Uploaded July 2026 | Updated September 2026, 2 weeks ago
Title: Preventing Retry Storms in AI-Assisted Microservices
Date: July 16, 2026
Duration: 1HR
ABSTRACT
Modern microservices depend on retries to survive failures. When used carefully, retries improve reliability. When used without limits, they can turn a small problem into a major outage. As organizations adopt AI-assisted operations and autonomous agents, this risk becomes even greater. An AI system may detect a problem and respond exactly as designed, but if every service retries at the same time, the result can be overloaded dependencies, growing queues, rising costs, and cascading failures across the platform.
This talk challenges a common assumption in distributed systems; that more retries always improve reliability. Using real-world examples from cloud-native financial systems, we will explore why retry storms happen, how they spread, and why traditional approaches often fail under pressure. We will discuss practical techniques such as retry budgets, backoff strategies, request deadlines, observability signals, and feedback controls that help keep systems stable during failures.
The session will also examine how AI-assisted operational systems can make better decisions when they are guided by clear boundaries and system-level feedback rather than simply reacting to local failures. As systems become more autonomous, reliability will depend not only on making smarter decisions, but also on knowing when not to act.
Attendees will leave with practical patterns for building resilient microservices that remain stable even when failures, automation, and AI-driven decisions collide.
SPEAKER
Sibasis Padhi
Staff Software Engineer at Walmart Global Tech
MODERATOR
Anusha Nerella
Senior Software Engineer; ACM Practitioner Board
Title: Preventing Retry Storms in AI-Assisted Microservices
Date: July 16, 2026
Duration: 1HR
ABSTRACT
Modern microservices depend on retries to survive failures. When used carefully, retries improve reliability. When used without limits, they can turn a small problem into a major outage. As organizations adopt AI-assisted operations and autonomous agents, this risk becomes even greater. An AI system may detect a problem and respond exactly as designed, but if every service retries at the same time, the result can be overloaded dependencies, growing queues, rising costs, and cascading failures across the platform.
This talk challenges a common assumption in distributed systems; that more retries always improve reliability. Using real-world examples from cloud-native financial systems, we will explore why retry storms happen, how they spread, and why traditional approaches often fail under pressure. We will discuss practical techniques such as retry budgets, backoff strategies, request deadlines, observability signals, and feedback controls that help keep systems stable during failures.
The session will also examine how AI-assisted operational systems can make better decisions when they are guided by clear boundaries and system-level feedback rather than simply reacting to local failures. As systems become more autonomous, reliability will depend not only on making smarter decisions, but also on knowing when not to act.
Attendees will leave with practical patterns for building resilient microservices that remain stable even when failures, automation, and AI-driven decisions collide.
SPEAKER
Sibasis Padhi
Staff Software Engineer at Walmart Global Tech
MODERATOR
Anusha Nerella
Senior Software Engineer; ACM Practitioner Board
