DEVOPS
P95 Latency Breach to Vercel Autoscale Recommendation
When Honeycomb reports a sustained p95 latency breach on a service, this workflow correlates request volume and recommends a concrete Vercel scaling change.
How it runs
The automated pipeline, trigger to output.
- TriggerHoneycomb p95 SLO breach trigger firesHoneycomb
- ActionQuery Honeycomb for request rate and p95/p99 over windowHoneycomb
- LogicCompute recommended instance count from latency-to-throughput ratio
- ActionRead current Vercel scaling config to compute deltaVercel
- OutputPost scaling recommendation to Slack for approvalSlack
What it does
Watches a Honeycomb p95 latency trigger for a named service, pulls the matching trace window, and turns the signal into a specific, human-readable scaling recommendation (target instance count and reason). It never auto-applies — it posts the recommendation to Slack with the supporting numbers so an on-call engineer approves the change.
When to use it
Use it when your service runs on Vercel and you want autoscaling decisions driven by real tail-latency data instead of CPU averages. Ideal for teams that want a human in the loop but are tired of eyeballing dashboards during traffic spikes.
How it works
- 1A Honeycomb trigger fires when p95 latency for the service stays above the SLO threshold for the configured window.
- 2The flow queries Honeycomb for request rate and p95/p99 over the same window to size the load.
- 3A logic step computes a recommended instance count from current concurrency and the latency-to-throughput ratio.
- 4It reads current Vercel deployment scaling config to compute the delta.
- 5It posts the recommendation, current vs. proposed settings, and trace link to Slack for approval.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect VercelDeploys, runtime logs, analytics.
- 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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