Monitor error spikes in Telegram
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
- totelegramTelegramchat@oncall
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 Telegram
Message a person, group, or channel through a connected bot.
- 01
connect a bot
Create a bot with @BotFather and paste its token. We register the webhook and verify it in-region.
- 02
start a chat
Send /start to the bot from the target chat — or add it to the group/channel — then pick the chat from the list.
- 03
format the text
Messages use MarkdownV2; the default template bolds the event name and lists fields. Reserved characters in field values are escaped for you.
oncall *support.ticket.created* ticket T-4821 subject API returning 500s tier enterprise urgency critical
notes
- Telegram caps a bot at roughly 30 messages per second overall, and one per second to a single chat.
- The bot must be added to a group — and promoted to admin for a channel — before it can post.
- MarkdownV2 requires escaping characters like _ * [ ] ( ); ingestlayer escapes field values, but custom templates are your responsibility.
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 EmailEmail
- Monitor error spikes in WebhookWebhook
- Monitor error spikes in PostgresPostgres
- Monitor error spikes in NotionNotion
more, into Telegram
- Track user signups in Telegramtrack
- Monitor failed payments in Telegrammonitor
- Route support escalations in Telegramalert
- Track waitlist signups in Telegramtrack
- Track new subscriptions in Telegramtrack
- Track canceled subscriptions in Telegramtrack
- Track successful payments in Telegramtrack
- Track trial conversions in Telegramtrack
- Track form submissions in Telegramtrack
- Track feature usage in Telegramtrack
- Track file uploads in Telegramtrack
- Monitor failed logins in Telegrammonitor
- Monitor usage-limit hits in Telegrammonitor
- Monitor cron-job health in Telegrammonitor
- Monitor CI/CD build status in Telegrammonitor
- Flag high-value leads in Telegramalert
- Catch churn-risk signals in Telegramalert
- everything you can pipe to Telegramhub