SUMMARIZATION
Daily Honeycomb p99 spike digest written for non-engineers in Notion
Every morning, scans Honeycomb for the worst latency spikes from the prior day, picks the slowest representative trace for each.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled run each morning for the prior 24 hours
- ActionPull p99 latency by endpoint with representative trace IDsHoneycomb
- LogicKeep only endpoints that breached their latency threshold
- ActionFetch span waterfalls for each surviving traceHoneycomb
- ActionWrite a per-endpoint plain-English spike summaryOpenAI
- OutputAppend the dated digest to a Notion pageNotion
What it does
Each morning it looks back over yesterday's traffic in Honeycomb, finds the endpoints whose p99 latency spiked, grabs a representative slow trace for each, and turns the whole picture into a readable digest in Notion. Product and leadership get a standing record of where the app felt slow, in language they can act on.
When to use it
Use it when leadership wants a recurring, low-effort pulse on performance without learning Honeycomb. It replaces the weekly 'how's latency?' Slack thread with a dated Notion page anyone can skim.
How it works
- 1A scheduled trigger fires every morning for the previous 24 hours.
- 2Honeycomb returns p99 latency by endpoint plus the slowest trace ID behind each spike.
- 3A logic step filters to endpoints that breached their threshold and drops the noise.
- 4For each survivor, Honeycomb fetches the span waterfall of its representative trace.
- 5OpenAI writes one short paragraph per endpoint: what got slow, by how much, and the likely culprit span in plain terms.
- 6The combined digest is appended as a dated entry on a Notion page.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Summarization workflows
On-submit Loom standup roll-up archived to Confluence
When a standup video is submitted via webhook, transcribes it, generates a per-person written summary, and appends it to a running team standup page in Confluence.
Front Escalation Handoff Doc in Notion
When a Front escalation closes, drafts a structured handoff document in Notion capturing the resolution, customer commitments, and open follow-ups, then alerts the AE in Slack.
Front Escalation War-Room Brief to Slack
On a Front escalation, posts a concise threat-assessment brief to a Slack channel only when the AI judges the situation high-severity.
VIP Front Escalation Instant Exec Page-Out
Detects escalations from VIP accounts in Front, generates a one-paragraph executive recap, and pages the named account exec via Slack and Salesforce task within minutes.
Release health note per Vercel deploy
When a Vercel deploy goes live, summarizes the Sentry errors observed in the release window into a plain-English health note that separates brand-new error classes…
Rollback recommendation when a deploy spikes errors
When a Sentry alert fires for an error spike, attributes it to the most recent deploy, summarizes whether the spike is dominated by new error classes introduced by that release.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.