Self-Healing REST Services Using Artificial Intelligence in Multi-Cloud Environments

The current day digital applications are based on the search of RESTful services and use distributed cloud infrastructures. The problem of service reliability becomes much more complicated as organizations are switching to multi-cloud architecture to enhance their scalability, reliability, and independence with a single vendor. Conventional methods of monitoring and incident-response usually respond very slowly to failures like API spikes in latencies, service failures, container crashes, and configuration errors. These limits cause downtime, reduced performance and operational costs. Self-healing systems have become a good solution in order to overcome these challenges. A self-healing architecture allows software systems to automatically identify, diagnose, and recover failure automatically without human intervention. Together with Artificial Intelligence (AI), self-healing can forecast possible failures and optimise system behaviour, as well as automatically implement corrective measures. Monitoring systems that are powered by AI can process large amounts of system telemetry, logs and performance metrics to find anomalies and initiate automatic remediation. This paper suggests