make horizontal scaling and server replacement painful or impossible.
Cloud & DevOps · Application Development
Cloud application development built around managed services
We write software that uses the cloud on purpose (managed databases, queues, object storage and functions) so your team spends its time on features rather than on servers.
What is Cloud Application Development?
Cloud application development is the design and coding of software intended to run on cloud platforms, using the platform's managed services instead of reproducing them on self-managed servers. A cloud-native application is typically stateless, packaged in containers or functions, stores files in object storage, uses a managed database and is deployed through an automated pipeline. The aim is software that scales, recovers and ships changes with less manual operations work.
Putting an application on a cloud server does not make it a cloud application. Software written for one machine keeps uploaded files on local disk, holds sessions in memory, runs scheduled jobs from a crontab and assumes the database is on localhost, so it cannot run a second copy, cannot survive a server replacement and cannot take advantage of anything the platform offers. Building cloud-native from the start avoids an expensive rewrite later.
Why running on a cloud server isn't enough
Undirected service sprawl
Cloud catalogs list hundreds of services. Choosing too many creates an application that is hard to run locally, hard to debug and expensive to operate.
Lock-in worries
Teams fear that using any proprietary managed service will trap them, so they avoid useful ones, or use them everywhere without an exit plan.
Costs that grow with usage in surprising ways
Per-request pricing, data transfer and chatty function calls can make a successful feature unexpectedly expensive.
Our Cloud Application Development service
Cloud-native application design
Service boundaries, data model, state handling and which managed services each component uses, documented before development starts.
Backend and API development
Stateless APIs in Node.js or Python, designed to run as multiple instances behind a load balancer, with configuration supplied through the environment.
Serverless functions and event processing
Functions for scheduled jobs, webhooks, file processing and queue consumers where event-driven execution genuinely suits the work.
Containerized services
Docker images for services that need longer-running processes, deployed to a managed container service or Kubernetes when the scale justifies it.
Managed data and storage
Managed PostgreSQL, MySQL or MongoDB, object storage for files, caches and message queues, configured with backups and access controls.
Pipelines and environments
Automated build, test and deployment to separate development, staging and production environments from the first sprint.
Included capabilities
- Stateless services that scale horizontally
- Object storage for uploads and generated files
- Background jobs through queues
- Scheduled and event-triggered functions
- Twelve-factor configuration via environment
- Structured logging and tracing hooks
- Health checks and graceful shutdown
- Local development that mirrors the cloud setup
- Infrastructure defined as code with the app
What Cloud Application Development changes for your business
Less infrastructure to babysit
Patching databases, rotating disks and scaling queues become the provider's job instead of your team's.
Scale when it is needed
Stateless services can run more copies under load and fewer when traffic drops.
Faster, safer releases
Automated pipelines and identical environments make deployments routine instead of risky events.
Deliberate portability
Containers and standard databases keep the core of the application movable, with provider-specific services isolated behind clear interfaces.
Where it makes the biggest difference
SaaS platforms
Multi-tenant products where many customers share one deployment and load varies through the day.
Customer portals and mobile backends
APIs serving web and mobile clients, with file uploads, notifications and authentication handled by managed services.
Data and document processing
Uploaded files, imports or webhooks processed asynchronously by queue workers or functions instead of blocking users.
Internal business systems
Line-of-business tools that need to be reliable and accessible from multiple offices without an on-premises server room.
How a cloud-native build runs
Pipelines and environments come first, so every feature ships the same way.
Scope
Product goals, users, expected load and integration points, captured as a prioritized backlog.
Architect
Service and data design, choice of managed services, and a running-cost estimate for the expected usage.
Set up foundations
Repositories, environments, CI/CD pipeline and infrastructure as code before feature work begins.
Build iteratively
Short development cycles with working software deployed to staging for review at the end of each one.
Test
Automated unit and integration tests plus load testing of the paths that will see the most traffic.
Launch
Production deployment with monitoring, alerting and a rollback path in place.
Operate and improve
Usage and cost reviewed after launch, with the architecture adjusted as real traffic patterns emerge.
What it connects to
Cloud Application Development
- Managed databases on AWS, Google Cloud or Azure
- S3-compatible object storage
- Message queues and pub/sub
- Serverless function platforms
- Payment gateways
- Email and SMS providers
- Identity providers and OAuth
- GitHub Actions or GitLab CI
Built with
Choosing a compute model
| Criterion | Serverless functions | Managed containers | Virtual machines |
|---|---|---|---|
| Scaling | Automatic, per request | Automatic or rule-based | Manual or scripted |
| Operational effort | Lowest | Moderate | Highest |
| Long-running processes | Limited by execution time limits | Yes | Yes |
| Cost pattern | Pay per invocation; cheap when idle | Pay for running containers | Pay for the machine around the clock |
| Good for | Webhooks, scheduled jobs, spiky events | APIs and services with steady traffic | Legacy software, special OS needs |
Security, quality and scale
No secrets in code
Credentials come from the platform's secrets manager or environment, never from the repository.
Scoped service permissions
Each function and service gets an identity with only the permissions it needs.
Private data tier
Databases and caches sit on private networks, reachable only by the application.
Scalability under load
Load tests before launch identify the component that will saturate first, so it can be sized or redesigned.
What working with us looks like
Developers who also run infrastructure
Our team builds the application and operates the cloud underneath it, so design decisions account for both.
Managed services where they pay off
We use a managed service when it removes real operational work, not because it is new.
Cost estimated with the design
You see an expected running cost before development commits you to an architecture.
Full product stack
The same company can deliver the web front end, the mobile app and the cloud backend that serves both.
What it costs
Fixed-price packages with the scope written down, paid stage by stage. Your project goes live once it's fully paid.
Related services, technologies and industries
Sources and further reading
Official documentation and guidance if you want to read more about this topic.
Cloud Application Development: questions we hear most
What makes an application cloud-native?
A cloud-native application is built to run as replaceable, horizontally scalable instances that rely on managed services for state. In practice that means no local file storage, configuration from the environment, a managed database, automated deployment and health checks the platform can act on.
Should we build our application on serverless?
Serverless suits event-driven, intermittent or spiky work, but it is not the best fit for every workload. Long-running processes, constant high traffic or heavy local development needs often run better and cheaper in containers. Many applications we build use both: containers for the main API and functions for background events.
How do you avoid vendor lock-in?
We keep the core of the application portable (containers, standard databases such as PostgreSQL, and infrastructure as code) and isolate provider-specific services behind small interfaces. Some lock-in is a reasonable trade for less operational work; the aim is to choose it knowingly.
Which cloud provider do you build on?
We build on AWS, Google Cloud, Azure and simpler providers such as DigitalOcean, depending on the client's needs and existing accounts. The application design is largely the same; the managed services used and their pricing differ.
Can you make our existing application cloud-native?
Yes, usually in stages. Typical first steps are moving file storage to object storage, externalizing sessions and configuration, containerizing the application and adding an automated pipeline. That work is often done as part of a cloud migration or legacy modernization project.
Next step
Plan a cloud-native build
Share what the application needs to do and the load you expect. We'll propose an architecture, the managed services involved and a rough running cost.