Cloud-Native Application Development: AWS, Azure, and GCP Compared

Choosing a cloud provider is one of the longer-lasting technology decisions a business makes. The application you build today will probably run on that platform for years, and the skills, tools and habits your team forms around it are hard to change later.

This article explains what “cloud-native” means, how Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP) compare in general terms, and how to choose between them. It is written for business owners and product managers in the UAE and GCC who need to make or approve the decision, not for the engineers who will configure it.

One note before starting: all three are capable, mature platforms. For most business applications the right answer depends more on your own situation than on any feature one provider has and another lacks.

What cloud-native means

Moving an existing application onto a rented server in someone else’s data centre is cloud hosting. Cloud-native goes further: the application is designed from the start to use what the cloud is good at. Four ideas sit at the centre of it.

Containers

A container packages an application together with everything it needs to run, so it behaves the same on a developer’s laptop, in testing and in production. Docker is the most familiar tool for building containers. Kubernetes, an open-source system that originated at Google, is widely used to run and coordinate many containers at once. Large applications are often split into smaller independent services (microservices), each in its own container.

Managed services

Instead of installing and patching your own database, message queue or search engine, you rent one that the provider operates. Your team spends its time on your product, and the provider handles backups, updates and failover. The trade-off is less control and a closer tie to that provider.

Automation

Servers, networks and databases are described in configuration files (often called infrastructure as code) and created by scripts, not by hand. New versions of the application are tested and released through an automated pipeline, usually referred to as CI/CD. This makes releases repeatable and reduces the errors that come from manual steps.

Scaling

The system adds capacity when demand rises and removes it when demand falls. A retailer can absorb a Ramadan or White Friday peak without paying for that capacity all year. Some workloads go a step further with serverless functions, where code runs only when triggered and you manage no servers at all.

How the three providers compare

The descriptions below are general and reflect how each platform is commonly perceived. Service catalogues change often, so treat this as orientation and confirm specifics with the provider.

AWS

AWS was the earliest of the three to offer cloud services at scale and is known for the breadth of its catalogue. There is an AWS service for almost every need, often more than one. It has a very large community, a deep pool of experienced engineers and a wide choice of third-party tools. The flip side of that breadth is complexity: newcomers can find the number of options and the billing structure hard to navigate.

Microsoft Azure

Azure’s main appeal is how well it fits with other Microsoft products. Organisations already using Microsoft 365, Windows Server, SQL Server, .NET, Dynamics or Microsoft’s identity tools often find that sign-in, permissions and licensing carry across with less friction. Azure is also well regarded for hybrid arrangements, where some systems stay on your own premises and others move to the cloud. Teams without a Microsoft background sometimes find its conventions less intuitive.

Google Cloud Platform

GCP is especially respected for data analytics and machine learning. BigQuery, its data warehouse, is a common reason for choosing it, and its managed Kubernetes service benefits from Google’s long involvement with that technology. Many developers find its console and tooling clean and consistent. Its catalogue is generally seen as more focused than the other two, and in some markets there are fewer engineers and local partners with deep experience of it.

Comparison at a glance

Factors for choosing

Work through these in order. The first two settle the question for many organisations.

• Existing skills. The platform your developers and IT staff already know will be faster and safer to launch on. Retraining a team costs time, and mistakes made while learning can affect security.
• Data residency. Some sectors, such as government, healthcare and financial services, have rules about where data is stored and processed. Establish your obligations with your legal or compliance adviser first, then confirm directly with each provider which regions and services meet them. Do not rely on a blog post, including this one, for that answer, because availability differs by service and changes over time.
• Integrations. List the systems the application must connect to: ERP, CRM, payment gateways, identity and single sign-on, analytics. A provider that connects natively to what you already run removes a layer of work.
• Workload type. A transactional e-commerce platform, a reporting system fed by large data sets and an internal line-of-business tool each lean on different services.
• Support. Compare the paid support plans, response commitments and the availability of local partners who can help in your time zone, and in Arabic if your team needs it.
• Commercial terms. Existing enterprise agreements, start-up credit programmes and committed-use discounts can shift the balance. Ask each provider for a like-for-like estimate based on your own expected usage.

Avoiding lock-in

Lock-in means that moving away from a provider would be so costly that you are effectively unable to. Some degree is unavoidable and often worth it: managed services save real effort. The aim is to choose where you accept it.

Practical steps include packaging the application in containers so it can run anywhere, preferring open-source technologies such as PostgreSQL, MySQL, Redis and Kubernetes over provider-specific equivalents where the difference is small, and describing infrastructure with a tool that works across providers, such as Terraform. Keep your business logic separate from provider-specific code, and make sure you can export your data in a standard format.

Running the same application across two or three clouds at once (multi-cloud) is sometimes proposed as the answer. For most small and mid-sized businesses it adds more cost and complexity than it removes. Being portable is usually enough.

Cost control habits

Cloud bills grow quietly. A few habits, applied from the first month, keep them predictable.

1. Set budgets and spending alerts in the provider’s billing tools on day one.
2. Label every resource with its project, environment and owner so you can see what each part of the business costs.
3. Switch off development and test environments outside working hours.
4. Review server sizes regularly and reduce any that are consistently under-used.
5. Use automatic scaling so capacity follows demand.
6. Move older files and backups to cheaper storage tiers.
7. Consider committed-use or reserved pricing only once usage is stable and well understood.
8. Give one named person responsibility for reviewing the bill each month.

Watch for charges that are easy to overlook, such as data transferred out of the cloud, idle storage volumes and forgotten test databases.

How HelloPixels can help you choose and build

HelloPixels designs, builds and maintains applications on all three platforms, so our advice starts from your requirements and not from a preferred vendor. You can read more about our work with AWS, Microsoft Azure and Google Cloud. We can assess an existing system, plan a migration or build a new cloud-native application, with cost depending on scope and quoted in AED after a consultation.

If you would like a second opinion on your cloud plans, get in touch with our team.