Cloud native development is the practice of designing, building and running applications specifically for cloud environments, so they can scale on demand, recover from failures and ship changes often. Instead of one large program moved onto a rented server, a cloud native app is a set of small, independent services, packaged in containers, managed by an orchestrator and released through automated pipelines. This guide explains what that means in practice, what the architecture includes, how the 12-factor principles fit in, and how to decide whether it is the right path for your product.
TL;DR
- Cloud native means an application is built for the cloud from the start, typically as loosely coupled microservices in containers, rather than a legacy system moved to a cloud server.
- The core building blocks are microservices, containers, an orchestrator such as Kubernetes, CI/CD pipelines and DevOps practices.
- The payoff is faster, safer, more frequent releases and easier scaling. The cost is more architectural discipline and a cultural shift in how teams work.
- The Twelve-Factor App is a practical checklist for building services that deploy and scale cleanly.
- Start with a discovery phase, one well-bounded product and a clear deployment pipeline, not a full rewrite.
Table of Contents
- What cloud native development actually means
- Cloud native vs. cloud hosted
- The building blocks of cloud native architecture
- The 12-factor principles in plain language
- Examples of cloud native applications
- Benefits and trade-offs
- How to start: a practical path
- Our perspective
- Building cloud native software with Requestum
- FAQ
- Sources
What cloud native development actually means
Cloud native development is an approach to building, deploying and managing modern applications that take advantage of the scalability, elasticity and distributed nature of cloud computing. Google Cloud describes a cloud native application as one designed from the ground up as a collection of loosely coupled, independent microservices, as opposed to a single monolithic structure.
The Microsoft .NET architecture guide puts the engineering goal well: loosely coupled systems that are resilient, manageable and observable, which let engineers make high-impact changes frequently and predictably with minimal toil.
Two ideas sit under every definition:
- The cloud is the design target, not the destination. The application assumes it will run on infrastructure that can be created, scaled and destroyed by code.
- Change is normal. JFrog notes that cloud native applications are designed to assume frequent change, with support for incremental updates and automated scaling based on real-time demand.
The term also covers the people and process side. The Cloud Native Computing Foundation (CNCF), part of the Linux Foundation, supports open source projects such as Kubernetes, Envoy and Prometheus that many cloud native stacks rely on.
Cloud native vs. cloud hosted
This is the distinction that trips up most business owners. Running your software on a cloud server does not make it cloud native.
A cloud hosted (or cloud based) application is often a legacy monolith that was migrated to the cloud. Google Cloud notes that such apps may use some cloud features but remain inflexible. A cloud native application, by contrast, is built from the ground up for the cloud. An open textbook from OpenStax makes the same contrast: native apps use automation, elasticity and microservices, while hosted apps often work as a single component that lacks the same scalability and agility.
| Aspect | Cloud hosted (lifted and shifted) | Cloud native |
|---|---|---|
| Design origin | Built for on-premises or a single server, then moved | Built for the cloud from day one |
| Structure | Usually one monolithic unit | Independent microservices |
| Scaling | Scale the whole application, often by a bigger machine | Scale individual services up or down automatically |
| Releases | Infrequent, larger, riskier | Small, frequent, automated |
| Failure handling | One fault can take down the whole app | Services are isolated and can self-heal |
Neither is wrong for every case. A stable internal tool may be fine as a hosted app. A product that must grow, change weekly and stay available is where cloud native earns its keep.
The building blocks of cloud native architecture
The Microsoft guide to cloud native applications describes a design built from isolated microservices, each with its own code, data and dependencies, deployed in containers and managed by an orchestrator. Services may use relational or NoSQL datastores or distributed caches, and client traffic routes through an API gateway.
Microservices
Microservices break an application into small, independent, loosely coupled services that can be updated and scaled individually, as Microsoft Azure explains. In a marketplace, for example, search, payments, notifications and user accounts can each be a separate service with its own release cycle. A bug in notifications no longer blocks a checkout fix.
Good service boundaries follow business capabilities, not technical layers. Getting them right is the hardest design decision in the whole project, which is why our own work starts with analysis before code. Our guide to web application architecture covers the checks we run from patterns to deployment.
Containers
A container packages a service with everything it needs to run, so it behaves the same on a laptop, in testing and in production. That consistency removes a whole class of "it worked on my machine" failures.
Orchestration
Containers need something to run them at scale. Orchestration platforms such as Kubernetes automatically manage container lifecycles, with auto-scaling, auto-updating and self-healing, according to Microsoft Azure. When traffic spikes, more copies of the busy service start. When one crashes, it is replaced.
APIs and backing services
Services talk through well-defined APIs, and they treat databases, queues and caches as attachable resources. Clear contracts matter more here than in a monolith, since many teams and services depend on them. An API-first approach, with service level objectives defined early, is the discipline we describe in our API integration strategy.
CI/CD and DevOps
Continuous integration and delivery pipelines build, test and deploy every change automatically. Google Cloud lists CI/CD pipelines and DevOps methodologies alongside microservices and containers as key components. Without them, microservices just become many small things to deploy by hand. If you are setting this up, see our walkthrough on CI/CD pipeline setup.
The 12-factor principles in plain language
The Twelve-Factor App is a methodology for building software-as-a-service applications. It optimizes for portability, agility and minimal divergence between development and production. Its declarative setup, portability and support for continuous deployment and scaling without major changes to tooling or architecture make it a natural fit for cloud native work.
The twelve factors, as listed by Oracle's developer blog, are: codebase, dependencies, config, backing services, build-release-run, processes, port binding, concurrency, disposability, dev/prod parity, logs and admin processes.
Here is what several of them mean for a product owner:
- Codebase. One codebase per service, tracked in version control. In a cloud native setup, each microservice or function has its own repository and CI/CD flow.
- Config. Settings that change between environments (database addresses, keys) live outside the code. This is what lets the same build run in testing and production.
- Backing services. A database or message queue is a swappable resource. Changing providers should be a configuration change, not a rewrite.
- Processes and concurrency. Services are stateless and scale by running more copies.
- Disposability. Services start fast and shut down cleanly, which is what makes auto-scaling and self-healing practical.
- Dev/prod parity. Keep development, staging and production as similar as possible, so releases hold no surprises.
- Logs. Treat logs as a stream of events that a monitoring system collects, so you can see what is happening across dozens of services.
You do not need to follow every factor on day one. They work best as a review checklist: which ones does your current system violate, and which violation hurts most?
Examples of cloud native applications
Cloud native apps are software programs designed for dynamic, cloud-based environments, characterized by modularity and independence. JFrog lists streaming platforms, e-commerce systems, mobile backends and online payment services as common examples.
Those categories map to everyday business products:
- Marketplaces and e-commerce platforms with traffic spikes around promotions and seasonal peaks, where scaling the checkout independently saves money.
- SaaS products that ship weekly and serve many customers on shared infrastructure. See our SaaS application blueprint for how we plan these.
- Mobile backends that must handle unpredictable load and several client apps at once. Our mobile app backend plan covers budget and security.
- Real-time and AI-driven systems, such as streaming and analysis pipelines. One example from our portfolio is an AI solution for analyzing and streaming casino card games in real time.
Benefits and trade-offs
What you gain
AWS lists efficiency, lower costs, availability, scalability and competitive advantage from fast, frequent changes as the main benefits. Red Hat frames the goal as optimizing the speed of building and updating applications while reducing risk and improving quality.
For a business, that translates into:
- Faster feature delivery. Small services and automated pipelines let teams release without coordinating one giant deployment.
- Better availability. Isolated services mean a fault stays local.
- Elastic cost. You pay for the capacity you use at a given moment, rather than sizing for the worst day of the year.
- Room to adopt new technology. Adding an AI service or a new mobile client does not require rebuilding the core.
The Microsoft guide notes that organizations have addressed the fear cycle of the monolith, where releases get rarer and riskier, by adopting a cloud native approach.
What it asks of you
AWS points out that a cultural shift is important, and that is the honest summary of the effort involved. Cloud native works when the team owns services end to end, automates testing and deployment, and monitors production. Plan for these from the start:
- Design skill. Service boundaries, data ownership and API contracts need experienced architects.
- Automation and observability. Pipelines, tests and monitoring are part of the product, not extras.
- Security across many services. Each service and its connections must be secured and tested.
- Team workflow. Distributed systems reward clear documentation and asynchronous communication. Our notes on how to manage remote developers apply directly.
These are all manageable with the right partner and the right sequencing, and they are the reason the architecture phase deserves real time and budget.
How to start: a practical path
You do not need to rebuild everything. A sensible sequence looks like this:
- Define the business goal. Faster releases, handling growth, entering a new channel? The goal decides how far to go.
- Run a discovery phase. Map your domain, users, integrations and risks, and decide which parts benefit from independent services and which can stay simple.
- Choose one bounded product or module. A new product, or the most painful part of an existing one, makes a good first target.
- Set up the delivery pipeline first. Version control, automated tests, container builds and one-click deployment to staging.
- Build services around business capabilities. Keep each with its own data and a clear API.
- Add monitoring and quality gates. Logs, metrics and automated QA tell you whether each release is healthy.
- Expand gradually. Move or add services as the value is proven.
New products can go cloud native from day one. For existing systems, an incremental approach, extracting services one at a time, typically carries less risk than a big-bang rewrite.
Our perspective
In our experience, the teams that get the most from cloud native development are the ones that treat it as a product decision first and a technology decision second. Kubernetes and microservices are tools. The real question is how often you need to change your product, how fast you need to grow, and how much downtime you can accept.
That is why we begin with business analysis and a discovery phase. We map what the product must do, where independent services pay off and where a simpler structure is the smarter choice. Then design, development and QA work as one flow, so the architecture on the diagram is the architecture that ships.
We also see cloud native as the natural foundation for AI. When data pipelines, APIs and services are cleanly separated, adding machine learning models, AI agents or computer vision to a product is an integration task, not a rebuild. Startups and established companies alike get room to grow without paying for a second rewrite.
Whatever you build, insist on automation, testing and observability from the first sprint. They are what turn a modern architecture into dependable releases.
Dmitry
Building cloud native software with Requestum
We build custom web and mobile applications, SaaS platforms, CRM and ERP systems, marketplaces and AI-powered products for businesses across industries. For cloud native projects, we combine business analysis, UI/UX design, development and QA under one team, and we can work as a dedicated team or as a project engagement.
If you are planning a new product, start with our discovery phase and startup development options. If your roadmap includes web platforms, explore our web development services. For SaaS products, see our SaaS development services. If you want to add intelligence to a cloud native product, our AI development services are listed from $30,000 to $60,000 as a one-off engagement. Final scope and cost depend on your project.
FAQ
What is meant by cloud native development?
It means building applications specifically for cloud environments, as a set of loosely coupled services that scale, recover and update independently. Teams pair this architecture with automation, such as CI/CD and container orchestration, to release changes often and safely.
What is an example of a cloud native app?
Streaming platforms, e-commerce systems, mobile backends and online payment services are common examples, according to JFrog. In each, separate services handle functions such as search, checkout or notifications and scale independently when demand changes.
Is cloud native the same as cloud hosted?
No. A cloud hosted application is often a legacy monolith moved onto cloud infrastructure. A cloud native application is designed from the start around microservices, containers and automation, so it can take full advantage of cloud elasticity.
Do I need to follow all 12 factors?
Not on day one. The Twelve-Factor App is a methodology for portable, continuously deployable services. Use it as a checklist, fix the gaps that cause the most pain, such as config handling or dev/prod parity, and improve from there.
Where should a business start with cloud native development?
Begin with a discovery phase that ties architecture to business goals, then pick one bounded product or module and set up the delivery pipeline first. Expanding gradually is usually safer than rewriting a whole system at once.
Sources
- What Is Cloud Native | Google Cloud
- What Is Cloud Native? | Microsoft Azure
- What is Cloud Native? | Microsoft Learn
- Introduction to cloud-native applications | Microsoft Learn
- What is Cloud Native? | JFrog
- Introduction to Cloud-Native Applications | OpenStax
- The Twelve-Factor App
- The Twelve-Factor App | Oracle developers blog
- What is Cloud Native? | AWS
- Understanding cloud-native apps | Red Hat
- Cloud Native Computing Foundation