ITRS Analytics Feature Guide

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Welcome to the comprehensive feature documentation guide for ITRS Analytics. This guide serves as your definitive resource for understanding, implementing, and maximizing the value of the ITRS Analytics observability platform.

Introduction Copied

This documentation serve as the single source of truth for ITRS Analytics capabilities, features, and strategic value. Whether you’re evaluating the platform for your organization, planning an implementation, or seeking to expand your current deployment, this guide provides the insights you need to make informed decisions and achieve success. This documentation is designed to serve multiple stakeholder groups within your organization.

Technical stakeholders:

• Engineers and developers seeking detailed implementation guidance.
• DevOps and operations teams planning deployments and integrations.
• Support teams needing comprehensive troubleshooting resources.
• Product managers evaluating features and capabilities.

Business stakeholders:

• Executives and managers assessing strategic value and ROI.
• End-users understanding available functionality and benefits.
• Administrators planning organizational adoption and governance.
• Compliance officers evaluating regulatory and audit capabilities.

What is ITRS Analytics? Copied

ITRS Analytics is a real-time observability platform and the technology chassis that powers ITRS’ product offerings. It is designed to help financial services and other highly regulated enterprises ensure that their mission-critical applications are always-on.

ITRS Analytics within the Geneos ecosystem Copied

ITRS Analytics serves as a core component of the Geneos system as ITRS modernizes its product architecture to deliver scalable monitoring solutions on industry-standard infrastructure. This strategic integration creates a comprehensive observability ecosystem that combines the proven monitoring capabilities of Geneos with the advanced analytics and storage capabilities of ITRS Analytics.

Key integration points:

Data collection and centralization — ITRS Analytics acts as the central data repository for metrics, logs, and events collected by Geneos Gateways and Netprobes. This centralized approach consolidates critical monitoring data from infrastructure, applications, and networks into a single, searchable location.

Enhanced analytics capabilities — While Geneos excels at real-time monitoring and alerting, ITRS Analytics extends these capabilities with advanced forecasting, probable cause analytics, and historical trend analysis. This combination transforms raw monitoring data into actionable business insights.

Scalable architecture foundation — Several new Geneos capabilities require ITRS Analytics to be installed, providing the foundation for a modern, scalable monitoring architecture. This ensures that organizations can grow their monitoring capabilities without architectural limitations.

Monitor of monitors Approach — ITRS Analytics functions as a “monitor of monitors” within the Geneos ecosystem, bringing context and meaning to alerts from various monitoring systems. This approach helps reveal the most likely source of problems in IT operations through intelligent correlation and analysis.

Unified visualization — The integration enables seamless data flow between traditional Geneos interfaces (like Active Console) and modern ITRS Analytics applications (such as Entity Viewer, Dashboards, and Web Console), providing users with multiple ways to interact with their monitoring data.

This integrated approach ensures that existing Geneos users can leverage their current investments while gaining access to next-generation analytics and visualization capabilities. Organizations can continue using familiar Geneos tools while gradually adopting ITRS Analytics applications to enhance their monitoring and analytics capabilities.

Core value proposition Copied

For technical teams — centralized repository for time series metrics, logs, traces, and events.

• Advanced analytics capabilities with forecasting and anomaly detection.
• Scalable, Kubernetes-native architecture supporting hybrid environments.
• Powerful APIs for integration with existing toolchains.
• Real-time processing with configurable data retention policies.

For business stakeholders — faster issue detection and resolution, protecting revenue and reputation.

• Reduced operational risk through predictive analytics and early warning systems.
• Enhanced regulatory compliance with comprehensive audit trails.
• Improved operational efficiency through consolidated monitoring.
• Lower total cost of ownership via unified platform approach.

Target users Copied

• Operations Teams — real-time monitoring and incident response.
• DevOps Engineers — application performance monitoring and troubleshooting.
• Business Managers — KPI dashboards and operational oversight.
• Compliance Officers — audit trails and regulatory reporting.
• Infrastructure Teams — capacity planning and resource optimization.

Platform architecture Copied

Core components Copied

ITRS Analytics consists of three fundamental layers:

Platform layer Copied

• Purpose — core data ingestion, storage, and processing engine.
• Components — operator managing Kubernetes services, Platform instances providing gRPC interfaces.
• Capabilities — high-throughput data processing, scalable storage, multi-tenancy support.

Web Console Copied

• Purpose — unified user interface for all ITRS Analytics applications.
• Features — common navigation, shared authentication, integrated app switching.
• Benefits — single-pane-of-glass experience reducing context switching.

Application layer Copied

• Purpose — specialized tools for specific monitoring and analysis needs.
• Architecture — modular design enabling custom app development and deployment.
• Integration — seamless data sharing between applications via Platform APIs.

Data model Copied

The platform uses a canonical data model based on:

• Entities — uniquely identified by dimensions (key/value pairs).
• Datapoints — self-describing observable data with timestamps and metadata.
• Namespaces — logical separation for different data streams.
• Properties — arbitrary metadata for contextual information.

Apps in ITRS Analytics Copied

ITRS Analytics hosts a powerful suite of apps within its platform, designed to help teams visualize, analyze, and act on monitoring data. These apps allow you to explore their data from multiple perspectives, uncover actionable insights, and make informed decisions faster.

Core apps Copied

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Specialized apps Copied

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Supporting apps Copied

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Installation and deployment Copied

Interactive sizing tool Copied

Use the ITRS Analytics Sizer for accurate resource estimation based on your specific requirements. This interactive tool considers:

• Cluster type selection
• Application requirements
• Configuration details
• Latest version specifications

Installation methods Copied

• Online installation — direct internet connectivity for latest updates.
• Air-Gapped installation — secure environments with pre-downloaded packages.
• Embedded Cluster — self-contained deployment with minimal dependencies.
• BYO Cluster — integration with existing Kubernetes infrastructure.

Use cases and business value Copied

Primary use cases Copied

Alert aggregation and noise reduction Copied

• Challenge: Overwhelming volume of alerts from multiple monitoring tools.
• Solution: ITRS Analytics consolidates and correlates alerts, reducing noise by 70-80%.
• Business Impact: Faster response times, reduced alert fatigue, improved operator effectiveness.

Log investigation and pattern analysis Copied

• Challenge: Scattered log data across multiple systems making troubleshooting complex.
• Solution: Centralized log storage with advanced search and correlation capabilities.
• Business Impact: Faster root cause analysis, improved MTTR, better pattern recognition.

Predictive capacity lanning Copied

• Challenge: Reactive capacity management leading to outages or over-provisioning.
• Solution: AI-driven forecasting with configurable prediction horizons.
• Business Impact: Proactive scaling, cost optimization, improved availability.

Cross-team collaboration Copied

• Challenge: Siloed monitoring data preventing effective collaboration.
• Solution: Shared dashboards, unified alerting, role-based access control.
• Business Impact: Improved collaboration, faster issue resolution, better knowledge sharing.

Industry-specific applications Copied

Financial services Copied

• Trading System Monitoring: Real-time FIX protocol analysis
• Regulatory Reporting: Automated compliance data collection
• Risk Management: Early warning systems for operational risks

Telecommunications Copied

• Network Performance: End-to-end service quality monitoring
• Capacity Planning: Predictive bandwidth management
• Customer Experience: Service-level agreement monitoring

Healthcare Copied

• System Availability: Critical system uptime monitoring
• Compliance: HIPAA and regulatory requirement adherence
• Performance Optimization: Resource utilization analysis

Monitoring and maintenance Copied

Backup and disaster recovery Copied

Backup strategy Copied

The backup and restore feature is currently supported only for BYO installations. Embedded Clusters are not currently supported for backup or disaster recovery operations. This feature is under development and will be introduced in a future release.

• Tool: Velero-based backup solution.
• Scope: Kubernetes resources, persistent volumes, application state.
• Schedule: Configurable automated backups with retention policies.
• Storage: Remote object storage (S3, GCS, Azure).

Restore process Copied

• Velero validation and configuration.
• Namespace cleanup and preparation.
• Resource restoration from backup.
• Application reinstallation and validation.

Support Bundle generation Copied

• For comprehensive diagnostic data collection.
• Contents: Logs, configurations, performance metrics, cluster state.
• Generation: Web console or command-line interface.
• Analysis: Automated issue detection and recommendations.

Development roadmap Copied

Short-term enhancements (Next 6 months) Copied

Platform improvements Copied

• Enhanced Multi-tenancy: Improved isolation and resource allocation
• Advanced Analytics: Machine learning-based anomaly detection
• API Expansion: Additional REST and GraphQL endpoints
• Performance Optimization: Improved query performance and data compression

Application features Copied

• Entity Viewer: Real-time value updates, dark theme, enhanced filtering
• Dashboards: Advanced visualization options, template marketplace
• Alerting: Improved correlation algorithms, custom notification channels
• Traces: Enhanced service map visualization, custom instrumentation support

Medium-term developments (6-12 months) Copied

New applications Copied

• Cost Analysis: Cloud cost optimization and chargebacks
• Security Monitoring: SIEM integration and threat detection
• Business Intelligence: Advanced reporting and analytics
• Mobile Interface: Responsive design and mobile applications

Integration enhancements Copied

• Cloud Providers: Native integration with AWS, Azure, GCP
• Observability Tools: Expanded ecosystem integration
• ITSM Platforms: ServiceNow, Jira, PagerDuty connectivity
• Data Lakes: Integration with modern data platforms

Long-term vision (12+ months) Copied

Artificial intelligence and machine Learning Copied

• Predictive Analytics: Advanced forecasting across all data types
• Root Cause Analysis: AI-powered incident investigation
• Automated Remediation: Self-healing system capabilities
• Natural Language Processing: Conversational interfaces for queries

Ecosystem expansion Copied

• Partner Integrations: Third-party application marketplace
• Custom Development: Low-code/no-code application builder
• Edge Computing: Distributed deployment capabilities
• Real-time Streaming: Event-driven architecture enhancements

Feature request process Copied

Community feedback Copied

• User Forums: Regular community engagement and feedback collection
• Beta Programs: Early access to new features for selected customers
• Advisory Board: Strategic input from key enterprise customers
• Support Analytics: Feature requests derived from support patterns

Prioritization Criteria Copied

• Business Impact: Revenue and operational benefit assessment
• Technical Feasibility: Development complexity and resource requirements
• Market Demand: Customer request frequency and urgency
• Strategic Alignment: Platform vision and architectural consistency

Getting started Copied

Quick start guide Copied

For technical users Copied

1. Assessment: Use ITRS Analytics Sizer for resource planning.
2. Prerequisites: Validate Kubernetes cluster and storage requirements.
3. Installation: Choose appropriate deployment method.
4. Configuration: Set up data sources and basic monitoring.
5. Applications: Install and configure relevant apps based on use cases.

For business users Copied

1. Use Case Identification: Map business requirements to platform capabilities.
2. Team Training: Schedule onboarding sessions for key stakeholders.
3. Pilot Deployment: Start with limited scope to demonstrate value.
4. Expansion Planning: Develop roadmap for broader organizational adoption.
5. Success Metrics: Define KPIs for measuring platform effectiveness.

Resource requirements planning Copied

Assessment questions Copied

• What is your current monitoring tool landscape?
• What are your primary pain points with existing solutions?
• What are your scalability requirements over the next 3 years?
• What compliance and security requirements must be met?
• What integration points are critical for success?

Success factors Copied

• Executive Sponsorship: Ensure leadership support and resource allocation
• Cross-functional Team: Include operations, development, and business stakeholders
• Phased Approach: Implement incrementally to manage risk and demonstrate value
• Training Investment: Provide adequate training and documentation
• Feedback Loop: Establish mechanisms for continuous improvement

Next steps in your ITRS Analytics journey Copied

1. Contact ITRS: Discuss specific requirements and deployment options.
2. Proof of Concept: Design limited pilot to validate capabilities.
3. Training Program: Develop skills and knowledge transfer plan.
4. Implementation Planning: Create detailed project timeline and milestones.
5. Success Measurement: Establish metrics and monitoring for ROI tracking.

Key takeaways Copied

ITRS Analytics represents a comprehensive solution for modern observability challenges, providing the scalability, flexibility, and intelligence needed to manage complex enterprise environments. Its modular architecture, extensive application ecosystem, and focus on business value make it an ideal platform for organizations seeking to transform their monitoring and analytics capabilities.

The platform’s continued evolution, guided by customer feedback and market demands, ensures that investments made today will continue to deliver value as organizational needs grow and change. With proper planning, implementation, and ongoing optimization, ITRS Analytics can serve as the foundation for operational excellence and business resilience.

This guide is designed as a living resource that evolves alongside the ITRS Analytics platform. As new features are developed, capabilities are enhanced, and use cases expand, this documentation will be continuously updated to reflect the latest information and best practices.