Backend Development Services

What backend development covers

The backend is everything users do not see: the APIs that apps call, the business rules, the database, authentication, background jobs, file storage, integrations with other systems and the infrastructure it all runs on. A well-built backend is secure, fast, easy to change and observable when something goes wrong.

Backend technologies we use

What we build

Backend architecture principles

• Modular monolith first — simpler and faster to build; split into services when there is a clear reason.
• Stateless services — easy to scale horizontally in containers or serverless.
• Secure by default — validated input, parameterised queries, least-privilege access and secrets management.
• Observable — structured logs, metrics and tracing from day one.

Designing data models that last

The database schema usually outlives every other part of an application. Frameworks are upgraded and front ends redesigned, but data structures persist for a decade or more. We spend time on the data model early: clear entities and relationships, constraints that prevent invalid data, sensible naming, indexes for the queries you will actually run, and audit fields that record who created and changed records.

We plan for change too. Migrations are version-controlled and repeatable, large data changes run in batches without locking tables, and reporting needs are considered before they become performance problems. A well-designed data layer makes every later feature faster to build and every report easier to trust.

Scaling a backend step by step

• Measure first — profiling and tracing show where time is actually spent before anything is changed.
• Optimise queries and indexes — often the largest and cheapest improvement.
• Cache — frequently read data in Redis or at the edge.
• Move slow work to queues — emails, exports and integrations handled in the background.
• Scale horizontally — stateless services behind a load balancer, plus read replicas for heavy reporting.
• Split services — only when a component has clearly different scaling or team needs.

Backend frameworks compared

Every framework below is production-proven. The differences that matter in practice are ecosystem, team familiarity, built-in features and how naturally each one fits your workload.

A reference backend architecture

For most products we start with a modular monolith: one deployable application, organised into clear modules (billing, accounts, orders and so on) that communicate through defined interfaces. It is simpler to build, test and operate than microservices, and the module boundaries make it straightforward to extract a service later if a part of the system genuinely needs to scale or deploy independently.

When independent scaling or team autonomy is a real requirement, we move to microservices deliberately, one service at a time.

Performance and security fundamentals

• Measure before optimising — tracing and slow-query logs usually point to a handful of database queries or external calls that cause most of the delay.
• Cache with intent — cache expensive reads close to the user and invalidate explicitly, rather than caching everything and hoping.
• Push slow work to queues — the request should return quickly while reports, emails and syncs run in the background.
• Least privilege everywhere — database users, cloud roles and API keys get only the permissions they need.
• Validate every input at the API boundary, and use parameterised queries so injection is not possible by construction.
• Rate limiting and audit logs on authentication, payments and admin actions.

Moving off a legacy backend

Older back ends — classic ASP, early PHP, unsupported Java or .NET Framework versions — often still run critical processes. Rewriting everything at once is risky. We prefer the strangler approach: put an API or routing layer in front of the old system, build new functionality in the modern stack, and move existing features across one at a time until the old code can be switched off. Users see continuous improvement instead of a big-bang cut-over.

See legacy software modernization for how we plan these migrations, or hire backend developers to strengthen your own team.

APIs that other teams enjoy using

A back end is only as useful as its API. We design APIs contract-first: the schema is agreed and documented before implementation, so front-end, mobile and partner teams can work in parallel against mocks. Consistent naming, pagination, filtering and error formats make every endpoint predictable. Breaking changes go into a new version with a deprecation period, never silently into an existing one.

Documentation is generated from the code (OpenAPI for REST, introspection for GraphQL), so it cannot drift out of date. Read more about API development.

Observability from day one

Production problems are much cheaper to solve when you can see what happened. Every back end we deliver includes structured logs with request IDs, metrics for latency, throughput and error rates, distributed tracing across services and queues, and alerts tied to user-facing symptoms rather than raw server statistics. Dashboards show the health of each module, and runbooks explain how to respond to the most likely incidents.

This also makes performance work evidence-based: instead of guessing, the team can see which endpoint, query or third-party call is slow and fix that first.

Testing strategy for back ends

We keep business rules covered by fast unit tests, verify database queries and integrations with tests that run against real PostgreSQL or MySQL in containers, and protect public APIs with contract tests so changes cannot break mobile apps or partners unexpectedly. A small set of end-to-end tests exercises the most important flows through the whole system. Tests run on every pull request, and a change cannot be merged while they fail.

For integrations with third parties — payment providers, CRMs, shipping carriers — we use their sandboxes in automated tests where available, and recorded responses where not, so the build never depends on someone else’s uptime.

Choosing a backend language

All of these are good choices; the best one depends on your team, product and integrations. AI-heavy products lean towards Python; Microsoft-centric companies towards .NET; teams sharing code with a JavaScript front end towards Node.js; content and commerce-heavy businesses towards PHP and Laravel. See also API development.

Explore more in Software Development Technologies We Use.