DATA OPS
Axiom and Datadog Cross-Check Spike Triage Agent
On an Axiom cost-spike webhook, an agent pulls the spiking service's logs from Axiom and its metrics from Datadog to decide whether the volume came from a real incident or pure…
How it runs
The automated pipeline, trigger to output.
- TriggerAxiom cost-spike monitor webhookAxiom
- ActionQuery Axiom spiking log lines and levelsAxiom
- ActionQuery Datadog error rate and trafficDatadog
- LogicAgent decides incident vs log noise
- ActionCreate labeled Linear ticket with evidenceLinear
- OutputPost verdict and link to SlackSlack
What it does
Distinguishes a meaningful spike from wasteful noise. When Axiom flags a cost jump, an agent correlates the log surge with Datadog error-rate and traffic metrics for the same service and window, then decides: real incident worth investigating, or just logging waste worth cleaning up. It opens a Linear ticket of the matching type.
When to use it
Use it when not every ingest spike deserves an incident. Cross-checking metrics avoids paging people for a debug-log leak while still routing genuine error storms to the right queue.
How it works
- 1An Axiom monitor webhook fires on a detected cost spike for a service.
- 2The agent queries Axiom for the spiking log lines and their levels in the window.
- 3It queries Datadog for the service's error rate, latency, and request volume over the same window.
- 4The agent reasons over both: a metrics anomaly means incident, flat metrics with high log volume means noise.
- 5It creates a Linear ticket, labeled incident or log-cleanup, with the correlated evidence and a recommended next step.
- 6It posts the verdict and ticket link to the on-call Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect AxiomLog streams, queries, dashboards.
- 2Connect DatadogMetrics, traces, log search.
- 3Connect LinearIssues, projects, cycles, triage.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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