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SRE Agent release notesRSS

June 11
SRE Agent 1.1

preview

We're still working on this feature, but we'd love for you to try it out!

This feature is currently provided as part of a preview program pursuant to our pre-release policies.

What's new

  • New Relic AI Knowledge is now in the SRE Agent

    • 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 SRE Agent 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 SRE Agent 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 SRE Agent 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 SRE Agent 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 SRE Agent 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 SRE Agent 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.

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