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A resilience pattern that automatically retries transiently failing operations to increase reliability in distributed systems.
DESCRIPTION
The Retry pattern handles transient faults by reattempting operations likely to succeed after a short delay. It is common in microservices, cloud APIs, and networked systems where intermittent failures occur. Configurable parameters include maximum attempts, delay strategy, and error categories considered retryable. Idempotency is crucial to prevent duplicate side effects. Combine retries with backoff and jitter to avoid thundering herd issues. Integrate with circuit breakers to stop retries when failures persist. Logging and metrics help tune retry behavior and observe impact on latency.
ALTERNATIVE DEFINITIONS
Microsoft Learn
Enable an application to retry an operation that has previously failed due to a transient fault.
Explicitly frames transient faults and application-level enablement.
AWS Well-Architected
Implement retries with exponential backoff and jitter to handle transient failures and reduce contention.
Emphasizes backoff and jitter to mitigate retry storms.
Google Cloud
Clients should retry failed requests that return retryable error codes using an appropriate backoff strategy.
Links retry behavior to API error codes and backoff.
RELATED TERMS
Retry with Backoff Jitter Idempotency Timeout Rate Limiting Bulkhead Pattern Dead Letter Queue Transient Fault Handling Load Shedding
COMPETING TERMS
KNOWLEDGE AREAS
Software Engineering Data Engineering Real-time & Streaming Data Infrastructure Observability & Telemetry
TARGET AUDIENCE
Software Developer DevOps Engineer Data Engineer Cloud Architect Solution Architect
EXTERNAL SOURCES
- Wikipedia - Resilience pattern
- Microsoft Learn - Azure cloud design pattern
- AWS Well-Architected - AWS reliability guidance
- Google Cloud - API error and retry guidance
TOP QUESTIONS
When is the Retry Pattern appropriate?
Use it for transient failures, such as temporary network issues or service throttling. It is not suitable for permanent errors or validation failures.
Category: Requirements
What is a common mistake with the Retry Pattern?
Retrying non-idempotent operations without safeguards can cause duplicate side effects. Design idempotent endpoints or include de-duplication.
Category: Mistakes
How should delays be managed in the Retry Pattern?
Use backoff and jitter to space retries and avoid synchronized bursts. Adjust delays based on error type and service guidance.
Category: Management
What risks accompany aggressive retries?
They can overload a struggling service, amplify outages, and increase latency. Circuit breakers and caps on attempts mitigate these risks.
Category: Risks
How does the Retry Pattern relate to Circuit Breakers?
Circuit breakers stop retries when failure rates exceed thresholds, protecting services and callers from cascading failures.
Category: Misunderstanding
What is currently a hot topic around the Retry Pattern?
Adaptive retry policies informed by service health signals and error taxonomy, combined with client-side rate limiting, are gaining traction.
Category: Topic
How to validate a Retry Pattern implementation?
Use chaos experiments and fault injection to simulate transient errors. Monitor retries, success rates, and latency under load.
Category: Testing
What metrics should be monitored with retries?
Track retry counts, backoff durations, error codes, success after retry, and tail latency to tune behavior.
Category: Observability
What are alternatives to the Retry Pattern?
Circuit Breaker, Timeouts with fallback, and asynchronous queue-based processing can complement or replace retries depending on context.
Category: Alternatives