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Autopilot release notesRSS

August 13
Autopilot 2.1

What's new

Autopilot: More Reliable Analysis

  • More accurate anomaly detection: Transaction dependency analysis now uses a more rigorous threshold. The previous setting was overly-sensitive and flagged noise as anomalies. Downstream dependency analysis also more clearly differentiates between correlation and causation, reducing speculative root-cause attribution.
  • Trend comparisons grounded in real data: When Autopilot compares current error rates or counts to a prior period, those baselines now come from verified NRQL queries.
  • Longer investigations complete reliably: Resolved a bug where some investigation flows did not properly perform context window compaction when they needed to occur. If compaction encounters an error, your investigation progress is preserved rather than lost. Investigations also properly stop when you navigate away, freeing browser resources.
  • Correct active issue counts: Added fixes to return more accurate number of issues when asking for number of active issues in your account.
  • Slack responses render cleanly: Markdown tables and structured formatting (headers, dividers, and lists) now display correctly in Slack notifications and workflow responses.
  • EU entity resolution fixed: Resolved a bug that made it difficult for Autopilot running in the EU to find the Kubernetes agent.
  • Your timezone and context preserved: Your timezone and the entity context you're investigating are now correctly maintained throughout the entire session. Previously, context could be lost when multiple context sources were present.
  • General fixes to UI rendering when using comparison operators and special characters: NRQL queries containing comparison operators or other special characters are no longer mangled in the response visualization.
  • Improved prompt-injection identification, with fewer false positives: Autopilot no longer incorrectly declines benign in-chat notes (such as providing context or clarifying details) with a misleading "prompt injection" warning. The guardrail is now properly scoped so valid requests proceed normally.
  • Memory recall improvements: Fixed bugs that prevented Autopilot from finding facts from multi-memory lookups and improper flags on valid memories.
  • Preferences honored correctly: Autopilot no longer incorrectly tells you it can't remember your stated preferences (like how you'd like to be addressed). Your conversational preferences are now recognized and respected.
  • Documentation citations reference the right account: When Autopilot cites documentation or entity information from RAG lookups, it now references entity GUIDs belonging to your account.
  • Accurate timeseries results reporting: TIMESERIES NRQL queries that return valid data are no longer incorrectly reported as having no results.
  • No more repeated reasoning text: Fixed a bug where the same reasoning text could appear multiple times in Autopilot's thinking display during an investigation.
  • Improved stability of the chat panel in the browser: Fixed a memory leak that could cause browser tab crashes when loading chat history on accounts with many conversations. Also fixed crashes when multiple browser tabs had the AI chat panel open simultaneously, and prevented concurrent agent streams from conflicting when starting a new conversation mid-stream.
  • Better visualization summaries: Investigation responses now capture both NRQL queries and their resulting visualizations more completely, giving you richer context in summary cards.
  • Incident investigation follows related issues: When investigating major incidents with related issues across different accounts, Autopilot now resolves each related issue using its own account ID rather than defaulting to the parent incident's account.
  • UI polish: Feedback ratings now only persist when you explicitly submit them. Action icons are always visible (no longer hidden behind hover). Copy conversation is properly disabled until there's content to copy. Slash command connector names display correctly.

GitHub MCP Integration Capability (Public Preview)

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.

When an alert points at a deployment-related regression, the first question is almost always "what shipped?" You end up switching between the New Relic incident, your Change Tracking event, and the GitHub PR to piece the story together. Connect Autopilot to GitHub so it can pull the Pull Request behind a Change Tracking deployment and return the "what shipped" story inline.

  • Link a deployment to a PR: When Autopilot identifies a Change Tracking event with a commit SHA during an investigation, it fetches the associated Pull Request and returns the number, title, description, author, and URL as part of the investigation response. No tab switching needed.
  • Summarize what changed: Autopilot reports the files touched and the added and deleted line counts for the PR that shipped the incident-adjacent deployment.
  • Follow-up questions in the same thread: Once a PR is on the record, you can ask Autopilot to compare it to the previous deployment or correlate the change with the failing signal. The GitHub context stays live in that investigation.
  • Works from any entry point: GitHub context flows into investigations triggered by an SRE alert destination, a Slack message, or the AI Chat panel. Autopilot brings in the PR automatically whenever a Change Tracking event with a commit SHA is present.
  • Read-only access via Personal Access Token: Autopilot uses your configured GitHub PAT scoped to Pull requests: Read, Contents: Read, and Metadata: Read. It never creates PRs, posts comments, merges branches, or stores source code. This preview supports public github.com only. GitHub Enterprise Server (self-hosted) and GitHub Enterprise Cloud are not supported yet.
  • Org-level setup: A New Relic organization manager connects GitHub once from Configure → Autopilot → External MCP connections. The PAT is encrypted at rest in the New Relic Secrets Service, isolated to your organization, and retrieved into request-scoped memory only for the duration of a single investigation.

Prerequisites: Active Autopilot setup, Change Tracking configured with commit SHAs flowing into New Relic, GitHub organization admin access to create a fine-grained PAT, New Relic org manager access, and the sre_agent_github_integration feature flag enabled on your account. Contact your New Relic account team to confirm the flag.

July 22
Autopilot 2.0

What's new

Autopilot 2.0: Remember What Matters, Investigate in Slack, and Scale to Every Account

  • Memories: give Autopilot lasting context

    • Autopilot now has the option to build a persistent knowledge base from your investigations, so you do not need to re-explain the same environment quirks, workarounds, and past incidents every session.

      • Save any Autopilot response to memory with a new button in the chat panel, memories can be saved that are specific to you, your account, or your organization, so useful findings persist instead of getting lost in chat history.
      • Autopilot recalls what it learned last time: if a past investigation determined that a recurring spike is expected behavior from a scheduled job, Autopilot applies that context to future analyses without requiring you to repeat it.
      • You control what's remembered: authorized users can view, search, and delete individual memory entries from the Memory Management UI at any time.
      • Access follows your role: organization managers can manage memory at the organization, account, and user level; other roles manage their own private memory and can view what's shared at broader scopes.
    • For more information about specific functionality and controls, see Autopilot Memories.

  • Get Autopilot Investigations in Slack with the Slack Integration

    • Stay in the Slack thread your team is already in: Mention the New Relic app in any channel you add Autopilot and Autopilot investigates right in the thread, so that you don’t have to bounce between Slack and the New Relic UI to triage an alert.
    • Triage alerts without retyping context: When New Relic posts an alert notification to a channel, replying with @New Relic is enough. The agent reads the notification to help identify the entity and the issue, so the first response remains focused on the target issue.
    • Keep the conversation going: Multi-turn investigations work in-thread, follow-up questions inherit the prior context, and every reply runs with the asking user's New Relic permissions.
    • Connect once, then move on: Linking your Slack identity to New Relic is a one-time step per workspace, and switching the New Relic organization tied to your Slack identity is a single click in the app's Home tab.
    • For more information about specific functionality and controls, see Autopilot Slack integration.
  • Other new features

    • Turn Autopilot on or off with one click. Organization managers can now easily turn Autopilot on or off for their organization using New Relic Feature Control.
    • Connect more accounts. Now Autopilot can correlate signals across more of your accounts instead of a subset of it.
    • Attach specific knowledge documents to a prompt with a slash command. Type the slash command in the Autopilot side panel to pull a specific runbook, retro, or postmortem into the prompt. Attached documents stay in scope for follow-up prompts until you remove them or end the session.
    • Autopilot is now the default agent in the chat panel, so you land in it automatically instead of having to switch to it.
    • Autopilot is available on HIPAA-designated accounts.
    • A redesigned investigation panel is rolling out, with a new header and homepage, inline context management, a reorganized history view, a fullscreen mode, and consistent icon and author styling throughout the conversation.
    • Configuration troubleshooting. Instead of a generic error message, you may now see a specific reason and a link to fix potential configuration issues, whether that's a missing entitlement, an account that isn't configured, or a required setup step.
    • Downstream-dependency root cause analysis: investigations can now help trace an issue to the services downstream of it, for accounts with Transactions 360 enabled.
  • Improvements and fixes

    • URL decoding: Fixed a class of failures where the agent couldn't determine the account ID from certain New Relic alert URL formats (including HURL state-encoded URLs).
    • Long-running investigation improvements. Requests that exceed the execution time limit now route to a summarizer instead of stalling, so you should receive a response even when an investigation runs long.
    • Fixed account resolution from certain alert URLs, including HURL state-encoded URLs, that previously prevented Autopilot from determining the correct account.
    • More accurate answers, with fewer wrong-account and wrong-entity mistakes: fixes corrected cases where a question about one account or entity could silently return results for a different one, where broad system questions only looked at the literally named service, and where health-summary responses cited correlations that weren't actually supported by evidence.
    • Fewer broken or garbled responses: fixes addressed responses rendering as raw text instead of formatted output, broken charts from bad account data, incorrect classification of unhealthy entities as healthy, and bugs that broke generated queries or crashed the panel.
    • Faster, more resilient responses under load: this release added retry logic for rate-limit errors, a faster model and timeout handling for simple queries, and graceful degradation so an investigation still returns results if an agent is unavailable.
    • Accessibility fixes to composer tooltips and controls in the chat panel.

June 11
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.

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