GovindQuestion / Claim
Why do retries and lack of idempotency cause major failures in distributed systems?
Key Assumptions
- Distributed systems are always in a state of partial failure(high confidence)
- Retries without strict idempotency amplify load and cause cascading failures(high confidence)
- Many retry mechanisms are enabled by default without system-level coordination(high confidence)
Evidence & Observations
- Real-world outages often stem from retry storms where upstream services overwhelm degraded downstream dependencies.(personal)
- AWS Architecture Blog and postmortems show that retry storms and thundering herd effects are common root causes of cascading failures in distributed systems.(citation)
- Google SRE literature documents that retries without backoff and idempotency can amplify partial outages into full system failures.(citation)
Open Uncertainties
- How well modern AI-generated systems handle coordinated retries and idempotency at scale
Current Position
Most large-scale outages are caused not by failures themselves, but by uncontrolled retries and non-idempotent operations that amplify partial failures.
This is work-in-progress thinking, not a final conclusion.
References(3)
- 1.^"Avoiding Fallback in Distributed Systems"↗aws.amazon.com— AWS Builders’ Library article explaining how retries and fallback mechanisms can amplify failures if not carefully designed.
- 2.^"Handling Overload"↗sre.google— Google SRE Book chapter describing overload, retries, backoff strategies, and idempotency in large-scale systems.
- 3.^"Idempotent Consumer Pattern"↗martinfowler.com— Martin Fowler article describing design patterns to safely handle retries and at-least-once delivery.
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