AI-Powered Operations & Observability Platform
A comprehensive platform-as-a-service combining AI-driven incident correlation, smart operator response, and enterprise alert orchestration. Built on AWS serverless architecture with multi-agent AI systems for real-time root cause analysis.
Architecture Overview
Data Sources
Alert Pipeline
- EventBridge ingestion
- Lambda alert parsing
- Entity extraction
SNOW Pipeline
- SQL extraction + GPT-4
- Vector embedding (9D)
- PostgreSQL storage
ADO Pipeline
- ECS Fargate release fetch
- Instance analysis
- PostgreSQL ETL
CrewAI Multi-Agent Orchestrator
Teams Notification
- Adaptive card alerts
- Probable root causes
- Recommended actions
- Domain & team context
Data Storage
- Correlation results stored
- Analysis audit trail
- Effectiveness tracking
- Continuous learning
Downstream Events
- EventBridge publishing
- SOR knowledge base
- AOO_V2 orchestration
- Risk dashboards
SOR — Smart Operator Response
AOO_V2 — Alert Orchestration
AI-Powered Incident Correlation (AOO Core)
Comprehensive AI-powered system that automatically correlates production alerts with recent deployments, historical incidents, and real-time observability data to provide actionable root cause analysis.
Multi-Agent AI Orchestration
- CrewAI multi-agent system on AWS Lambda
- Sequential agent processing: intake, search, correlation, analysis
- GPT-4 powered root cause analysis via AWS Bedrock
- Deterministic rule engine for pattern matching and confidence boosting
- Dynamic AI decision engine for connector selection and parameter optimization
Data Pipeline Architecture
- Real-time alert ingestion via EventBridge
- ServiceNow incident extraction with vector embeddings (Titan Embed v2)
- Azure DevOps release pipeline with ECS Fargate containers
- Eagle View external alert correlation via MCP connectors
- ArmorCode security posture integration (CVEs, vulnerabilities, compliance)
- Domain context mapping with multi-strategy matching
Result: Real-time correlation completing in 6-10 seconds, with AI-generated root causes and recommended actions.
Smart Operator Response (SOR)
Streamlines alarm troubleshooting by combining a React web portal with AWS serverless services and AI/ML models. Operators submit alarm queries which are embedded and matched against a pgvector-backed knowledge base, then enriched with Bedrock-driven response generation.
Operator Workflow
- React web portal for alarm query submission
- Secure REST endpoint via AWS API Gateway
- Lambda-based query embedding using Bedrock Titan
- pgvector cosine similarity search against knowledge base
- AI-enriched troubleshooting response generation
Knowledge Base Management
- PostgreSQL with pgvector extension for vector-indexed storage
- Alarm procedures, runbooks, and historical resolution patterns
- Continuous knowledge base enrichment from resolved incidents
- Secure, low-latency workflow with VPC-attached Lambda
Result: A single-pane interface that surfaces relevant procedures and recommended actions in seconds.
AOO_V2 — AI-Driven Alert Orchestration
The next evolution of the AOO platform, purpose-built for enterprise-scale operations. Turns raw incident signals into clear business-impact insights and actionable next steps.
Core Capabilities
- Accelerated incident resolution via cross-source correlation
- Prioritized root-cause hypotheses delivered in seconds
- Automated domain and team mapping for rapid escalation
- Integrated security posture alongside operational health
- Consistent automated analysis at enterprise scale
Intelligence Features
- Deployment age risk assessment (FRESH/RECENT/SETTLED/AGED)
- Dynamic risk-based recommendations (rollback, mitigation, forward fixes)
- AI-generated log summaries replacing raw data with actionable insights
- Effectiveness tracking for continuous learning and adaptation
Result: Enterprise-scale automated analysis that improves service reliability and customer experience.
Integration & Distribution
Comprehensive output channels and downstream integrations ensure that AI-generated insights reach the right teams through the right channels.
Output Channels
- Microsoft Teams adaptive cards with structured alert summaries
- PostgreSQL storage for correlation results and audit trail
- EventBridge publishing for downstream system consumption
- Domain-aware routing to owning teams and functions
Key Integration Points
- Hostname-to-instance mapping for precise deployment tracing
- Vector embeddings (1024-dim) for semantic similarity search
- EventBridge event buses for decoupled, scalable processing
- S3-based ECS container communication for batch pipelines
- MCP connectors for real-time external API access
Result: Scalable, event-driven architecture with parallel processing and real-time distribution.
Cloud-Native Infrastructure
Compute & AI
- AWS Lambda (7 serverless functions) — Python 3.11/3.12
- ECS Fargate (3 containerized tasks) — Sequential processing
- AWS Bedrock — GPT-4 analysis + Titan Embed v2 embeddings
- CrewAI framework for multi-agent orchestration
Data & Security
- PostgreSQL RDS Aurora with pgvector extension (22 tables)
- Amazon S3 for inter-container communication and config
- Amazon EventBridge for event-driven orchestration
- IAM roles with least-privilege permissions
- VPC-attached Lambda with private subnets for DB access
- CloudWatch Logs for comprehensive audit trail
Result: Fully serverless, elastic architecture supporting real-time and batch processing workloads.
Platform Value Delivered
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