DEVOPS
Axiom Spike Responder: AI Agent Decides Rollback vs Mute, Files the Task
On a sharp Axiom ingest spike, an agent investigates whether the chatty deploy is safe to roll back or whether the logger should just be muted.
How it runs
The automated pipeline, trigger to output.
- TriggerAxiom ingest-spike webhook hands context to agentAxiom
- ActionFetch suspect Vercel deploy and its GitHub diffGitHub
- ActionClassify new Axiom volume: errors vs debug noiseAxiom
- LogicAgent decides rollback candidate vs hygiene fix
- OutputPage PagerDuty for rollback or open GitHub hygiene issuePagerDuty
What it does
Adds judgment to spike response. An agent reads the spike, inspects the suspect deploy's diff, and reasons about whether rolling back is warranted or whether the noise is benign and the logger should be quieted. It then routes to the right channel with its rationale attached.
When to use it
Use it when blind automation is risky and pure alerting is too slow. Best for mature teams that want a documented recommendation, not just a notification, when log costs spike unexpectedly.
How it works
- 1An Axiom monitor webhook fires on a sharp ingest spike and hands context to the agent.
- 2The agent queries Vercel for the suspect deploy and pulls its GitHub diff to understand what changed.
- 3It cross-checks Axiom for whether the new volume is errors and warnings versus debug or info noise.
- 4A logic branch routes on the agent's call: error-driven volume escalates as a rollback candidate, noise-driven volume becomes a hygiene fix.
- 5For rollback it pages PagerDuty with the SHA and evidence; for noise it opens a GitHub issue with the mute recommendation and reasoning.
Set it up
What you configure once, before turning it on.
- 1Connect AxiomLog streams, queries, dashboards.
- 2Connect VercelDeploys, runtime logs, analytics.
- 3Connect GitHubRepos, issues, pull requests, actions.
- 4Connect PagerDutyIncidents, on-call, escalations.
- 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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