Autopilot 1.1

What's new

• New Relic AI Knowledge is now in Autopilot

  • Connect Confluence retros, postmortems, runbooks, and custom documents like PDFs, CSVs, and text files so the agent delivers recommendations grounded in your team's best practices, not generic guidance.
  • Reduce investigation time by surfacing the past incident that matches what you are seeing, the steps that resolved it, and the team who handled it.
  • Ask about standard triage steps for an alert or request the runbook for a specific error, and get a direct answer from your own documentation.
  • Update documentation on a recurring schedule so the agent always reflects your most current content as your environment evolves.

  For more information, refer to New Relic AI Knowledge.

• Improvements to investigation completion - with testing showing a 21% increase in completion rates.

• Get the right investigation for the problem you actually have: The Autopilot now picks its strategy based on whether you are seeing a latency spike, an error burst, or missing data, rather than following a fixed template. Coverage now spans APM applications, browser apps, synthetic monitors, external services, Kubernetes workloads, mobile apps, and infrastructure hosts.

• Get answers from your data without writing NRQL: The Autopilot now translates plain-language questions about your telemetry into NRQL queries and returns the results, so you can investigate ad hoc questions without knowing the query language or jumping to the query builder.

• Compare before-and-after performance after a deployment: The Autopilot uses purpose-built change event tools to give you structured deployment correlation rather than guesswork.

• Identify who changed what before an incident: A new audit skill correlates configuration changes to alert policies, monitors, and workloads using NrAuditEvent data, so you can connect a change to the symptom.

• Trace requests across services: The Autopilot uses distributed tracing call graphs to identify the upstream and downstream dependencies driving latency or errors.

• Better Kafka investigations: Consumer lag, producer throughput, and partition balance analysis are integrated into Kafka-related investigations.

• Investigations that read your dashboards and help build new ones: The Autopilot now pulls context from the dashboards you have already built and generates JSON code so you can easily create dashboards from a question, so the views your team has already curated inform every answer and you can walk away with a tailored visualization rather than just text.

• Get APM-native answers for APM entities: Investigations on APM applications now query APM-specific metrics directly rather than relying solely on golden signals.

• Ask broader questions and get a complete answer in one pass: A single investigation can combine multiple analysis techniques, so you no longer need a chain of follow-up prompts to get a comprehensive picture.

• Find out why telemetry went missing: When data appears to be gone, the agent queries NrIntegrationError to surface dropped data, rejected payloads, rate limits, and pipeline failures.

• Investigations are tailored to your environment from the start: Before the Autopilot picks a strategy, it gathers your entity relationships, recent deployments, and active alerts so the investigation reflects what is actually happening in your environment rather than following a generic playbook.

• Catch the signal you would have missed before: Alert-triggered investigations now use wider time windows, and issue lookups use the full default lookback period so you see the complete context around each incident.

• Know what the agent could not see: When tool results are truncated or come back empty, the agent tells you exactly what was limited and why.

• Vague questions get a useful response: Asking "what's wrong with my app" now triggers a targeted clarifying question instead of silently failing, so you get to an actionable target faster.

• Simple questions get simple answers: General and low complexity questions get a direct response instead of being forced through the full investigation pipeline.