ingestlayer/recipes

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

sourcesdk.eventTypeScript SDK
matcherror.spike

02pipeline · 2 steps

  • 01CTLfilter.matchenv = prod only
  • 02ENRclassifyseverity → page | notify | ignore

03destinations · 1

  • towarehouse.pgPostgres
    tableevents.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.

emit error.spike
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.

  1. 01

    add the connection

    Paste a Postgres connection string. Connections originate from our EU region — allowlist those egress IPs on your database.

  2. 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.

  3. 03

    map columns

    Match event fields to columns with $event.* references, or accept the default mapping into a typed events table.

in postgresdelivered
INSERT INTO events.signups
  (user_id, email, plan, source, payload)
VALUES
  ('u_018f', 'ada@acme.com', 'pro',
   'marketing-site', '{ … }'::jsonb);

notes

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.
build this pipelineor read the quickstart →

error spikes, routed elsewhere

more, into Postgres