AI AGENTS
Axiom Spike to GitHub Deploy Correlation
When Axiom ingest spikes, an agent correlates the timing with recent GitHub deploys, identifies the likely culprit PR that added logging.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled ingest-spike detection
- ActionPull spike window and noisy fields from AxiomAxiom
- ActionFetch recent merged PRs and deploy times from GitHubGitHub
- LogicMatch spike onset to closest logging-related PR
- ActionAgent assembles evidence and proposed fixOpenAI
- OutputComment proposed fix on the culprit PRGitHub
What it does
Connects log-cost spikes to the code change that caused them. On an ingest spike, the agent lines up the spike timestamp against recent merges and deploys, finds the pull request that most likely introduced the chatty logging, and posts a comment on that PR with the volume evidence and a suggested change (lower log level, structured field removal, or sampling).
When to use it
Use it when spikes are usually caused by a freshly shipped change and you want the feedback to land on the exact PR while context is still fresh, instead of a vague team-wide warning.
How it works
- 1A scheduled check detects an Axiom ingest spike over baseline.
- 2The agent pulls the spike window and the noisiest new fields from Axiom.
- 3The agent fetches recent merged PRs and deploy timestamps from GitHub.
- 4A logic step matches the spike onset to the closest deploy and confirms the PR touched logging code.
- 5The agent comments on the culprit PR with the cost evidence and a proposed log-level/sampling fix.
Set it up
What you configure once, before turning it on.
- 1Connect AxiomLog streams, queries, dashboards.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect OpenAIModels, embeddings, files.
- 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.
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