AI AGENTS

On-Call Agent: Postgres Saturation Webhook to Query Culprit Mitigation Plan

A webhook fired by a Postgres connection or load saturation alert triggers an agent that inspects active and slow queries, identifies the culprits.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps4
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSaturation webhook receivedHTTP webhook
  • ActionInspect active and slow queries in PostgresPostgreSQLPostgres
  • LogicRank query culprits and map to mitigations
  • OutputPost approval-gated mitigation plan to SlackSlack

What it does

Handles database saturation incidents specifically. When connections or load spike, the agent looks directly at what the database is doing — long-running and blocking queries, lock waits, connection counts — and proposes targeted mitigations rather than generic restarts.

When to use it

Use it when your most painful incidents are database pressure events and you need to know *which* query or client is the problem before deciding to kill a session, add an index, or throttle a caller. Read-only inspection plus human-approved action.

How it works

  1. 1A monitoring system posts a webhook when Postgres connection or load saturation crosses threshold.
  2. 2The agent runs read-only inspection queries against Postgres for active statements, slow queries, lock contention, and connection counts.
  3. 3Logic ranks the culprits by impact and matches each to a candidate mitigation — terminate a runaway session, add a missing index, or rate-limit a noisy client.
  4. 4It assembles a mitigation plan with the supporting evidence for each recommendation.
  5. 5The agent posts the plan to Slack with each action gated behind approval; nothing is terminated or changed until an operator signs off.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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