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Beta Experiences

As part of our beta program, our users can explore newly developed product capabilities while providing feedback. Beta releases may be restricted to a select number of Honeycomb users (private) or open to all Honeycomb users (public).

If you would like to participate in a beta, contact your account representative or Honeycomb Support.

Metrics 2.0 

Type: Private
Dates: mid-July–December 2025

Metrics 2.0 is a major update to Honeycomb’s metrics experience, built to align with the OpenTelemetry specification for metric types and behaviors. This upgrade introduces a more expressive query model, advanced temporal functions, and full support for alerting via Triggers.

This update enables:

  • OpenTelemetry Metric Type Support: Native support for gauges, cumulative and delta sums, and histograms.
  • Temporal Aggregation Functions: Use RATE(), INCREASE(), SUMMARIZE(), and LAST() to get deeper insight into your time series data.
  • Automatic Aggregation Defaults: Honeycomb chooses the appropriate temporal aggregate based on the metric type—no manual tuning required.
  • Query-Scoped Calculated Fields for Metrics: Apply temporal calculations directly in your queries without changing your dataset schema.
  • Trigger Support for Metrics: Build alerts from metric queries and configure thresholds, evaluation frequency, and notification delivery method.
  • Native Histogram Support: Histograms are stored as distributed structures, enabling accurate percentiles and flexible merging across time and groups.

To explore the beta in more depth, check out the Metrics 2.0 Beta Enablement Guide.

We’d love your feedback, especially on usability, results, and any rough edges you encounter! To opt in or share feedback:

Model Context Protocol (MCP) 

Type: Public
Dates: In progress

The Model Context Protocol (MCP) enables AI assistants to directly interact with your Honeycomb observability data through natural language. This open standard allows seamless communication between AI models and Honeycomb, transforming how you investigate issues and analyze system behavior.

With MCP, you can:

  • Query trace, metric, and log data using natural language like “Show me the slowest endpoints today”
  • Automatically generate complex queries without manual syntax
  • Create visualizations and boards through conversational AI
  • Analyze patterns and anomalies with AI-powered insights
  • Build automated workflows that respond to system events

MCP maintains context across interactions, enabling sophisticated multi-step investigations that would typically require deep Honeycomb expertise.

To explore the beta in more depth, check out our Honeycomb Model Context Protocol (MCP) documentation.

We’d love your feedback on the AI integration experience, query accuracy, and use cases you discover! To opt in or share feedback:

Activity Logs 

Type: Public
Dates: In progress

Want to see how your teammates are using Honeycomb? Activity logs give you visibility into changes made to key resources in your environment—whether by a person or an automated process.

With activity logs, you can track updates to:

  • User logins, including authentication and IP address changes
  • Calculated fields (otherwise known as Derived Columns), including when they’re created, updated, or deleted
  • Service Level Objectives (SLOs), including creation, update, deletion, resets
    • Service Level Indicator (SLI) expression, including updates
  • Triggers, including creation, update, deletion, and state changes to or from Triggered
  • Query results, including creation
  • API keys, including creation, update, and disabling
  • Burn alerts, including creation, update, deletion, and state changes to or from Triggered

Your team can explore this data in a dedicated Activity Log Environment, which includes a set of datasets that capture activity for each resource type. Within this environment, you can use all of Honeycomb’s features—like queries, visualizations, Boards, and Triggers—to investigate activity and uncover patterns or issues.

Text Panels on Boards 

Text Panels let you add narrative context directly to a board, alongside your queries. Use them to explain what the data means, highlight key insights, or link to runbooks and playbooks so your team knows what action to take.

You can format Text Panels with Markdown, making it easy to structure and style your content with headings, lists, links, code blocks, and more.

This feature is in beta. While in beta, we may make changes to functionality or presentation based on feedback. We’d love to hear how you’re using Text Panels and what would make them more useful—please share your feedback with us.

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