The Challenge
The client's NOC team was drowning in alert noise — thousands of daily events from Nokia network elements requiring manual triage. Mean time to resolution was measured in hours, not minutes. Root cause analysis was performed manually by senior engineers, creating bottlenecks and burnout.
The Atsky Solution
We architected and deployed an ML-powered Situation Enrichment Pipeline that ingests raw event streams, applies multi-layer ML classification to filter noise, and generates automated RCA summaries integrated directly into the client's BMC Helix ITSM platform.
The pipeline runs on Kubernetes, with a full MLOps framework for model versioning, performance monitoring, and scheduled retraining — ensuring accuracy improves continuously as new network patterns emerge.
Outcomes
Alert noise reduced by over 90%. RCA generation time dropped from 2–4 hours to under 60 seconds. NOC team capacity redirected from reactive triage to proactive network optimisation.