AI AGENTS
Axiom Log-Noise Clustering to Logging-Config PR
Weekly, an agent clusters high-volume Axiom log patterns, drafts sampling and drop rules for the noisiest low-value lines.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires the noise review
- ActionQuery 7 days of events from AxiomAxiom
- LogicCluster by template, rank by volume and cost
- LogicKeep high-volume, low-value candidates
- ActionOpen GitHub PR editing logging config with rules and savingsGitHub
- OutputPost PR link and projected savings to SlackSlack
What it does
This agent finds the log lines that cost the most and tell you the least, then proposes concrete config changes to suppress or sample them. It clusters raw Axiom events by message template, ranks clusters by volume and estimated ingest cost, and opens a GitHub pull request editing your logging configuration with the proposed sampling and drop rules plus a projected monthly savings estimate.
When to use it
Use it when your Axiom bill keeps climbing and most of the volume is repetitive debug or health-check chatter. Good for platform and SRE teams who want a reviewable, version-controlled way to trim log noise instead of ad-hoc dashboard edits.
How it works
- 1A weekly schedule fires the run.
- 2The agent queries Axiom for the past 7 days of events and aggregates them into message-template clusters with counts and byte volume.
- 3It scores each cluster by volume, cost, and signal value, then keeps only high-volume, low-value candidates.
- 4For each candidate it drafts a sampling ratio or drop rule and computes projected monthly savings.
- 5It opens a GitHub PR editing the logging config file with the rules and a savings summary in the description.
- 6It posts the PR link and headline savings number to Slack for review.
Set it up
What you configure once, before turning it on.
- 1Connect AxiomLog streams, queries, dashboards.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 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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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.