Repository navigation
Product or Service
Sentinel is an AI-powered DevOps Incident Triage Copilot designed to automate and structure the incident management lifecycle in production environments.
The platform integrates directly with monitoring and observability systems to consume real-time operational data such as alerts, logs, and metrics. Through a stateful agent-based architecture orchestrated with LangGraph, Sentinel analyzes incidents in multiple structured phases: detection, classification, investigation, evidence correlation, remediation proposal, verification, and post-incident documentation.
The system maintains contextual awareness throughout the entire workflow, preserving the incident state, collected evidence, hypotheses, and executed actions. This prevents information loss and reduces the need for engineers to manually reconstruct investigation steps.
Sentinel’s key functionalities include:
- Automatic ingestion of alerts and operational events
- Log and metric correlation across integrated systems
- AI-generated remediation recommendations
- Human approval for high-risk actions
- Real-time incident timeline visualization
- Historical incident tracking for long-term learning
All information is presented through a real time React dashboard, where DevOps engineers can monitor active incidents, inspect evidence, review the agent’s reasoning, and approve or reject suggested remediation steps.
By centralizing investigation, reasoning, and decision-making into a single platform, Sentinel directly addresses the inefficiencies and repetitive tasks that increase MTTR in traditional incident workflows.
Sentinel delivers value by transforming incident response from a fragmented, manual process into a structured, AI-assisted workflow.
The benefits for the client include:
- Reduced Mean Time to Resolution (MTTR): By automating evidence gathering and correlation, Sentinel accelerates root cause identification.
- Lower Operational Cognitive Load: Engineers no longer need to switch between multiple dashboards and tools during incidents.
- Automation of Repetitive Tasks: Log review, metric correlation, and documentation lookup are streamlined through AI.
- Improved Reliability and Availability: Faster and more consistent resolution reduces downtime impact.
- Human Control and Safety: Critical actions require explicit approval, ensuring responsible AI usage.
- Transparency and Auditability: Every decision, action, and reasoning step is traceable within the system.
- Continuous Operational Learning: Historical incidents are preserved to prevent recurrence and improve future responses.
Sentinel acts as a continuously available, context-aware DevOps assistant that enhances both immediate incident response and long-term system reliability without replacing human expertise.