Meet Optimus — the AI-SRE that sees incidents coming
Observability on Your Terms, Built for engineering Stack.
Monster is the software-reliability platform that detects incidents the moment they start, runs the response through AI, and closes the loop to detection, on-call, war-room, status pages and retros in one command deck.
SOC 2 Type II · SSO & SAML · deploys in your own cloud
Monster · Command Overview
1 SEV1 · DETECTED IN 8s
Services healthy
42/45
Open incidents
1
MTTR · 30d
9m
Caught pre-page
91%
Service fleet · live heartbeat
checkout-api
OK
payments-svc
DOWN
ledger
DEGR
identity
OK
The reliability layer for teams that can't afford downtime
NORTHWINDApertureMERIDIANVantageHALCYONUmbral
Representative placeholders — swap for your customer logos.
One platform, first signal to final fix
Most tools wait to be told. Monster already knows.
Response platforms only start working after another monitor pages you. Monster watches your stack itself — so detection, response, and prevention live in one place, and every incident makes the next one shorter.
Detect
See it before it pages you
Optimus learns the normal shape of every service and flags the anomaly the instant it starts — often before a single customer is affected. No threshold spelunking, no alert fatigue.
Anomaly models across latency, errors, saturation and queues
Auto-opens and severity-grades the incident
Self-heals the noise — pages only what matters
Explore Detection
AI anomaly radar
pre-page detection
92%payments-svc · connection pool exhaustion−8s
78%ledger · write latency +180%watch
healsearch · retry blip auto-resolved22s
okcheckout-api · nominal142ms
Respond
Run the whole response from one command deck
The war-room opens itself with roles, a live timeline, and an AI-SRE co-pilot that proposes the root cause and the fix — with the evidence to back it. No swivel-chairing between six tools while the clock runs.
Root-cause hypothesis with confidence and evidence
One-click mitigations: rollback, scale, drain
Every action captured to the timeline, Slack-native
Explore Response
Optimus AI-SRE
89% conf.
Root-cause hypothesis
payments-svc@v2.48 moved the fraud check inside the checkout transaction — each request now holds a pooled DB connection across an outbound call, exhausting the pool.
Roll back payments-svc@v2.48
reverts to v2.47.3 · ~90s
Run ›
Bump connection pool 50 → 120
stopgap while rollback ships
Review ›
Page
The right person, every time
Schedules and escalation policies route each alert to whoever's actually on — across regions and time zones — and Optimus filters the noise so your rotation doesn't burn out.
Follow-the-sun schedules with cover requests
Escalation policies with phone, push and Slack
Noise suppression keeps pages meaningful
Explore On-call
On-call schedule
Mon 27 · 10:29
EUR
Maya Chen
AMER
Diego Ruiz
APAC
Priya Shah
Inform & learn
Keep everyone posted, then get sharper
Your status page updates itself from detection — customers hear it from you first. When it's over, Optimus drafts the retro from the real timeline, so the follow-ups actually get written.
Public & private status pages, auto-updated
AI-drafted postmortems from the war-room
Owned follow-ups + a learnings library
Explore Status & Retro
Public status page
Partial outage
Checkout & WebOperational
PaymentsDegraded
Powered by Optimus
A living model of your production
Optimus is built from your telemetry, deploys, code and incident history — so when something breaks, it already understands your systems the way your best engineer does.
Sees every service, deploy and dependency in real time
Reasons across telemetry, deploys, code and past incidents
Challenges its own root cause with an adversarial check before paging
Learns your systems — every incident makes it sharper
Stop waiting to be paged.
Put Monster on your stack and see the next incident before your customers do.