OttoKit (the rebrand) hosts the workflow canvas in its cloud, but the plugin itself ships local tables. Every trigger fire writes a row to wp_suretriggers_logs with the trigger, the integration, the outcome, the duration, and the outgoing-call count. Version 1.1.4 added the Status / Clear-cache page that surfaces a status view.

That run data is the local source of truth for what your automations actually did. The plugin's Detailed Logs feature shows it row by row; the OttoKit dashboard groups it at the workspace level. Neither view answers operational aggregate questions, the outcome mix today, the runs-per-day cadence over the rolling window, the top integrations by failure rate, the total outgoing-call count this week.

SleekView Charts reads wp_suretriggers_logs directly and renders four cards on one dashboard. Total runs today as a number, outcome distribution as a donut, runs per day as an area, and top integrations by failure count as a bar. Automation ops happens without a cloud login.

Most automation platforms keep their run history in the cloud, which is fine until ten teams each need to know whether a particular workflow fired correctly in the last hour. OttoKit is unusual in that it writes the run log to local WordPress tables, and that locality changes the operational posture. You can run SQL against the data, you can join it to other WordPress tables, and you can audit it without a workspace login.

The day-to-day friction is that the plugin's native UI was built around drill-downs into single events rather than around the dataset as a whole. An operator chasing the daily outcome distribution, the runs-per-day cadence, or the top failing integration wants charts, not a paginated log. SleekView Charts treats wp_suretriggers_logs as the operational primitive it already is and renders the aggregate answers as cards.

The donut shows the outcome mix. The area shows the cadence. The bar shows the failure ranking.

The number anchors the day.