ATLAS: Learning to Rewire the Web—Predictive Architecture Transformation for Autonomous Cloud Systems

Online platforms and IoT back-ends face abrupt traffic surges. A tightly coupled monolith keeps response times short but becomes fragile under peak load, whereas loosely coupled microservices scale and isolate faults at the price of extra network communication and infrastructure. We present ATLAS (Adaptive Traffic-aware Loose–tight Architecture System), which changes at runtime which modules execute in-process and which run as isolated services. An LSTM forecasts traffic, an Isolation Forest detects anomalies in aggregate telemetry, and a binary optimisation model with a switching cost, solved exactly for small module sets, selects tight, hybrid or loose coupling (all reported results use this exact solution; a linearised heuristic for larger module sets is assessed offline only); an explicit switching protocol hands module state over between hosts and a seven-step self-healing protocol recovers failed modules. We evaluate ATLAS with a released simulator driven by synthetic workloads and with a process-level prototype. On held-out traffic, the trained LSTM reaches a five-minute MAPE of 14.8%. In 30 paired simulated runs with a flash sale, a resource anomaly and a service failure, ATLAS achieved a p99 latency of 90 ms against at least 128 ms for four autoscaled microservice baselines, 51% fewer SLA violations, no failed requests and 20% lower cost (p<0.01, Wilcoxon), with a similar recovery time. This advantage holds under the simulated conditions only: ATLAS performed worse than the baselines with pod start-up above about a minute, ±30% service-demand deviations, repeated failures, and in several combinations of adverse conditions, and its anomaly detector improved results only when an anomaly coincided with high load. The single-host prototype hands a stateful module over with a 1.4 ms pause and recovers from a process crash in 325 ms (process level, without container restart, service mesh or inter-node communication) without failed or lost requests. In a simulated connected-vehicle case study, ATLAS achieved the lowest latency (10.2 ms at peak against 20.8 ms for static microservices) and the highest SLA compliance (99.79%), at a slightly higher cost than static microservices. Smart-hospital and smart-factory scenarios illustrate further applications. Validation on production Kubernetes clusters with real traces remains future work.