Proactive incident response for IT operations teams

Use full context to optimize alert data, enhance investigation, and speed resolution with an actionable view of your IT environment.

Improve alert quality to meet SLAs

Eliminate manual efforts so IT operations teams can focus on critical incidents despite the volume of alert noise.

Avoid surprises

Automatically distill thousands of multisource alerts into meaningful insights for clear, prompt impact assessment. Expedite identification and prioritize remediation to prevent escalation of critical incidents.

Diagram showing filtering to highlight actionable alerts.
A hub and spoke view of data fed from multiple sources.

Bridge gaps between teams

Centralize alert data to share knowledge from monitoring and observability tools. Use an open, agnostic hub view to access the complete dataset for rapid identification and remediation.

Accelerate analysis with full context

Automated Incident Analysis provide real-time root-cause analysis for more efficient incident management recommendations, higher-quality tickets, and first-touch resolution. Automate workflows to reduce manual work, escalations, and bridge calls.

AI-generated summary of incident analysis from multiple alerts.
Chart showing improvements in noise reduction, MTTR, and team productivity

Meet SLAs consistently

Detect developing incidents and surface root cause before they become into outages and result in SLA penalties. Full-context data reduces triage time, shortens response timelines, and keeps systems available.

“BigPanda has helped significantly with deduplicating, correlating, and automating our process. We now have the full context around what is impacted throughout the organization and how to fix it quickly.”

“We can now route alerts to the appropriate teams. They get visibility into what’s happening in their network and know that we’re working on the right things with the right people.”

FAQ

How does BigPanda reduce costs and improve operational efficiency?

The BigPanda event correlation and automation platform reduces alert volume by more than 95% and automates repetitive tasks. Automated Incident Analysis and Root Cause Changes add context, enabling IT operations management teams to handle increased alert data and resolve more incidents.

How does BigPanda reduce MTTR?

Leveraging AI and ML for alert, change, and topology data correlation, BigPanda identifies incidents at inception, curbing outage frequency and impact to crucial applications. BigPanda swiftly pinpoints potential root causes with AI and routes incidents to the appropriate teams for rapid resolution.

What type of data does BigPanda use to deliver full-context operations?

BigPanda aggregates and normalizes data from sources including topology, CMDB, and change data. It enriches actionable insights and automated root-cause analysis using multidimensional alert correlation and AI analysis to facilitate swift, informed decision-making. This holistic approach streamlines incident identification and resolution, offering a comprehensive view of system interconnectivity and operational impacts.