Monitor error spikes in Postgres
Turn a sudden burst of one error into a single, classified alert — production only, severity already decided — instead of a wall of duplicate noise.
01source
02pipeline · 2 steps
- 01CTLfilter.matchenv = prod only
- 02ENRclassifyseverity → page | notify | ignore
03destinations · 1
- towarehouse.pgPostgrestableevents.signups
the event
You emit error.spike with this shape. The TypeScript SDK keeps the call type-safe, and the event is stored whole — so every field below is available to the pipeline by name.
- servicestring
- errorstringerror class
- countnumberin window
- windowstringe.g. 5m
- envstringprod | staging
emit it
From your code with the TypeScript SDK — or any language over the REST endpoint and signed webhook ingress.
import { ingest } from "@ingestlayer/sdk";
await ingest("error.spike", {
service: "checkout",
error: err.name,
count: windowCount,
window: "5m",
env: process.env.NODE_ENV,
});route it to Postgres
Insert each event as a row into a table in your own Postgres.
- 01
add the connection
Paste a Postgres connection string. Connections originate from our EU region — allowlist those egress IPs on your database.
- 02
point at a table
Name the target table. Top-level event fields map to columns, and the full payload is also available as a jsonb column.
- 03
map columns
Match event fields to columns with $event.* references, or accept the default mapping into a typed events table.
INSERT INTO events.signups
(user_id, email, plan, source, payload)
VALUES
('u_018f', 'ada@acme.com', 'pro',
'marketing-site', '{ … }'::jsonb);notes
- The target table must already exist with compatible column types; ingestlayer never runs DDL on your database.
- Connections come from fixed EU egress IPs — add them to your firewall, or inserts will time out.
- Use a jsonb column for the full payload when your event shape changes often, so a new field never breaks the insert.
questions
- Can staging stay out of the on-call channel?
- Filter on env so only production spikes page anyone; staging can route to a quieter place or nowhere.
- How is severity decided?
- classify weighs the error class and count against your prompt and returns a typed severity the pipeline branches on.
- Will one bad minute spam the channel?
- You emit one spike event per window, so a burst is summarized as a count rather than streamed error by error.
error spikes, routed elsewhere
- Monitor error spikes in SlackSlack
- Monitor error spikes in DiscordDiscord
- Monitor error spikes in TelegramTelegram
- Monitor error spikes in EmailEmail
- Monitor error spikes in WebhookWebhook
- Monitor error spikes in NotionNotion
more, into Postgres
- Track user signups in Postgrestrack
- Monitor failed payments in Postgresmonitor
- Route support escalations in Postgresalert
- Track waitlist signups in Postgrestrack
- Track new subscriptions in Postgrestrack
- Track canceled subscriptions in Postgrestrack
- Track successful payments in Postgrestrack
- Track trial conversions in Postgrestrack
- Track form submissions in Postgrestrack
- Track feature usage in Postgrestrack
- Track file uploads in Postgrestrack
- Monitor failed logins in Postgresmonitor
- Monitor usage-limit hits in Postgresmonitor
- Monitor cron-job health in Postgresmonitor
- Monitor CI/CD build status in Postgresmonitor
- Flag high-value leads in Postgresalert
- Catch churn-risk signals in Postgresalert
- everything you can pipe to Postgreshub