Compare BigPanda vs. Noction IRP

All data sources, including topology, monitoring, change, and observation tools, are aggregated. BigPanda's Open Box Machine Learning will combine the data into a limited number of actionable insights. This allows incidents to be detected as they occur, before they become outages. Automatically identifying the root cause of problems can speed up incident and outage resolution. BigPanda identifies both root cause changes and infrastructure-related root causes. Rapidly resolve outages and incidents. BigPanda automates the incident response process, including ticketing, notification, tickets, incident triage, and war room creation. Integrating BigPanda and enterprise runbook automation tools will accelerate remediation. Every company's lifeblood is its applications and cloud services. Everyone is affected when there is an outage. BigPanda consolidates AIOps market leadership with $190M in funding and a $1.2B valuation

Noction IRP is an edge-deployed BGP optimization platform that analyzes traffic in real-time to detect congestion, link failures, and performance degradation. The system continuously probes network routes across all available providers, measuring latency, packet loss, and historical reliability to identify the best paths for both inbound and outbound traffic. Route probing operates independently of production traffic flow, ensuring comprehensive visibility without impacting live sessions. IRP manages ingress and egress bandwidth intelligently, distributing traffic flows across providers to minimize costs while maintaining quality of service. The platform features configurable traffic engineering policies that allow operators to define cost priorities, performance targets, and failover behaviors. Traffic is automatically rerouted when performance thresholds are reached, ensuring optimal traffic delivery, while respecting network policies and business requirements. Built-in Automatic Anomaly Detection (AAD) provides DDoS protection by analyzing traffic behavior and identifying deviations from established baselines. Unlike static threshold-based systems, AAD builds adaptive behavioral models that adjust to legitimate traffic patterns. AAD detects volumetric floods, amplification attacks, TCP SYN floods, and application-layer threats, then executes mitigation automatically using BGP FlowSpec for granular filtering and RTBH mechanisms for complete traffic blocking when necessary. IRP delivers 30%-50% average performance improvement, up to 50% latency reduction, and near-100% network availability while reducing bandwidth costs through intelligent multi-homed routing decisions. The platform integrates seamlessly with existing BGP infrastructure.