Unified Availability Model (UAM): A Normalization-Based Framework for Measuring Availability Across Heterogeneous Information Systems

The Unified Availability Model (UAM) introduces a systematic, mathematically grounded method for evaluating the availability of heterogeneous information systems whose operational characteristics differ across architectural layers, functional domains, and metric spaces.
Unlike traditional SRE- or API-centric approaches that assume homogeneous latency–error metrics, UAM provides a generalizable normalization framework that transforms diverse raw indicators into a unified scale in [0,1]

The model is based on four normalization constructs:

1. Statistical baselines (long-term behavior of the system),

2. SLA thresholds (contractual or internal targets),

3. Physical/architectural limits,

4. Acceptable deviation ranges.

Each construct is formalized as a normalization operator, allowing their weighted combination into a single availability score for any subsystem — from REST/gRPC microservices and payment gateways to SAP S/4HANA, Oracle EBS, HSM signing services, batch/ETL pipelines, EDI/IDoc flows, message brokers, and search/logging platforms (Elastic, Kafka, Loki, VictoriaMetrics).

At the business level, UAM introduces the notion of a business-process contour — a structured chain of interdependent systems — and defines contour availability as a weighted aggregation of subsystem scores. This makes end-to-end service health measurable and comparable across heterogeneous infrastructures.

The methodology includes Prometheus, Zabbix, Grafana, Loki, Elastic, and Kafka integration patterns, as well as normalization templates for major system classes.