Software systems fail. The expensive part is not the failure itself but the recovery: manual restarts, replayed jobs, drained queues, and configuration changes performed under pressure at inconvenient hours. Most teams already know the corrective actions for their common incidents. What they lack is an architecture that can apply those actions without waiting for a human to intervene every time.
This book brings recovery into the architecture. It treats self-healing as a design discipline and provides a reference architecture that organizes detection, decision, safety, execution, and verification into a coherent control loop. It then delivers a concrete reference implementation in .NET, mapping every architectural layer to explicit contracts and components that teams can study, adapt, and extend.
The architecture is grounded in production experience on a large distributed platform that connected dozens of public administrations through document exchange flows. As external integrations multiplied, each new dependency brought failure modes that demanded their own detection logic and recovery strategies. The design described in these pages emerged from that growth, and the anecdotes, case studies, and decisions throughout the text reflect that origin.
The treatment goes beyond cloud-native microservices. It covers monoliths, legacy systems, hybrid environments, batch processing, messaging, and queue-centered workloads. It addresses the operating model as well: governance, safety boundaries, adoption roadmap, anti-patterns, and organizational roles. No existing title combines a self-healing reference architecture with a .NET reference implementation, and I believe this book addresses a gap that practicing .NET architects will recognize.


What You Will Learn:

• Design and implement a self-healing reference architecture in .NET, with explicit contracts for observation, detection, decision, safety, execution, and verification.
• Classify failure modes (stall, degradation, traffic absence, gray failure) and build composite detection rules that reduce false positives while catching real conditions.
• Design bounded recovery actions (restart, degraded mode, quarantine, replay, credential rotation) with safety guards, cooldowns, action budgets, and verification gates.
• Apply self-healing patterns across different deployment topologies: single deployable, API-worker pair, queue-centered tier, modular monolith, distributed services, and hybrid/legacy environments.
• Build the organizational operating model behind self-healing: governance, adoption roadmap, maturity assessment, incident integration, and team roles.

Who This Book is For
The primary audience is .NET software architects and senior developers who design and operate backend systems, distributed services, messaging platforms, and integration layers. These professionals deal with production reliability challenges and are looking for a structured approach to automated recovery beyond ad-hoc retry logic and restart scripts.