ENGINEERING
Hourly Honeycomb error-budget scan to GitLab issue
On an hourly schedule, queries Honeycomb for services burning their error budget faster than target and opens a GitLab issue for each newly-breaching service with the burn rate…
How it runs
The automated pipeline, trigger to output.
- TriggerHourly scheduler runs the budget scan
- ActionQuery Honeycomb for per-service error-budget burn rateHoneycomb
- LogicKeep only newly-breaching services without an open issue
- ActionFetch representative trace exemplars from HoneycombHoneycomb
- ActionOpen a GitLab issue per breaching serviceGitLab
- OutputPost a summary of new issues to engineering SlackSlack
What it does
Proactively catches slow-burn error budget violations that never trip a single sharp alert, by sweeping Honeycomb every hour and filing a GitLab issue the moment a service crosses its burn-rate target.
When to use it
Use it when you run SLOs in Honeycomb and want budget-burn regressions tracked as engineering work rather than dashboard-only signals. Good for teams where GitLab is the dev workflow home and gradual degradation matters as much as spikes.
How it works
- 1A scheduler runs the flow at the top of every hour.
- 2The flow queries Honeycomb for each monitored service's current error-budget burn rate over the trailing window.
- 3A logic step keeps only services whose burn rate exceeds target and that don't already have an open burn-rate issue.
- 4For each newly-breaching service it pulls a few representative trace exemplars from Honeycomb.
- 5A GitLab issue is opened per service with the burn rate, budget remaining, trace exemplar links, and the SLO definition.
- 6A summary of all new issues is posted to the engineering Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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.
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