Technology

1. AIOps Implementation (Technical Details)

Core Technologies Used:

  • Machine Learning Models:

    • Supervised Learning (Classification for incident prioritization)

    • Unsupervised Learning (Clustering for anomaly detection)

    • Time-Series Forecasting (Predictive maintenance using LSTM/Prophet)

  • Data Sources:

    • Logs (ELK, Splunk, Graylog)

    • Metrics (Prometheus, InfluxDB, Dynatrace)

    • Traces (Jaeger, OpenTelemetry)

  • Key Features:

    • Noise Reduction: AI-based alert correlation (e.g., Topological Analysis)

    • Automated RCA: Bayesian Networks to identify root causes

    • Self-Healing: Integration with Ansible, Terraform, or Kubernetes for auto-remediation

gray concrete wall inside building
gray concrete wall inside building

2. Single Pane of Glass (SPOG) – Technical Specs

Architecture:

  • Data Layer:

    • Unified data lake (Snowflake, BigQuery, or Elasticsearch)

    • Real-time streaming (Kafka, Flink)

  • Integration Layer:

    • APIs (REST, GraphQL) for tool aggregation (ServiceNow, Zabbix, PagerDuty)

    • Custom adapters for legacy systems

  • Visualization Layer:

    • Grafana, Kibana, or custom React/D3.js dashboards

    • Role-based views (NOC Team vs. CISO)

Key Capabilities:
Cross-Domain Correlation: Link infra, app, and security events
Dynamic Thresholding: Adaptive baselines using statistical models
Customizable Widgets: Drag-and-drop KPIs for Saudi compliance (e.g., SAMA, NCA)

3. Disaster Recovery (DR) Automation – Technical Breakdown

Solution Stack:

  • Orchestration Tools:

    • AWS/Azure Site Recovery + Custom Python/Go automation

    • VMware SRM (Site Recovery Manager) with API extensions

  • Failover Logic:

    • Rule-Based: If RPO > 5min → Trigger failover

    • AI-Driven: Predictive failover based on risk scoring

  • DR Testing Automation:

    • Chaos Engineering (Gremlin, LitmusChaos) for validation

    • Automated reporting for NDMO compliance

Compliance & Security (Saudi-Focused)

  • Data Sovereignty:

    • All AI/ML models hosted locally (e.g., Saudi Cloud)

  • Regulatory Alignment:

    • SAMA CSF – Automated audit trails for IT ops

    • NDMO – Disaster recovery testing logs

Deployment Models

  • Cloud (Hybrid/Multi-Cloud):

    • AIOps on AWS SageMaker/Azure ML + SPOG on Grafana Cloud

  • On-Premises:

    • Air-gapped deployments for Saudi government/defense

  • Managed Services:

    • 24/7 monitoring by our Riyadh-based SOC/NOC

Relationships