DEVOPS

Cross-check Honeycomb burn against Datadog before freezing

When Honeycomb signals a fast burn, it pulls corroborating latency and error metrics from Datadog and only freezes deploys if both systems agree the service is degraded.

CategoryDevOps
Enginesim
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHoneycomb fast-burn alert webhookHoneycomb
  • ActionPull corroborating metrics from DatadogDatadogDatadog
  • LogicRequire both signals to agree on degradation
  • ActionApply deploy-freeze on the GitHub repoGitHubGitHub
  • OutputPost side-by-side signal summary to SlackSlack

What it does

This reduces noisy freezes by requiring two independent signals. A single Honeycomb burn alert can be triggered by a brief blip; this template confirms real degradation against Datadog's latency and error-rate monitors before it ever locks the repo, so the team only stops shipping when the problem is real.

When to use it

Use it if your burn-rate alerts have been too trigger-happy and engineers have lost trust in the freeze. The cross-signal check buys precision at the cost of a few seconds of confirmation.

How it works

  1. 1A Honeycomb webhook fires on a fast-burn budget alert.
  2. 2An action queries Datadog for the same service's recent latency and error-rate monitor state.
  3. 3A logic step requires both Honeycomb burn AND Datadog degradation to agree before proceeding.
  4. 4If confirmed, an action applies the deploy-freeze label and blocking check on the GitHub repo.
  5. 5The output posts a Slack message showing both signals side by side so the freeze decision is auditable.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HoneycombDistributed traces and queries.
  2. 2
    Connect DatadogMetrics, traces, log search.
  3. 3
    Connect GitHubRepos, issues, pull requests, actions.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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