Mike Mannion
Mike Mannion is a software developer, consultant, and long-time Java practitioner with more than three decades of experience building enterprise systems. He has spoken at JavaOne in San Francisco and at many other conferences and user groups.
He is the creator of PUnit, an open-source framework for probabilistic testing in Java. His recent work focuses on a problem many teams are now encountering: once AI, LLMs, distributed systems, or other non-deterministic components enter the control flow of an application, traditional one-shot assertions are no longer enough.
Mike’s talks explore how developers can regain confidence in such systems by using statistical evidence: repeated sampling, pass-rate thresholds, confidence intervals, empirical baselines, and ongoing monitoring. His goal is to make probabilistic thinking accessible to working developers without burying them in statistical theory.
Session
Software does not simply break — it reveals. Every fault, latency spike, and cascading failure is a signal about the assumptions baked into your design. The question is whether your system — and your test suite — is equipped to hear it.
This workshop fuses two complementary disciplines into one intensive, hands-on session:
Probabilistic Testing with Punit — the statistical tooling that lets Java teams measure, enforce, and version-control the resilience properties of non-deterministic systems: LLM integrations, ML inference, distributed services, and randomized algorithms that traditional binary pass/fail tests were never designed to handle.
Resilience Engineering for Java — the design principles, and architectural patterns that turn pressure into performance, like circuit breakers, fault injection, and TDD-driven failure handling.
The thread connecting both halves is a concrete end-to-end scenario: an AI-enriched Java application, where non-deterministic LLM calls meet production-grade resilience requirements. Participants work through the full arc — from writing probabilistic test specifications and latency percentile assertions, to implementing and verifying the resilience patterns that make those specifications pass.
Participants leave with a concrete vocabulary, a proven pattern catalogue, and running JUnit 5 tests that express and verify resilience as first-class distributional contracts, and not vague aspirations.