Real-time metrics ingestion, ML-powered anomaly detection,
and containerized log aggregation — built for production-grade monitoring.
Trained on historical system metrics to flag CPU, memory, and latency deviations. Auto-refit triggered on distribution drift.
Multi-node metric collection with SQLite time-series persistence, configurable scrape intervals, and REST endpoints.
Full service isolation per component. One-command startup, reproducible across dev, staging, and production environments.
Cross-service log collection with severity classification, pattern matching, and searchable event history across all nodes.
Real-time node health, throughput graphs, and anomaly alert feed — no page reload required. Sub-second update latency.
Threshold-based and ML-derived alerts across CRIT / WARN / INFO levels with event correlation and deduplication.