Catalog
concept#Architecture#Platform#Integration#Security

Backend

The backend is the server-side application layer that provides business logic, data storage, and integration endpoints. It encapsulates APIs, authentication and data processing independently of the frontend.

The backend is the server-side application layer that implements business logic, data storage, and integration points.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

Relational and NoSQL databasesIdentity and access providers (OAuth, SSO)Message brokers and streaming platforms

Principles & goals

Clearly defined API contracts and versioning.Loose coupling and high cohesion between components.Observability, monitoring and measurable SLAs.
Build
Team, Domain, Enterprise

Use cases & scenarios

Compromises

  • Insecure interfaces or poor authentication.
  • Scaling bottlenecks in databases or synchronous calls.
  • Technical debt from lacking modularization.
  • Clearly version contracts between services.
  • Implement idempotent interfaces and clear error handling.
  • Integrate observability from the start (tracing, metrics, logs).

I/O & resources

  • architecture and API specifications
  • data models and integration endpoints
  • security policies and compliance requirements
  • Exposed endpoints (APIs), data stores
  • Operational metrics, logs and audits
  • SLAs, monitoring dashboards and runbooks

Description

The backend is the server-side application layer that implements business logic, data storage, and integration points. It manages APIs, authentication, processing, and communication with external services, decoupled from frontend technologies. Deployment, scalability, security, and operational monitoring are key operational concerns.

✔

  • Encapsulation of business logic and data access.
  • Scalability through separate services and resource control.
  • Reusable APIs for different clients.

✖

  • Increased operational effort for deployment and monitoring.
  • Complexity in consistency and distributed transactions.
  • Third‑party dependencies can increase outage risk.

  • Requests per second (RPS)

    Measure throughput to assess scalability.

  • Error rate (5xx rate)

    Indicates stability and misbehavior.

  • Mean response time (P50/P95/P99)

    Key indicators for user experience and SLAs.

E‑commerce backend with order domain

Separation of order, product and payment logic into separate services with asynchronous order processing.

Analytical backend for event aggregation

Real‑time ingestion, streaming processing and materialized views for dashboards.

Backend for mobile applications

Lightweight APIs, offline synchronization and push notifications as core features.

1

Define API interfaces and data models.

2

Implement core logic modularly and secure with tests.

3

Set up deployment pipeline, monitoring and alerting.

⚠️ Technical debt & bottlenecks

  • Monolithic database without partitioning strategy.
  • Missing tests for integration paths.
  • Outdated dependencies and insecure libraries.
Database throughputSynchronous third‑party callsBlocking I/O operations
  • Backend takes on UI logic instead of providing APIs.
  • Little or no monitoring after production rollout.
  • Missing authentication for internal endpoints.
  • Underestimating operational effort for security patches.
  • Optimizing only for P99 latency without cost consideration.
  • Too tight database schemas block future extensions.
Server‑side programming and API designDatabase modeling and performance tuningOperations, observability and security principles
Scalability and load distributionSecurity and complianceAvailability and fault tolerance
  • • Existing database architecture and migration effort
  • • Regulatory requirements (data protection, retention)
  • • Budget for infrastructure and operations