Honeycomb vs Rootly
Side-by-side trajectory, velocity, and editorial themes.
Honeycomb is rebuilding observability around an autonomous investigation surface called Canvas.
Every meaningful release in the last quarter rolls up to one product motion: Canvas, an agentic investigation surface that Honeycomb is propagating across the entire product. The May 20 launch turned Canvas into a multiplayer workspace where humans and AI agents investigate together, with auto-investigations that kick off when triggers fire, GitHub-grounded analysis, custom skills for runbook knowledge, and a Slack app. Around the headline launch, Honeycomb shipped BubbleUp Insights (AI-summarized anomaly diffs), a Gen-AI tab in trace view, Query Math, dark mode, and earlier beta surfaces of Ask Canvas and Slack Canvas that the big release now consolidates.
Honeycomb is repositioning from 'query your telemetry' to 'investigate with agents that know your system.' Canvas is the through-line: it shows up on Home, in Slack, in alert flows, in traces. The Gen-AI trace tab and BubbleUp Insights point at a parallel bet - that the kind of system worth observing increasingly includes LLM-powered apps, and the observability tool has to speak that language natively. Together this is a category-redefining move on the AI-native ops front, where competitors are still bolting chatbots onto dashboards.
Expect Canvas to keep absorbing surface area: deeper IDE/GitHub integration so investigations can suggest or open PRs, marketplace-style sharing of custom skills, and Canvas access via MCP so agents in other tools can query Honeycomb directly. The next spark will likely be Canvas writing back to the system - e.g., proposing config changes or runbook edits from what it learned.
Rootly is moving the incident workflow out of the dashboard and into the IDE.
Rootly is shipping steadily across three lanes: on-call ergonomics (SLA follow-ups, deferred paging, team heartbeats), AI surfaces (Claude Code and Cursor plugins), and enterprise plumbing (Google Workspace directory sync, deeper RBAC). The cadence is roughly one release per week and the changes are coherent rather than scattershot — each lane is building toward a recognizable end-state.
The on-call work is a maturation arc: features that used to be coarse (paging, heartbeats, follow-ups) are gaining ownership, scheduling, and SLA awareness. The AI work is the more interesting axis — pulling on-call context, retros, and incident state into Claude Code and Cursor signals that Rootly wants engineers to interact with the platform inside their editor, not by tabbing away to a separate UI.
Expect the IDE plugins to gain write-side actions next (acking pages, drafting retros, triggering runbooks from the editor), and on-call configuration to keep moving toward team-scoped, RBAC-aware defaults rather than global ones.
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