The development of self-healing applications is a process. Business enterprises ought to begin by evaluating the vital systems and determining the possible areas of failure. This involves the analysis of application workflows, databases, network dependencies and third-party integrations. The companies can concentrate on the areas where self-healing mechanisms will be most valuable by focusing on high-impact components.

The second step is to select appropriate AI and monitoring frameworks by organizations. In the case of .NET, integrating ASP.NET core development with cloud AI services, such as Azure Monitor and Azure Application Insights, allows tracking the health and performance of the system in real-time. AI agents can be conditioned to identify anomalies, do root-cause analysis, and even automatically roll back code changes in case something goes wrong.

Also, the implementation of DevOps and CI/CD pipelines will be used to make sure that self-healing capabilities are properly tested in staging environments prior to deployment. A set of automated tests can be used to mimic failures to test the reaction of the self-healing mechanisms, which will give confidence that the production systems will be resilient.