Checkly in Honeycomb Canvas: Bring Synthetic Checks In

Honeycomb has launched a Canvas connector for Checkly that integrates synthetic monitoring into its AI-powered incident investigation workspace, allowing the Canvas Agent to examine failing checks, locations, failure timing, status pages, and Checkly Rocky AI root-cause analyses alongside Honeycomb telemetry. Built on Checkly’s spec-compliant MCP server, the connector lets agents read monitoring data automatically while requiring user approval for actions such as rerunning checks, creating new checks, updating configurations, or starting analyses. The integration combines Honeycomb’s internal observability data with Checkly’s outside-in perspective from browser, API, and uptime checks across more than 20 locations, helping teams identify whether users experienced failures and why. In a demonstration using the OpenTelemetry Astronomy Shop, the agent correlated degraded catalog-service checks with hourly Playwright suites and traces, identifying resource contention on a shared machine as the cause of latency. Users can connect their Checkly account through Canvas without an API key, with access limited to each user’s existing permissions, while teams managing checks as code are advised to add Canvas-made changes back to their repositories to prevent later deployments from overwriting them.

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