Pagerstack collapses a wall of alerts into one page to one owner, opens the war room, pins the runbook, and writes the timeline while you fix it. Median acknowledge is 38 seconds — and the postmortem is half-drafted before the incident is resolved.
INC-4471 checkout error-rate > 5% SEV2 status: ACKNOWLEDGED
00:00 ⚡ 41 alerts collapsed → 1 incident (service: payments)
00:04 📟 paged @primary — on-call, payments squad
00:38 ✅ acknowledged (no escalation needed)
00:41 🔗 war room opened #inc-4471 · Slack + Zoom bridge live
00:43 📖 runbook pinned 'payments: high error-rate' (last used 11d ago)
00:52 🧭 likely cause surfaced deploy v2.31.0 shipped 14m before spike
02:10 👥 pulled in the db owner — one tap, already briefed
08:34 🟢 resolved rollback v2.31.0 · error-rate 0.2%
draft postmortem ready · timeline, responders & impact auto-filled
next: assign action items → owners + due datesPoint the monitors you already run at Pagerstack — no new agent on a single box
Most on-call tools just forward noise to a phone. Pagerstack decides who owns it, how loud to be, and what to do next — then keeps the record, so the 2 a.m. you and the 9 a.m. you are reading the same story.
Every alert is matched to the service that fired it and sent to that service's rotation — not a catch-all channel a dozen people half-watch. Ownership lives next to the service in a versioned catalog, so when teams reorg, paging follows automatically and nobody inherits a page for code they've never touched.
If the primary doesn't ack, Pagerstack climbs the chain — secondary, then lead, then manager — and quiets the channels it already woke. It respects working hours, follow-the-sun handoffs, and the engineer who's already heads-down on a different SEV1.
One bad deploy shouldn't fire 400 pages. Correlated alerts — same service, same release, same blast radius — collapse into a single incident, so you chase the cause once instead of acking the symptoms forty times.
Declare a SEV2 and Pagerstack spins up the Slack channel, the video bridge, and an incident-commander prompt in the same second — no hunting for the right link while the graphs are still red.
The runbook for this service and this failure mode surfaces inside the incident, stamped with when it was last used and a one-tap 'step done' so a handoff never loses its place.
What the rotation looks like once it runs on Pagerstack.
Burnout is a reliability risk. Pagerstack treats the on-call engineer as the scarcest resource on the team — and defends their attention like one.
Drag-and-drop rotations, one-tap overrides, and self-serve swaps that don't wait on a manager's approval. Coverage gaps surface before the week starts, not at 3 a.m. when the gap is already a page.
Low-severity alerts wait for morning unless they escalate. Sleep is protected by default, and every override is written to the log so the policy can't quietly erode.
Pagerstack tracks off-hours pages, ack latency, and back-to-back incidents per person, then flags the lead before a rotation grinds someone down — while there's still time to rebalance.
Pull in a teammate and they land already briefed — timeline, suspected cause, what's been tried. No 'can someone catch me up?' tax in the middle of the fire.
Every incident moves through the same arc — Pagerstack carries the context across all of it, so nothing gets re-explained and nothing falls between two people at a shift change.
Forty-one alerts from one bad deploy fold into a single incident. You see the cause, not a scrolling wall of duplicates fighting for attention.
The page lands on the payments rotation that owns the failing service — matched from the catalog, not broadcast to a channel and left for someone to claim.
Ack, and the war room is already live: Slack channel, video bridge, incident commander assigned, and the runbook pinned to the exact failure mode.
The suspect deploy is surfaced, the db owner is pulled in already briefed, the rollback ships, and error-rate drops to 0.2% — all on one timeline.
A draft postmortem is waiting — responders, impact, and suspected cause filled in. You add the contributing factors and assign action items, then close the loop.
Point your existing monitors at Pagerstack and you're live by the afternoon. No rip-and-replace, no proprietary agent on every box, no instrumentation rewrite.
Native ingest for Prometheus, Datadog, Grafana, CloudWatch, and Sentry, plus a signed webhook for everything that isn't on the list yet.
Acknowledge, escalate, and resolve from Slack or Teams. The bot keeps the channel and the incident timeline in lockstep, so the record matches the conversation.
Push, SMS, phone call, and email — every notify carries a delivery receipt, so a missed push always falls through to a ringing phone instead of silence.
Wire in your CI and Pagerstack pins the releases that landed right before the spike straight into the incident — the first suspect is in front of you on arrival.
Define rotations, escalation policies, and routing rules in Terraform. A coverage change gets reviewed in a pull request like the rest of your infrastructure.
Trigger, update, and close incidents programmatically with idempotent calls and a replayable event stream — so your own automation can drive the same flow.
“We went from 400 pages a week to under 150 in a month. Grouping alone handed the team back their nights — and now our SEV1s are acked before I've found my laptop in the dark.”
“The escalation logic just gets it. It pulled in our database owner already briefed, skipped the three people who couldn't have helped, and we'd shipped the rollback before the old tool would have finished its first round of paging.”
“Postmortems used to be a day of digging through Slack to reconstruct who did what, when. Now the timeline assembles itself and the retro is spent on fixes instead of forensics.”
You pay for the people who carry the pager — never per alert. Flooding the night with noise shouldn't cost you more; fixing it should cost you less.
For small teams putting their first rotation on call.
For engineering teams that live on the pager.
For regulated, multi-region, follow-the-sun orgs.
No. Pagerstack sits on top of what you already run. Point Prometheus, Datadog, Grafana, CloudWatch, Sentry, or a plain signed webhook at us and alerts start routing — no proprietary agent, no rip-and-replace, no instrumentation rewrite.
Dedup squashes identical alerts. Pagerstack correlates related ones — same service, same deploy, same blast radius — into a single incident, so a cascading outage becomes one page to one owner instead of four hundred. You fix the cause once instead of acking the symptoms.
Severity-aware routing and quiet hours. Low-severity alerts wait until morning unless they escalate, working hours are honored per person, and a fatigue score warns leads before a rotation burns someone out. Every override is logged so the policy stays honest.
An afternoon. Connect one alert source, import a schedule (or build one with drag-and-drop), set an escalation policy, and you're paging. Most teams run their first real incident on Pagerstack the same day they sign up.
Yes. Rotations, escalation policies, and routing rules all live in our Terraform provider and a signed API, so on-call changes get reviewed in a pull request like the rest of your infrastructure — no clicking through a UI to reorg coverage.
Pagerstack hands you a draft postmortem with the full timeline, every responder, the suspected cause, and customer impact already filled in. You add the contributing factors and assign action items with owners and due dates — the reconstruction is done for you.
Connect one alert source and run your next incident on Pagerstack. No demo gate, no credit card to start.