ApexData
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AI-Powered SRE Service

Incident to root cause.
Minutes, not days.

ApexData SRE engineers investigate incidents down to the exact line of code — while traditional SRE teams are still reading dashboards.

Book a DemoSee Real Incidents
✕Traditional SRE
4–24 hrsMean time to resolve
  • 0:00Alert fires
  • 0:10On-call triages
  • 0:30Escalation to dev team
  • 2:00Dev investigates logs
  • 4:00Root cause hypothesized
  • 8:00+Fix deployed & verified
Escalates through 3 teams
32×
faster
AI-POWERED
⚡ApexData SRE
< 30 minMean time to resolve
  • 0:00AI detects anomaly
  • 0:03AI traces to root cause
  • 0:05Engineer validates
  • 0:10Incident report with code ref
  • 0:15Remediation delivered
One engineer validates. Done.
<30mMean time to root cause
Line:3179Exact code location identified
10xFaster than manual investigation
24/7Always-on SRE coverage
LIVE · payment-service · root cause found in 4m 12s RESOLVED · api-gateway · latency spike traced to redis-cluster:6379 RESOLVED · auth-service · OOM at user-session.js:882 · 22 min
The Problem

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.

Avg. 847 alerts/day per team

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.

3 days industry avg MTTR

You're paying for dashboards,
not answers

Datadog, Grafana, PagerDuty — they show symptoms. Red charts. But they don't tell you this:

handlers.go:318 → GetPlatformIDByCode("apple")
→ sql.ErrNoRows — missing row in
subscription_platform table
Case Studies

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

Severity: HighResolved in ~23 min
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
  1. +0:00CPU alert triggered on prod-node-k8s-07
  2. +0:08AI correlated CPU spike with pod app-backend at 511m CPU, traced anomalous 218 RPS to single Opera GX user-agent
  3. +0:16Cross-referenced access logs and pinpointed single user from Portugal, two endpoints: /api/profile/metadata + /api/payments/upsell/check-purchased
  4. +0:24Root cause confirmed: Effector reactive loop — failed attempt handler bypasses MAX_FAIL_ATTEMPTS safety limit. Full remediation report delivered
What makes this different

A traditional SRE team would have restarted the pod and moved on. The infinite loop would have triggered again with the next failed payment. We found the architectural bug.

Read Full Report
The platform

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.

01

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.

► Client asked:“Why do we have 404s?”► AI found:“404s are normal. But you havecritical 500s on payment endpoints.”
02

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.

ingress → pod:app-backend → 511m CPU→ 218 RPS from single user-agent→ Effector reactive loop in checkout→ file: upsell.ts, bypass of MAX_ATTEMPTS
03

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.

Deliverable: Incident report→ Root cause with file:line reference→ Impact analysis + traffic patterns→ 4-tier remediation plan
Comparison

Not all SRE support
is the same.

Every dimension where AI-first observability outperforms the traditional approach.

Traditional SREHours to days

Manual investigation across dashboards, logs, and traces

ApexData SREMinutes 50× faster

AI correlates all signals and surfaces the exact root cause

Detection

Before

Alert fires → human reads dashboard

After

AI continuously analyzes all signals, catches silent degradations

Investigation

Before

Engineer manually checks logs, traces, metrics

After

AI traces through service mesh to the specific code path

Root cause depth

Before

"The pod crashed" or "Memory spike"

Aftersolidgate_handlers.go:3179

nil pointer dereference on *Order

Proactive detection

Before

Only pre-configured alerts

After

AI finds anomalies you didn't alert on — silent failures, quota exhaustion, staging bugs

Knowledge retention

Before

In engineer's head — lost on turnover

After

In the platform — survives team changes

Your team's visibility

Before

Status page updates, weekly calls

After

Full platform access — your team sees what our engineers see

Security

Your infrastructure,
your rules.

Three levels of access — from zero-touch telemetry to full infrastructure collaboration. You choose what fits your security requirements.

Level 1 — Default

Telemetry Only

No infrastructure access. Our monitoring agent collects logs, metrics, and traces. All analysis happens on telemetry data — your servers are never touched.

  • No server access
  • No file system access
  • Metrics, logs & traces only
Level 2 — Read-Only

Safe Cluster Access

Custom-built kubectl that can only read — never modify, delete, or restart. Deeper diagnostic context when telemetry alone isn't enough.

  • Cannot modify resources
  • Cannot delete or restart
  • Read-only kubectl access
Level 3 — Full Access

Bastion + 2FA

Authorized engineers access your infrastructure through a bastion host with two-factor authentication. Every session and command is logged and auditable.

  • Bastion host required
  • 2FA on every session
  • Full command audit log
SOC-2 Type IICompliance in progressTPM EncryptionData encrypted at restFull Audit TrailEvery action logged2FA RequiredAll personnel access
Features

Everything you need.
Nothing you don't.

+ What we do

  • →24/7 incident detection, investigation, and root cause analysis
  • →AI-powered analysis down to file and line of code
  • →Proactive anomaly detection — we find problems before users do
  • →Full incident reports with remediation recommendations
  • →Performance optimization and scaling guidance
  • →Direct Slack access to senior SRE engineers
  • →Deep understanding of your business logic and architecture
  • →ApexData platform deployed and maintained on your infrastructure

− What we don't

  • −We don't replace your dev team — we arm them with answers
  • −We don't just restart pods and call it resolved
  • −We don't send you to a ticket queue
  • −We don't charge per alert or per incident
  • −We don't disappear after onboarding
The Platform

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.

Data Collection

Zero-Instrumentation Setup

Connect your Kubernetes cluster — get infrastructure metrics, APM traces, and container health without touching your code.

AI Investigation

AI Investigation Agents

Describe a problem in natural language, get root cause analysis. The agent builds the right dashboard for each incident automatically.

Experience Replay

Dependency Mapping

Automatic real-time service topology. When something breaks, you see actual dependencies — not manually maintained diagrams.

Hazard Visibility

Shared Visibility

Your team sees exactly what our SRE engineers see. Same platform, same data, same dashboards. No black boxes.

Your team gets full access to ApexData as part of every plan. Use it independently or alongside our SRE support — the platform works either way.

Pricing

Plans

Startup

starting from
$1,000 /mo
Conditions
  • Company ≤ 3 years old
  • Pre-seed / Seed stage
  • ≤ 10 engineers
  • ≤ 10 microservices
Features
  • ✓Full ApexData platform access
  • ✓Incident reports with exact file & line references
  • ✓Up-to-date application & infrastructure documentation
  • ✓Shared Slack channel with SRE team
Contact us

Essentials

starting from
$5,000 /mo
Conditions
  • ≤ 25 engineers
  • ≤ 30 microservices
Features
  • ✓Everything in Startup, plus:
  • ✓Dedicated SRE lead
  • ✓Incident analysis with application logic & architecture guidance
  • ✓Continuous proactive analysis to detect hidden failures
  • ✓Infrastructure improvement recommendations
  • ✓SQL query profiling & indexing recommendations
Contact us
Popular

Professional

starting from
$7,000 /mo
Conditions
  • ≤ 60 engineers
  • ≤ 60 microservices
Features
  • ✓Everything in Essentials, plus:
  • ✓Detailed reports + change impact analysis
  • ✓Weekly review call with your engineering team
  • ✓Dedicated engineering hours
  • ✓Reliability planning & failover architecture review
  • ✓Ongoing database & infrastructure best practices consulting
Book a Demo

Enterprise

starting from
$10,000 /mo
Conditions
  • 60+ engineers
  • 60+ microservices
Features
  • ✓Everything in Professional, plus:
  • ✓Resolution time SLA available
  • ✓Dedicated SRE team available
  • ✓Proactive infrastructure development
  • ✓Monthly engineering hours for infrastructure work alongside your team
  • ✓Collaborative reliability roadmap with your dev teams
  • ✓Custom platform adaptations for your requirements
Contact us
Getting Started

From onboarding to ongoing.

Week 1

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.

Week 2

Deep Dive

We learn your application architecture, business logic, and recurring pain points. Baseline performance metrics established. First proactive findings shared with your team.

Ongoing

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.

FAQ

Common questions

Contact

Book an intro call.
Tell us about your stack.
We'll take it from there.

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