Catalog
method#Integration#Software Engineering#Observability#Security

API Consumption

Guideline for the structured use of external and internal APIs by applications and services.

API consumption describes how applications and services use external or internal APIs in a structured way.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

API gateway / management (e.g., Kong, API Platform)Identity provider (OAuth2 / OpenID Connect)Observability stack (Prometheus, Grafana, Jaeger)

Principles & goals

Define clear contracts (schema, versioning) before consumption.Ensure resilience via timeouts, retries and fallbacks.Provide visibility through telemetry, logs and SLA metrics.
Build
Team, Domain

Use cases & scenarios

Compromises

  • Leakage of credentials or insecure authentication.
  • Unhandled failure cascades across the system.
  • Excessive synchronous dependencies increase outage risk.
  • Maintain contracts formally (e.g., OpenAPI) and test them automatically.
  • Configure conservative timeouts and exponential backoffs.
  • Collect telemetry per endpoint (latency, errors, throughput).

I/O & resources

  • API specification or contract (e.g., OpenAPI)
  • Authentication and authorization information
  • Operational and monitoring access
  • Consumed data and standardized DTOs
  • Metrics, logs and traces
  • Error reports and SLA alerts

Description

API consumption describes how applications and services use external or internal APIs in a structured way. It covers contracts, authentication, rate limiting, data transformation, and error handling. Robust consumption patterns improve reuse, reliability, observability, and performance in distributed architectures at scale.

✔

  • Increased reuse of services and clearer integration boundaries.
  • Better fault isolation and controllable stability in distributed systems.
  • Enables standardization, monitoring and automated tests.

✖

  • Additional latency from network calls and serialization.
  • Third‑party dependencies can affect availability.
  • Versioning and compatibility effort when interfaces change.

  • Error rate (5xx/4xx)

    Share of failed API calls relative to total calls.

  • Latency (P95, P99)

    Response time distribution to assess performance SLAs.

  • Throughput (requests per second)

    Measure of processed calls per time unit.

GitHub API for repositories

Consumers use REST/GraphQL interfaces to display and synchronize repository data.

Stripe payments integration

Payment processing via external API including webhooks, idempotency and security model.

Internal CRM as API

Unified CRM API consumed by multiple frontends and integrations, with versioning and access controls.

1

Define and publish the contract (spec).

2

Implement client adapter with timeouts, retries and circuit breaker.

3

Integrate monitoring, metrics and alerts.

4

Establish versioning strategy and migration plan.

⚠️ Technical debt & bottlenecks

  • Ad-hoc integrations without contract tests.
  • Missing SDKs or outdated client libraries.
  • Incomplete telemetry for critical calls.
Rate limits and throttlingAuthentication performanceData format and schema mismatch
  • Frontend calls internal microservices synchronously in series instead of using BFF aggregation.
  • Hardcoding sensitive API credentials in client code.
  • Omitting monitoring, causing undetected outage risks.
  • Missing timeouts cause hanging resources.
  • Caching without invalidation yields stale data.
  • Tight coupling to provider-specific features.
HTTP/REST, API design and schema understandingSecurity concepts (OAuth2, TLS, key management)Monitoring, logging and troubleshooting in distributed systems
Interface contracts and versioningSecurity and authentication requirementsLatency, availability and scalability goals
  • • Network latency and bandwidth limits
  • • Legal requirements for data exchange
  • • Provider-side rate limits and cost models