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AI Operations Center

Bring metrics, logs, traces and platform health into one operating picture.

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AI Operations Center
FoundationAICORTEX Core PlatformConnectedExecutive Intelligence & ReportingConnectedThreat Detection & Runtime Security
Signal path active8 deployment units

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

Prometheus-compatible metrics remote storage
Long retention
Query-driven monitoring workflows
Alerting and recording rules
Dashboards and ad-hoc data exploration
Multi-data-source queries and alert rules
Highly compressed label-indexed logging
Log search and metrics-from-logs
Collection of metrics, logs, traces and profiles
Prometheus and OpenTelemetry pipelines
OTLP receive/export pipelines
Distributed tracing
OTLP/Jaeger/Zipkin ingestion
Trace search
Trace-to-logs and trace-to-metrics correlation
Service graphs and RED metrics in the dashboards
PNG panel rendering
Infrastructure status dashboard

How it fits the platform

Services/host -> telemetry collector/Prometheus/OTLP/log files -> metrics database + log store + trace store -> dashboards -> alerting engine/dashboard alerts -> Telegram/reports.

Included services

Metrics database, Alerting engine, Dashboards, Report renderer, Log store, Telemetry collector, Trace store, ops-dashboard

Platform requirements

From prerequisites to operation

Prerequisites
  1. Telemetry endpoints/log paths
  2. Storage sizing
  3. Dashboard and alert objectives
Deployment
  1. Deploy metrics/log/trace backends
  2. Configure telemetry collector pipelines and scrapes
  3. Register dashboard data sources
  4. Import/create dashboards
  5. Create alert rules and notifier path
Configuration
  1. Retention
  2. Scrape targets
  3. Log labels
  4. OTLP endpoints
  5. Trace sampling
  6. Dashboards
  7. Alert thresholds
Operations
  1. Storage/cardinality growth
  2. Alert delivery
  3. Collector health
  4. Trace cost/benefit
  5. Dashboard lifecycle

What this unlocks with other layers

AI Operations Center + MCP Agent Hub + Persistent AI Memory + Knowledge Graph & Institutional Intelligence

AI SRE Foundation

Agents can reason over the same telemetry and history humans use for diagnosis.

Threat Detection & Runtime Security + AI Operations Center

Security Operations Story

Edge attacks, software vulnerabilities and runtime behavior feed one alert and response narrative.

Technology behind this capability

Metrics databaseAlerting engineDashboardsReport rendererLog storeTelemetry collectorTrace storeOperations dashboardAICORTEX native
Browse Marketplace
Operations

Executive Intelligence & Reporting

Turn live operational data into images, summaries and delivery-ready reports.

Operations
Security

Threat Detection & Runtime Security

Detect abusive behavior at the edge, visualize it, scan the software supply chain and optionally enforce runtime policy in the kernel.

Security