Honeycomb Advances Observability for AI-Powered Software Development

New time series Metrics, MCP expansions, and expanded capabilities for AI-assisted investigations position Honeycomb as the observability platform built for the agent era

SAN FRANCISCO, March 11, 2026 /PRNewswire/ -- Honeycomb.io, the creators of observability, today announced a series of new AI capabilities and two major product milestones, including the general availability of Honeycomb Metrics and the expansion of its Model Context Protocol (MCP) integrations across leading AI development tools. As AI agents become both primary contributors to and consumers of production software, these releases position Honeycomb as the first observability platform purpose-built for that reality — giving agents the structured data and direct platform access they need to monitor, debug, and optimize systems autonomously.

"Observability was built for a world where humans wrote the code and humans read the dashboards," said Graham Siener, SVP of Product at Honeycomb. "That world is changing fast. AI agents are writing more code, deploying more services, and increasingly need to understand what's happening in production themselves. We're building Honeycomb for that reality: where your AI coding agent can investigate a production issue with the same telemetry your best SRE uses, and where more code shipping faster doesn't have to mean more things breaking."

Pushing the Boundaries of Observability with AI
Honeycomb is launching a series of new AI capabilities designed to remove manual, time-intensive observability tasks and bring functionality closer to where customers work everyday. These capabilities include:

• Speed up migrations, onboarding, and production investigations with Honeycomb Agent Skills, now available for Claude Code, Cursor, and dozens of other agents. Migrate legacy telemetry to OpenTelemetry, get expert advice on instrumentation, and create boards, triggers, and SLOs during onboarding to Honeycomb.
• When an alert fires or an SLO burns, Honeycomb Automated Investigations jumps into action with the same playbooks and instincts your best SREs use. The capability is able to autonomously detect issues, conduct investigations, and recommend solutions.
• The new Honeycomb Slackbot brings Canvas into Slack, allowing you to use natural language to ask questions, investigate alerts, get summaries, and explore observability data. It also provides evidence-backed analysis with its 'Chain of Thought' logic to detail which tool calls were made, the exact parameters passed to those tools, and how the agent adjusted its plan when a specific tool output was unexpected or irrelevant.
• Honeycomb Pipeline Intelligence is an AI-powered feature designed to simplify telemetry pipeline creation and management at a time when AI-driven systems are generating observability data at unprecedented scale. It automatically detects log types, chooses appropriate parsers, and builds pipelines according to established best practices — handling the vast majority of the configuration work on its own. What previously required days of manual effort per log source can now be completed in minutes, with only minor adjustments left for engineers to fine-tune.

Building Fast Feedback Loops with Honeycomb Metrics
Traditional metrics-first tools rely solely on time series data and charge per time series. This approach is highly effective for monitoring infrastructure health at scale, but penalizes high-cardinality data and forces teams to leave out vital context like customer IDs, workspace identifiers, and vendor information.

Honeycomb Metrics now offers both time series and event-based models on one platform with a unified query experience, eliminating this tradeoff. Teams can seamlessly pick up existing OpenTelemetry metrics workloads in Honeycomb, and utilize event-based collection to capture all the custom metrics and dimensions they need without worrying about runaway costs, preserving the rich context that AI-powered investigations depend on.

"Before Honeycomb, our engineers kept having to choose between getting the data they needed and keeping costs under control," said an Engineering Leader at Notion. "Moving metrics to Honeycomb means we can continue collecting time series data for standard metrics, covering more than 100 million users. But we can also add the dimensions to events, like host IDs and container metadata, without worrying about cardinality-based billing blowing up."

With Honeycomb Metrics now generally available, Honeycomb gives engineers — and the AI agents working alongside them — seamless access to all telemetry data in one place.

Honeycomb MCP Goes Beyond Dashboards to Drive Evidence-Based Investigations
Honeycomb is expanding the capabilities of its MCP to embed observability directly into the AI-powered development and operations tools engineering teams already use.

"We know that quality and completeness of data matter in AI just like they do for human-powered investigations," said Steven Tan, Senior DevOps Engineer at Scribe. "The foundation that we've built with Honeycomb means not just that we get better answers with better context from our MCP-powered investigations, but also that engineers have more trust in the results and we can use them to make fixes and improvements."

Honeycomb MCP users are already seeing the benefits including:

• The CTO of a Fortune 500 retailer leveraged the MCP to get real-time Black Friday performance insights
• A top streaming service connected Honeycomb and Slack MCPs to surface root cause from internal support requests in minutes
• Engineering teams at a Global 2000 financial firm leveraged one-click integrations into their preferred IDE for instant analysis of AI generated code

Availability and Pricing
Honeycomb Metrics is generally available to all Honeycomb customers starting today. MCP expanded capabilities and Agent Skills for Claude Code, Cursor, the AWS DevOps Agent, and additional platforms are available now. Honeycomb Slackbot and Automated Investigations are available in early access.

Honeycomb is also introducing introductory promotional pricing for Metrics as low as $2 per 1,000 time series per month, helping organizations scale observability affordably as modern systems and AI workloads generate increasing telemetry volumes. Promotional pricing valid until the end of June 2026.

For more information, visit honeycomb.io.

More Resources

• Blog: Honeycomb Metrics is Generally Available
• Blog: Introducing the Honeycomb Slackbot (in Beta)
• Web: Honeycomb Metrics
• Web: Honeycomb Model Context Protocol (MCP)

About Honeycomb

Honeycomb is the futureproofed observability platform that enables engineering teams to find and solve problems they couldn't before. It unifies telemetry, returns fast queries, integrates with AI agents, and reveals issues others miss in your ever-evolving tech stack. Honeycomb's unique event-based pricing model provides a predictable way to ingest high-cardinality telemetry without penalties or hidden costs. Learn more at www.honeycomb.io and follow us on LinkedIn.

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SOURCE Honeycomb