Incident to root cause.
Minutes, not days
ApexData SRE engineers + AI agents investigate incidents down to the exact line of code — while traditional SRE teams are still reading dashboards
Your team keeps things running.
We dig into why they break
🔔 Alert fatigue is real
Your on-call team restarts pods, rolls back deploys, puts out fires. But the root cause investigation? That gets queued for tomorrow. Or next sprint.
⏰ MTTR is measured in hours
The handoff from ops to dev, the context switching, the “can you reproduce it?” loop. Every hour is revenue, trust, and engineering time — lost.
📊 You're paying for dashboards, not answers
Datadog, Grafana, PagerDuty — they show symptoms. Red charts. But they don't tell you this:
→ sql.ErrNoRows — missing row in
subscription_platform table
Real incidents. Resolved in under 30 minutes
Every case below went from first alert to full incident report with root cause, code references, and remediation plan
Infinite Polling Loop Killing Production Node
What happened
A single user's failed payment triggered a reactive cascade in the frontend state management (Effector). The loop generated ~218 requests/second to backend API endpoints, pushing one production node to 78% CPU utilization. The service was running as a single replica — minutes from potential downtime for all users.
ApexData investigation
Product-powered SRE.
Not just people on call
ApexData SRE combines our AI observability platform with senior reliability engineers. The platform investigates. The engineer validates and acts
AI Detects Automatic
AI agents continuously analyze logs, traces, and metrics across your Kubernetes clusters. Anomalies are caught in real-time — often before users notice.
►AI found: “404s are normal. But you have
critical 500s on payment endpoints.”
AI Investigates Minutes
The AI agent traces the problem through your service mesh — from ingress logs to pod metrics to the specific function and line of code causing the issue.
→ 218 RPS from single user-agent
→ Effector reactive loop in checkout
→ file: upsell.ts, bypass of MAX_ATTEMPTS
Engineer Acts Human
Our SRE engineer reviews the AI-generated analysis, validates the root cause, and delivers an incident report with remediation steps to your team.
→ Root cause with file:line reference
→ Impact analysis + traffic patterns
→ 4-tier remediation plan
Not all SRE support is the same
| Traditional SRE | ApexData SRE | |
|---|---|---|
| Detection | Alert fires → human reads dashboard | AI continuously analyzes all signals, catches silent degradations |
| Investigation | Engineer manually checks logs, traces, metrics | AI traces through service mesh to the specific code path |
| Root cause depth | “The pod crashed” or “Memory spike” | solidgate_handlers.go:3179 — nil pointer dereference on *Order |
| Time to root cause | Hours to days | Minutes |
| Proactive detection | Only pre-configured alerts | AI finds anomalies you didn't alert on — silent failures, quota exhaustion, staging bugs |
| Knowledge retention | In engineer's head — lost on turnover | In the platform — survives team changes |
| Your team's visibility | Status page updates, weekly calls | Full platform access — your team sees what our engineers see |
Everything you need.
Nothing you don't
✦ What we do
✦ What we don't
Built on our own product.
Not stitched from OSS
Our SRE service runs on ApexData — the same observability platform your team gets access to. One platform, shared context, zero information silos
⚡ Zero-Instrumentation Setup
Connect your Kubernetes cluster — get infrastructure metrics, APM traces, and container health without touching your code.
🤖 AI Investigation Agents
Describe a problem in natural language, get root cause analysis. The agent builds the right dashboard for each incident automatically.
🔗 Dependency Mapping
Automatic real-time service topology. When something breaks, you see actual dependencies — not manually maintained diagrams.
👁 Shared Visibility
Your team sees exactly what our SRE engineers see. Same platform, same data, same dashboards. No black boxes.
Plans
Startup
- Company ≤ 3 years old
- Pre-seed / Seed stage
- ≤ 10 engineers
- ≤ 10 microservices
Essentials
- ≤ 25 engineers
- ≤ 30 microservices
Professional
- ≤ 60 engineers
- ≤ 60 microservices
Enterprise
- 60+ engineers
- 60+ microservices
From onboarding to ongoing
Connect & Deploy
ApexData deployed on your cluster with zero instrumentation. We map your services, dependencies, and business-critical paths. Integration with your Slack and communication channels.
Deep Dive
We learn your application architecture, business logic, and recurring pain points. Baseline performance metrics established. First proactive findings shared with your team.
24/7 Operations
Continuous AI-powered monitoring and incident detection. Immediate investigation and root cause analysis on every incident. Monthly reviews with trends and optimization recommendations.
