DEVOPS

Datadog p99 Tail Spike to PagerDuty Scaling Runbook

When Datadog detects a p99 latency spike that correlates with a saturation metric, this workflow pages on-call via PagerDuty with a pre-filled scaling runbook and the exact…

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDatadog p99 latency spike monitor firesDatadogDatadog
  • ActionQuery Datadog CPU and queue-depth saturation metricsDatadogDatadog
  • LogicConfirm saturation is the cause; exit if downstream dependency
  • ActionCompute recommended replica count from utilization headroom
  • OutputOpen PagerDuty incident with scaling runbookPagerDutyPagerDuty

What it does

Detects a p99 tail-latency spike in Datadog, confirms it is driven by resource saturation (not a downstream dependency), and pages the on-call engineer through PagerDuty with a ready-to-run scaling runbook that already contains the recommended replica count and the evidence behind it.

When to use it

Use it for latency-sensitive services where p99 regressions need a fast, decisive human response. The saturation check prevents false pages when slowness comes from an upstream API rather than your own capacity.

How it works

  1. 1A Datadog monitor fires on a p99 latency spike for the service.
  2. 2The flow queries Datadog for CPU and queue-depth saturation over the same interval.
  3. 3A logic branch confirms saturation is the cause; if the bottleneck is a downstream dependency, it exits without paging.
  4. 4It computes a recommended replica count from current utilization and headroom targets.
  5. 5It opens a PagerDuty incident with the runbook, recommendation, and metric links attached.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DatadogMetrics, traces, log search.
  2. 2
    Connect PagerDutyIncidents, on-call, escalations.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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