AI AGENTS

Honeycomb weekly latency-regression leaderboard

On a weekly schedule, an agent ranks the endpoints whose latency degraded most week-over-week in Honeycomb, writes a digest with likely causes.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly latency-leaderboard schedule fires
  • ActionQuery per-endpoint latency this week vs. lastHoneycomb
  • ActionRank endpoints by week-over-week regressionHoneycomb
  • LogicSplit top offenders from the rest
  • OutputPost ranked digest to SlackSlack
  • ActionOpen GitLab issues for worst endpointsGitLabGitLab

What it does

Gives engineering leadership a weekly view of where latency is quietly getting worse. The agent compares this week's per-endpoint latency to last week's in Honeycomb, ranks the biggest regressions, and produces a digest — posted to Slack for visibility and turned into GitLab issues for the top offenders.

When to use it

When slow creep matters as much as acute alerts and you want a regular, prioritized list of what to fix. Ideal for performance reviews, sprint planning, or a weekly reliability ritual.

How it works

  1. 1A weekly schedule triggers the digest run.
  2. 2The agent queries Honeycomb for per-endpoint latency this week and the prior week.
  3. 3It ranks endpoints by week-over-week regression to build a leaderboard.
  4. 4A branch separates the top offenders worth issues from the rest of the list.
  5. 5The agent drafts a digest with each regression's likely cause and posts it to Slack.
  6. 6It opens GitLab issues for the worst endpoints so they enter the backlog.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HoneycombDistributed traces and queries.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect GitLabRepos, MRs, pipelines, registry.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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