Introduction Retry storms historically impact business operations and brand trust. While retry configuration tuning and retry budgets provide meaningful mitigation at the service level, they’re manually configured and lack visibility into cross-service amplification caused by deep dependency chains and fan-out patterns. As a result, it can be difficult to shield infrastructure against the domino effect triggered by a single service outage deeper in the stack.  A key reason is that retry behavior today isn’t context-aware. While we can control how many retries occur, we can’t precisely control when they occur. This stems from the challenge of reliably distinguishing between errors generated by a service and those merely propagated through it. As a result, retries are applied uniformly rather than conditionally. This approach works for transient or low-rate failures. However, during moderate or severe degradation, it becomes counterproductive.…