Ceburu Support Model & SLA Framework

Created by niharika Velidhi, Modified on Wed, 25 Mar at 3:33 PM by niharika Velidhi

 

Overview

Ceburu's Support Model delivers enterprise-grade reliability, scalability, and responsiveness. It combines tiered support, intelligent escalation, and clearly defined SLAs, enhanced by AI-driven observability to reduce downtime, accelerate resolution, and improve operational efficiency.


Support Tiers

Tier 1 – Standard (8x5)

  • Basic troubleshooting and ticket handling
  • SLA: Response within 8 hours
  • Best for: Organizations with internal IT teams requiring baseline support

Tier 2 – Advanced (24x7)

  • L1 + L2 engineers
  • Coverage across network, logs, and integrations
  • SLA: P1 within 1 hour, P2 within 4 hours
  • Best for: Enterprises requiring continuous monitoring and rapid incident response

Tier 3 – Premium (24x7)

  • Dedicated Customer Success Engineer (CSE)
  • Root Cause Analysis (RCA) and architectural guidance
  • SLA: P1 within 2 hours, P2 within 4 hours
  • Best for: Enterprises requiring dedicated expert support with architecture-level guidance


Escalation Model

Ceburu follows a structured escalation path: L1 → L2 → Architect → Engineering

  • L1: Initial triage, basic troubleshooting, and ticket routing
  • L2: Resolves network, log, and integration-level issues
  • Architect: Engaged for complex systemic issues requiring design-level guidance
  • Engineering: Escalated for critical bugs, deep platform failures, or custom development needs

Most issues are resolved at L1 and L2 levels. Critical and complex issues escalate to senior architects and engineering teams.


SLA Definitions

PriorityDescriptionResponse Time
P1Critical Outage (system down)Tier 2: 1 hr / Tier 3: 2 hrs
P2Major Issue (degraded performance)4 hours
P3Minor Issue8 hours
P4Informational / RequestBest effort

Note: Response time = time to acknowledge and begin work. Resolution time is best effort and depends on environment complexity.


AI Differentiation

Ceburu enhances traditional support with AI-driven observability:

  • Rapid Anomaly Detection - Issues surfaced in minutes
  • Cross-Layer Correlation - Simultaneous analysis across network, logs, and applications
  • Faster Root Cause Analysis (RCA) - AI pinpoints root causes with precision

This reduces Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR) for superior enterprise outcomes.


Contact

Support Email: support@ceburu.com

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