AI Operations Center
Bring metrics, logs, traces and platform health into one operating picture.
Interactive platform map
Architecture in context
The focused blueprint, its required foundation, and declared recommendations.
AI Operations Center
Bring metrics, logs, traces and platform health into one operating picture.
What this replaces
Complex AI platforms fail across multiple layers, making root cause analysis difficult when data is scattered across containers and services.
What your team gains
A unified observability stack for infrastructure and applications with alerting, correlation and long-retention metrics.
What is inside the blueprint
How it fits the platform
Services/host -> Alloy/Prometheus/OTLP/log files -> VictoriaMetrics + Loki + Tempo -> Grafana -> vmalert/Grafana alerts -> Telegram/reports.
VictoriaMetrics, vmalert, Grafana, renderer, Loki, Alloy, Tempo, ops-dashboard
- AICORTEX Core PlatformThe observability stack is deployed and wired by Core.
From prerequisites to operation
- Telemetry endpoints/log paths
- Storage sizing
- Dashboard and alert objectives
- Deploy metrics/log/trace backends
- Configure Alloy pipelines and scrapes
- Register Grafana data sources
- Import/create dashboards
- Create alert rules and notifier path
- Retention
- Scrape targets
- Log labels
- OTLP endpoints
- Trace sampling
- Dashboards
- Alert thresholds
- Storage/cardinality growth
- Alert delivery
- Collector health
- Trace cost/benefit
- Dashboard lifecycle
What this unlocks with other layers
AI SRE Foundation
Agents can reason over the same telemetry and history humans use for diagnosis.
Security Operations Story
Edge attacks, software vulnerabilities and runtime behavior feed one alert and response narrative.