Build an agentic incident triage assistant with Amazon Quick and New Relic

· Source: Artificial Intelligence · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering, Cloud Computing & IT Infrastructure · Depth: Intermediate, long

Summary

An agentic incident triage assistant can be built using Amazon Quick and New Relic to streamline incident response workflows. This solution leverages Amazon Quick's native integrations with New Relic Model Context Protocol (MCP) Server and Asana to automate evidence collection, root cause analysis (RCA) brief generation, and task creation. From a single prompt, the Amazon Quick agent orchestrates five New Relic reasoning tools—including generate_alert_insights_report and analyze_entity_logs—to investigate incidents. It then compiles a comprehensive RCA brief with evidence links and creates a tracked Asana task for handoff. Internal testing by New Relic demonstrated that this agent reduced the evidence-gathering phase, leading to faster resolution, minimized knowledge loss, and standardized investigations across on-call rotations. Setting up requires an Amazon Quick Professional subscription, New Relic, and Asana accounts.

Key takeaway

For SREs or MLOps Engineers focused on reducing mean time to resolution (MTTR), implementing an Amazon Quick-based incident triage agent can significantly streamline your workflow. You can automate evidence gathering, root cause analysis brief generation, and task creation from a single prompt, ensuring consistent investigation standards across your team. This approach minimizes manual coordination between observability and tracking systems, freeing your engineers to focus on resolution rather than administrative overhead.

Key insights

An AI agent can automate incident triage by integrating observability and task management tools into a single conversational workflow.

Principles

Method

Configure Amazon Quick with New Relic and Asana integrations. Create a custom chat agent, define its purpose and tool routing, then link the configured integrations to enable automated incident investigation and task creation.

In practice

Topics

Best for: MLOps Engineer, AI Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial Intelligence.