Okta vs Honeycomb
Side-by-side trajectory, velocity, and editorial themes.
Okta's developer push is concentrated on Cross App Access and ISV-friendly low-code integrations.
The Okta developer surface is dominated by Cross App Access (XAA) content — protocol tutorials, an xaa.dev playground, and app-to-app connection guides — plus a recent OIN feature for ISVs called API Integration Actions and earlier work on entitlements. Cadence is roughly monthly. All recent posts are educational rather than product launches.
XAA is the centerpiece of the developer story. Okta is using the blog to seed an ecosystem around the spec while deepening ISV integration paths through Workflows-based low-code. An earlier MCP server hints at AI-agent identity interest, but the visible momentum is on XAA and OIN extensibility.
Expect more XAA enablement (partner-app tutorials, possibly a public-preview or GA milestone) and additional OIN features that push provisioning and entitlements toward AI-agent and ISV-tooling use cases.
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.
See more alternatives to Okta →
See more alternatives to Honeycomb →