Technologies KPIs, Pivots & Measures

GermainUX provides preconfigured KPIs, pivots and measures for monitoring the availability, performance and health of hardware, software and cloud services.

These analytics support desktop, server, mobile, containerized and distributed environments—whether deployed in the cloud or on premises. They help teams detect outages, degradation, capacity constraints, errors and abnormal behavior before they create a larger impact on users or business operations.

Preconfigured analytics can be used as provided or customized for your technologies, architecture and service-level objectives.

🔍 What Technology Analytics Help You Understand

GermainUX technology KPIs can answer questions such as:

Question

Is a server, service, database, application or container available?

Which components are failing or restarting?

Where are requests being rejected, queued or delayed?

Which resources are approaching capacity?

Which applications or dependencies generate the most errors?

Is performance degradation isolated to a host, environment, version or location?

Which technical condition caused a poor user experience or interrupted workflow?

Is an issue new, recurring or becoming more severe over time?

🔋 Availability and Uptime KPIs

Availability KPIs identify outages, failed components, crashes and conditions that prevent a technology from operating as expected.

🌐 General Availability

KPI

Purpose

Server Availability

Monitors whether a server is available.

Service Availability

Monitors the availability of operating-system services.

Process Uptime

Measures how long a monitored process remains operational.

HTTP Availability

Verifies whether an HTTP endpoint is reachable and responding.

Database Availability

Monitors the availability of configured databases.

Docker Container Availability

Identifies available, unavailable or stopped containers.

Apache ZooKeeper Node Availability

Monitors the availability of ZooKeeper nodes.

💥 Application Failures and Crashes

KPI

Purpose

http://ASP.NET Application Failed Requests

Counts requests that failed within an http://ASP.NET application.

http://ASP.NET Application Rejected Requests

Counts requests rejected because the application queue was full.

http://ASP.NET Rejected Requests

Counts requests that could not be processed because server resources were insufficient.

IIS Failed Request

Captures failed-request events reported by IIS.

Mobile App Crash

Captures mobile-application crashes.

Mobile App Uptime

Measures mobile-application uptime.

Node.js Unhandled Promise Rejections

Counts rejected promises for which no handler was present.

Unhandled Promise Rejection

Captures unhandled promise-rejection events in monitored web applications.

☕ .NET and Java Availability Indicators

KPI

Purpose

.NET Exception

Captures exceptions reported by .NET monitoring.

.NET Exception Rate

Measures the number of .NET exceptions generated per second.

.NET Requests Failed Rate

Measures the rate of failed HTTP requests within a monitored application domain.

.NET Classloader Failures

Tracks classes that failed to load after the application started.

Java Heap Available

Measures the percentage of JVM heap still available.

Java Non-Heap Available

Measures available JVM non-heap memory.

☁️ Salesforce and Siebel Availability

KPI

Purpose

Salesforce Code Exception

Captures Salesforce exceptions found in debug logs.

Salesforce Apex Unexpected Exception

Captures unexpected Apex exceptions collected through Salesforce Event Monitoring.

Siebel Component Availability

Monitors the availability of individual Siebel components.

Siebel Gateway Availability

Monitors Siebel Gateway availability.

Siebel Server Availability

Monitors the overall state of a Siebel Server.

Siebel HTTP Availability

Verifies the availability of a Siebel HTTP endpoint.

Siebel Component, Core, Enterprise and FDR Crashes

Captures crashes from the corresponding Siebel components and logs.

Siebel Failed Task Count

Counts failed Siebel tasks.

🔗 Messaging and Connection Availability

KPI

Purpose

AWS SES Rejected Mails

Counts email messages rejected by Amazon SES.

WebLogic JDBC Connections Available

Measures database connections available to applications from a WebLogic data source.

WebLogic JDBC Connections Unavailable

Measures connections currently unavailable because they are in use or being tested.

WebLogic JDBC Connection Wait Failures

Counts requests that waited longer than the configured connection-reserve timeout.

🚤 Performance KPIs

Performance KPIs measure speed, throughput, utilization, capacity, contention and operational health.

💻 Host and Operating-System Performance

KPI family

Representative KPIs

CPU

CPU Usage, CPU Queue Length, Context Switch Rate

Disk

Disk Usage, Disk I/O, Disk Queue Length

Files and directories

Directory Size, Directory File Size, Directory File Count

Capacity

Resource utilization, queue depth and saturation indicators

These KPIs help determine whether infrastructure constraints are contributing to slow applications, failed requests or interrupted workflows.

🌐 http://ASP.NET and IIS Performance

Representative http://ASP.NET KPIs include:

Application cache-hit ratio

Executing, current and queued requests

Request execution time and wait time

Current connections

Disconnected, failed and rejected requests

Application and worker-process restarts

Running worker processes

Together, these KPIs reveal whether poor application performance is caused by request volume, queue saturation, insufficient resources, restarts or communication failures.

🗄️ Database Performance

GermainUX includes database KPIs across several analytical areas:

Area

Representative KPIs

Sessions and connections

Active Sessions, Connections, Session Utilization, Long-Running Sessions, Top Session

CPU and elapsed time

Database CPU Time, Database DB Time, Query CPU Time, Query CPU Usage

Queries and transactions

Slow Query, Transaction Rate, Insert Rate, Update Rate, Delete Rate, Fetch Rate

I/O

Read, Write, Read Time, Write Time, Query I/O Usage

Locks and contention

Deadlocks, Lock Requests, Lock Timeouts, Lock Wait, Locks Held, Processes Blocked

Storage and capacity

Data File Size, Log File Size, Schema Size, Table Size, Tablespace Utilization, Free Temporary Space

Cache and access paths

Buffer Hit Ratio, Index Scans, Sequential Scans, Table Scans, Active Cursors

Wait analysis

Application, commit, concurrency, network, system I/O, user I/O and other wait time

Data maintenance

Dead Rows, Hot Updates, Broken Materialized-View Jobs, Rollbacks

These measurements help teams identify whether a database problem is caused by a costly query, blocked session, lock, capacity constraint, inefficient access path or storage bottleneck.

🐳 Containers and Images

KPI family

Representative KPIs

Container resources

CPU Utilization, Memory Utilization, Disk Input and Output, Network Input and Output

Container lifecycle

Container Event, Image Event, Network Event, Volume Event

Image security

Critical, High and Medium Vulnerability Counts

🏗️ Apache, ActiveMQ and ZooKeeper

Technology

Representative KPIs

Apache HTTP Server

Busy Workers, Idle Workers, Process Count, Request Rate, Request Size, Throughput, Shared Memory

ActiveMQ

Heap Usage, Message Backlog

Apache ZooKeeper

Live Connections, Dropped Connections, Latency, Outstanding Requests, Thread Count, Deadlocked Threads, Heap Usage, File-Descriptor Usage, Data Size, Packets and Bytes Sent or Received

🔎 Elasticsearch

Representative Elasticsearch KPIs include:

Cluster health

Active shards

Cluster node count

Read and write operations

Tasks

Rollup jobs

⚡ Cloud and Messaging Services

Technology

Representative KPIs

Amazon SES

Sent, bounced, complained-about and rejected email counts

Amazon EC2

Critical, high and medium vulnerability counts

📚 Oracle E-Business Suite and BI Publisher

Representative KPIs include:

Active, pending and running concurrent requests

Concurrent processes, programs and queues

Requests completed with warnings

Terminated processes

Invalid database objects

BI Publisher diagnostic and server events

🌍 Browser and Digital Experience Signals

Technology analysis can also incorporate browser-side evidence:

KPI

Purpose

Browser Event

Captures a custom browser event.

Browser Metric

Captures a custom numerical browser measurement.

Browser Transaction

Measures a custom browser transaction.

Browser Report

Captures CSP violations, policy violations, deprecated features, crashes and related reports.

Browser Visibility

Tracks whether a page is visible, hidden, active or inactive.

These signals help connect server and infrastructure conditions with what users actually experienced.

💓 GermainUX Platform Health

GermainUX can monitor its own components using KPIs such as:

Agent status

Component status

Engine and Engine Manager status

Engine and Engine Manager CPU utilization

Engine and Engine Manager memory utilization

Aggregation duration

Fact-processing rate

GermainUX service events and action logs

Datamart data and index tablespace utilization

📁 Fact Models

Each KPI is backed by a fact model appropriate for the type of data collected.

Fact model

Typical use

GenericMetric

Numerical values sampled over time, such as CPU usage, queue length or connection count.

GenericEvent

Discrete occurrences, such as a failure, crash or diagnostic event.

GenericTransaction

Activities with a start, end and duration, such as a long-running database session.

UxMetric

Numerical measurements captured from the user-experience layer.

UxEvent

Browser or user-experience events.

UxTransaction

Timed browser or user-experience transactions.

MobileEvent

Discrete events captured from a mobile application.

MobileTransaction

Timed mobile-application activity.

NativeEvent

Events captured from native applications, including .NET exceptions.

InternalEvent

Operational events generated by GermainUX components.

AlertEvent

Alerts generated by GermainUX.

AuditLog

Configuration and administrative audit events.

🔁 Pivots

A pivot segments a KPI result by a selected technology dimension. Available pivots vary by KPI and data source.

Common technology pivots include:

Pivot

Application, application component and service

Technology type and component type

Environment, system, host and target

Cluster, node, container and process

Database, schema, table, query or session

Error, event, status and severity

Browser, device and operating system

Data center, region, country and cloud zone

User, session and business transaction

Version, release and deployment

Pivots help determine whether an issue is widespread or concentrated in a particular component, host, environment or user population.

🧮 Measures

A measure is the calculation applied to a KPI. Depending on the underlying fact model, GermainUX can provide:

Measure

Count and distinct count

Minimum and maximum

Average and total

Current or latest value

Rate and throughput

Availability or uptime percentage

Error and failure percentage

Resource utilization percentage

50th, 90th, 95th, 99th and 99.9th percentiles

Standard deviation

Percentiles are particularly important for response-time and latency analysis because an average can hide severe degradation affecting a smaller population.

📈 Combining KPIs, Measures and Pivots

Operational question

KPI

Measure

Pivot

Which servers experience the highest CPU pressure?

CPU Usage

95th percentile

Hostname

Which databases generate the most lock contention?

Database Lock Wait

Total wait time

Database name

Which containers consume the most memory?

Docker Container Memory Utilization

Maximum

Container name

Which application versions generate the most exceptions?

.NET Exception

Count

Application version

Which environments have the slowest HTTP endpoints?

HTTP transaction or availability KPI

95th-percentile duration

Environment

Which browser families encounter the most policy violations?

Browser Report

Count

Browser family

From an aggregate KPI result, teams can drill into affected technologies, related events, traces and user sessions to identify root cause and business impact.

🔗 Correlate Technology with User and Business Impact

GermainUX can correlate technology KPIs with:

Real-user sessions and Session Replay

Application transactions and distributed traces

Errors and exceptions

Business processes and workflow steps

Conversion and drop-off events

Alerts and automated actions

This helps teams move from “the application is slow” to understanding which users and workflows were affected, which component caused the degradation and what corrective action should be prioritized.

🛠️ Customize the Analytics

GermainUX can support custom:

KPIs and fact models

Measures and formulas

Pivots and business dimensions

Availability and performance thresholds

Static and statistical SLAs

Correlation and tracing logic

Dashboards, reports and alerts

Automated diagnostic or remediation actions

The exact KPI, pivot and measure set depends on the monitored technology, enabled components and implementation requirements.


Service: Analytics

Feature Availability: 2021.3 or later