One SRE Full-stack reliability
When you're a 2-person SRE team responsible for a 40-service AWS architecture, you don't need more dashboards. You need Opsphere — an AI system that does the observability thinking, so your team can do the engineering.
THE OPERATIONAL PAIN
Small teams are asked to do impossible things
You're expected to triage 200 alerts a day, maintain 14 dashboards nobody reads, and still ship product features. The tools weren't built for teams your size — they were built for enterprises with dedicated NOCs.
"We have 3 monitoring tools, 14 dashboards, and a Slack channel that fires 200 alerts a day. We still found out about last week's outage from a customer tweet."
— Head of Engineering, 60-person SaaS Startup
The 2am rotation is destroying your team
On-call isn't a badge of honour — it's a burnout engine. When every alert pages the same two people, nobody does prevention work.
You're reactive, not proactive
You spend 80% of your time fighting fires and 20% on work that prevents them. The ratio should be the other way around.
Tooling complexity is crushing velocity
Datadog, PagerDuty, Terraform state, AWS Console — four tabs, zero correlation. Your team became tool operators instead of engineers.
HOW OPSPHERE SOLVES IT
An AI SRE that never sleeps, never misses context
Opsphere acts as an intelligent layer between your infrastructure signals and your team — correlating, prioritising, and resolving, so you get paged for things that matter.
AI-Driven Noise Reduction
Opsphere learns your infrastructure topology and suppresses correlated alerts automatically. 200 alerts become 3 actionable incidents.
Automatic Root Cause Analysis
When an incident fires, Opsphere traces the dependency graph across AWS, Vercel, and your services — surfacing the actual root cause, not the loudest symptom.
Context-Aware Runbook Generation
Every incident generates a runbook tailored to your stack, your services, and your team's past resolutions. No more generic wiki pages.
Proactive Anomaly Prediction
Opsphere detects degradation patterns before they become outages — giving your 2-person team the early warning a 20-person NOC would provide.
BEFORE / AFTER OPSPHERE
- 200 alerts / day
- Manual triage
- 3 separate tools
- 2am wake-ups
- 87min avg MTTR
- Reactive culture
- 3 incidents / day
- AI-triaged
- One unified view
- Smart escalation
- 14min avg MTTR
- Proactive ops
SCENARIO WALKTHROUGH
A Tuesday incident. Resolved before breakfast.
Here's how a 2-person SRE team at a 60-person startup uses Opsphere to handle a cascading production incident without drama.
Scenario: Multi-service degradation on prod
Tuesday 03:22 UTC — payment service response times spiking, downstream impact spreading to checkout and order APIs
- 03:22
Opsphere detects the anomaly
Correlated signals across payment-api, checkout-service, and order-worker. No human opened a dashboard.
⚡ 12 seconds to context build
- 03:22
Single, prioritised page sent to on-call
One Slack message with root cause hypothesis, affected services, and suggested first action. Not 40 separate alerts.
✅ 1 page instead of 40 alerts
- 03:22
Engineer opens pre-built runbook
Steps specific to this service topology: scale payment-api replicas, check Vercel edge cache, verify Stripe webhook queue.
📋 Runbook ready before first Slack reply
- 03:22
Incident resolved — systems normal
MTTR: 9 minutes. Postmortem draft auto-generated with timeline, root cause, and prevention recommendations.
🎉 9-minute MTTR · Zero customer escalation
READY?
Your team deserves a smarter way to operate.
Start free. Connect your stack in minutes. Sleep through the night.