"Their ability to translate my vision into a fully functional MVP in just 8 weeks was outstanding. Highly recommend!"
Eric M.
Founder at Intrinsic Sales
Cloud Application Development Services
RaftLabs develops new SaaS products, internal tools, APIs, and real-time applications on AWS, Azure, or GCP. The first release pairs one core workflow with managed infrastructure, deployment automation, observability, and handover, so the product and its operating model are scoped together rather than separated into later DevOps work.
Bring the problem, the current workflow, or the existing code. We reply with a practical next step within one business day.
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The brief
Good software decisions begin with the constraint, not a list of features or a preferred technology.
Is a new product being scoped without anyone owning its deployment, scaling, recovery, or cloud cost model?
Does every proposed architecture assume a different cloud service and make vendor estimates impossible to compare?
Plain answer
Cloud application development builds a new product around managed cloud services, deployment automation, observability, and explicit operating ownership. RaftLabs develops SaaS, internal tools, APIs, and real-time systems on AWS, Azure, or GCP. A focused first release pairs one core workflow with managed infrastructure, deployment automation, observability, and handover.
What to remember
A product can run on a major provider and still depend on manual deployments, one fragile server, hidden environment differences, and an engineer who knows how to restart it. Moving those problems into a cloud account changes the invoice, not the operating model.
The first release should prove both halves of the system: a workflow users value and an application the team can deploy, observe, recover, and change without reconstructing its infrastructure from memory.
Relevant delivery record
These figures describe shipped products with cloud or real-time demands. They are not standard performance guarantees for a new application. The ULT Movies and PSi case studies state their own evidence and delivery context.
Choose migration for an existing workload, or a configured platform when the requirement is already standard.
One user workflow can define a first release and its acceptance evidence.
Product and technical owners can decide data, integration, security, and recovery trade-offs.
The team wants application code, infrastructure, delivery, and observability scoped together.
The only goal is to move an existing application without changing its product boundary.
A standard SaaS tool already covers the workflow and custom differentiation is weak.
No owner can approve architecture, provide domain access, or operate the released system.
It is whether a new cloud application is the right answer at all. We use four possible recommendations before discussing a development scope.
Choose a maintained product when it handles the core workflow and the remaining gaps can be solved with configuration, a connector, or a small process change. Paying for cloud software you do not have to maintain is often the better trade.
Keep the existing product when users still get value from it and the code can be understood safely. Start with evidence: where the code lives, how the data is organized, what is tested, which outside services it depends on, who can access what, and how updates go live.
Own cloud software when the workflow shapes margin, customer experience, speed, or a product customers pay for. Start with one complete path and the system connections that path cannot work without.
Do not turn a changing policy into permanent software. Stabilise the rules, name the workflow owner, and measure the cost of the current process before paying for a product.
Not sure which path is yours? Bring it to a 30-minute call. Leave with the answer in writing.
First release
Build the interface, API, business rules, background work, and data path needed for one user outcome. Keep optional modules outside the first acceptance boundary until people can test the core loop.
Choose functions, containers, databases, queues, storage, identity, and networking from actual workload needs. Record where a managed service reduces operations and where it would create cost or lock-in without enough benefit.
Define infrastructure in code, separate staging and production, automate tests and deployment, keep secrets outside repositories, and make rollback a rehearsable path rather than a sentence in a launch plan.
Add structured logs, useful service measures, alerts with owners, backup and restore checks, and runbooks for likely failures. The operating team receives code, access, diagrams, decisions, and known limitations.
| Cloud application development | Cloud migration | |
|---|---|---|
| Starting point | New product or deliberate rebuild | Existing application and data |
| Primary decision | What should the first operable product be? | How should the current workload move safely? |
| Architecture freedom | High, within product and team constraints | Limited by dependencies and cutover risk |
| Acceptance | User workflow plus operating evidence | Parity, reconciliation, cutover, and rollback evidence |
| Price basis | Scoped to the first release | Scoped to the workload |
Choose this page when product and platform decisions must be made together. Choose cloud migration services when current behaviour, data, and continuity are the main constraints. Use SaaS development when multi-tenancy, billing, tenant isolation, and commercial onboarding are the defining problems.
Delivery
Four steps connect user value to the system that must run it.
Name the user workflow, traffic, data, integrations, security needs, recovery expectations, and team that will run the first release. Record acceptance evidence and the modules deliberately left out.
Select provider and managed services from workload evidence, then document cost assumptions, alternatives, and reversibility. Avoid designing for traffic or complexity the first release does not need.
Deliver the workflow, infrastructure code, environments, pipeline, tests, and telemetry through reviewable increments. Demonstrate working software in a real staging environment rather than presentation-only progress.
Test behaviour, load assumptions, failure paths, deployment, recovery, and handover before planning the next module. Record residual risks and give the operating team access before launch.
Scope and price
Begin with one complete workflow and the operating path required to release it.
Cloud use, model or communications APIs, licensed data, and other third-party fees are separate unless the written proposal includes them.
Starting investment
Starts at $10000
Modules, integrations, data work, real-time behaviour, recovery, and security controls move the estimate. After a 30-minute call, you get a written build, buy, repair, or wait recommendation plus first-phase direction. Free, whether or not you build with us.
Product and platform share one scope
The first phase states its workflow, infrastructure, deployment, monitoring, recovery, client dependencies, acceptance evidence, and exclusions.
The client owns the system
Application code, infrastructure code, environments, access, diagrams, and runbooks remain in the client's accounts and repositories.
Related delivery paths
Cloud migration services
Move and validate an existing workload when continuity, data reconciliation, cutover, and rollback matter most. It preserves more of the current product boundary.
Azure consulting
Resolve provider-specific architecture, Microsoft identity, cost, or one-workload questions in Azure.
DevOps services
Fix a focused release, infrastructure, monitoring, recovery, or production operating constraint.
Proof
Three-year average engagement. Founders and operators describing the work in their own words. No marketing varnish.
What distinguished RaftLabs from other providers was their fantastic ability to build real-time engagement-based products.
Georgina D.
CEO & Co-Founder, People Supported Technologies
"Their ability to translate my vision into a fully functional MVP in just 8 weeks was outstanding. Highly recommend!"
Eric M.
Founder at Intrinsic Sales
Work with us
We will review users, product, data, traffic, integration, recovery, and ownership assumptions, then propose the smallest cloud release worth testing.
Cloud application development creates a new software product with cloud deployment and operation designed alongside its user workflow. The scope may use managed databases, queues, functions, containers, storage, or identity where they fit. It should also include environments, deployment automation, monitoring, recovery, access, cost assumptions, and a team handover.
Cloud migration moves and validates an existing workload, often preserving some current architecture to manage cutover risk. Cloud application development builds a new product or deliberate rebuild around a fresh operating boundary. If the main problem is moving servers, data, and identity without disruption, use cloud migration rather than this page.
The choice follows existing skills and contracts, Microsoft or Google dependencies, data and AI services, regional requirements, expected traffic, service maturity, and acceptable operating burden. We document the decision and alternatives. We do not claim one provider is always cheaper or technically better for every workload.
Security and agreed technical controls can be included in architecture, implementation, testing, and evidence collection. Compliance obligations still depend on the customer's data, configuration, contracts, and operating process. RaftLabs does not provide legal advice, certify compliance, or promise that using a certified cloud service makes the resulting application compliant.
Neither, by default. Serverless fits spiky, event-driven, short-lived work: pay per request, near-zero operations. Containers fit consistent, predictable, high-volume services: portable, always warm, steady cost. Most real systems mix both, because the question is per workload, not per company. The common failure is platform bias: forcing stateless serverless onto stateful apps, which leads to latency and debugging nightmares. Auto-scaling that has not been load-tested fails when it is needed most.
Ask for the bill model before the architecture. A credible vendor proposes billing alerts, a right-sizing review, and infrastructure-as-code in a repository you own, and can explain the monthly cost curve: what the system costs at ten users versus ten thousand. Operational overhead grows at scale despite the cloud's promise; modelling that growth before you feel it is the vendor's job.
A focused first release with one core workflow is priced after the workflow, integrations, data, recovery, and operating boundary are defined. Product modules, integrations, real-time behaviour, data migration, multi-region recovery, sensitive-data controls, and unusual load increase scope. Cloud consumption and third-party service fees remain separate unless the proposal says otherwise.