🧱 Error Handling
Error handling design is the discipline of defining how a system detects, reports, propagates, and recovers from errors in a predictable, consistent, and maintainable way. It is a cross‑cutting architectural concern that affects every layer of the system—from UI to backend to infrastructure.
Error handling design — definition
Section titled “Error handling design — definition”Error handling design defines the strategy, patterns, and mechanisms a system uses to manage failures. It ensures errors are detected early, communicated clearly, logged consistently, and handled gracefully without breaking the system or confusing the user.
It answers:
- How do we detect errors?
- How do we propagate them?
- How do we recover from them?
- How do we communicate them to users and logs?
Why error handling design matters
Section titled “Why error handling design matters”Good error handling:
- Prevents system crashes
- Improves reliability and resilience
- Makes debugging easier
- Improves user experience
- Supports observability
- Reduces operational risk
- Enforces consistency across modules
Poor error handling leads to brittle systems, hidden failures, and painful debugging.
Core principles of error handling
Section titled “Core principles of error handling”- Fail fast — detect errors early and stop invalid flows
- Graceful degradation — keep the system usable even when parts fail
- Clear separation of concerns — centralize error handling logic
- Consistent error models — use predictable error formats
- Meaningful messages — help developers and users understand what happened
- Logging and monitoring — capture context for debugging
- Avoid silent failures — never swallow exceptions
- Use exceptions intentionally — throw only when necessary
- Retry and backoff — handle transient failures
- Circuit breaking — prevent cascading failures
These principles ensure predictable, maintainable error handling.
Error handling layers
Section titled “Error handling layers”1. Detection
Section titled “1. Detection”Identify when something goes wrong.
Examples: validation failures, exceptions, timeouts, failed API calls.
2. Propagation
Section titled “2. Propagation”Decide how errors move through the system.
Examples: throw exceptions, return error objects, publish events.
3. Handling
Section titled “3. Handling”Define how errors are resolved.
Examples: retries, fallback logic, compensation actions.
4. Reporting
Section titled “4. Reporting”Communicate errors to logs, monitoring systems, and users.
Examples: structured logs, alerts, user-friendly messages.
5. Recovery
Section titled “5. Recovery”Restore the system to a stable state.
Examples: rollback, circuit breaker reset, retry queues.
Error handling patterns
Section titled “Error handling patterns”- Try/catch with logging — basic exception handling
- Global exception middleware — centralized error handling
- Result objects — return success/failure without exceptions
- Retry pattern — handle transient failures
- Circuit breaker — prevent cascading failures
- Fallback pattern — alternative logic when primary fails
- Dead-letter queues — handle failed messages
- Compensation transactions — undo partial work
These patterns help build resilient systems.
Designing error messages
Section titled “Designing error messages”Good error messages are:
- Clear
- Actionable
- Contextual
- Consistent
- Non‑technical for end users
- Detailed for logs (stack trace, correlation ID)
Avoid vague messages like “Something went wrong.”
Error handling in distributed systems
Section titled “Error handling in distributed systems”Distributed systems require special care:
- Correlation IDs for tracing
- Structured logs for observability
- Retries with exponential backoff
- Circuit breakers to isolate failures
- Idempotency to avoid duplicate operations
- Dead-letter queues for unprocessable messages
Error handling becomes part of the architecture, not just code.
Example
Section titled “Example”If you apply error handling design to a Daily Scrum application:
- Global exception middleware → consistent API error responses
- Result objects → predictable service layer outcomes
- Retry logic → for PDF generation and notifications
- Circuit breaker → for external email/SMS providers
- Structured logging → include correlation IDs for each request
- User-friendly messages → “Unable to generate summary. Please try again.”
- Dead-letter queue → store failed notification messages
- Monitoring → Application Insights alerts for repeated failures
This ensures reliability and a smooth user experience.
Takeaway
Section titled “Takeaway”Error handling design defines how a system detects, propagates, reports, and recovers from failures. Good error handling is consistent, centralized, observable, and resilient. It is essential for building stable, maintainable, and user-friendly systems.