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Description
Iris serves as a comprehensive framework for data collection, aimed at efficiently and swiftly delivering key performance indicators for network management. Designed to be robust and scalable, this framework addresses the common challenges encountered by internet service providers, effectively resolving various issues. The system is capable of generating insightful reports from extensive data sets, ensuring that users can interpret information meaningfully. As a holistic solution for network monitoring, Iris supports both enterprises and carrier-grade networks in their pursuit of achieving zero downtime and optimal performance levels. By employing advanced algorithmic techniques for the correlation and clustering of alerts, it allows for proactive identification of potential issues within the development ecosystem. Additionally, Iris Home offers an affordable and user-friendly option for monitoring home networks, providing crucial performance metrics for home internet connections with minimal computing requirements. This simplicity makes it an appealing choice for everyday users seeking to enhance their internet experience.
Description
The development of IT Governance platforms designed for managing Large Computing Systems, particularly those utilizing Mainframe technology, aims to modernize organizational practices and decrease cost structures.
The Challenge:
The significant ownership expenses associated with Large Computing Systems are a major concern.
A multitude of specialized products and countless reports are required for the effective management of the entire spectrum of customers' Large Computing Systems.
There is a notable challenge in formulating and supervising the principles of effective IT Governance, as well as a lag in adapting these principles to the rapidly changing technological landscape.
Additionally, there is a skills gap regarding Large Computing Systems, leading to a heavy reliance on system integrators and outsourcing services.
The Proposed Solution:
Implementing real-time mapping of hardware assets along with the collection of service delivery metrics will streamline management processes.
A unified platform will be established to oversee both the Large Computing Systems and the delivery of business services.
Utilization of Machine Learning technologies will enable the automatic classification of the collected metrics, as well as their correlation with business service delivery and the associated Key Performance Indicators.
This integrated approach not only enhances efficiency but also provides organizations with the agility needed to adapt to future technological advancements.
API Access
Has API
No
API Access
Has API
No
Integrations
SONIFI
No
Pricing Details
$10 per month
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Iris Network Systems
Country
South Africa
Website
irisns.com
Vendor Details
Company Name
XStream Labs
Country
Italy
Website
www.xstream-labs.com
Product Features
Data Management
Customer Data
No
Data Analysis
Yes
Data Capture
No
Data Integration
Yes
Data Migration
No
Data Quality Control
Yes
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Product Features
Data Governance
Access Control
No
Data Discovery
No
Data Mapping
No
Data Profiling
No
Deletion Management
No
Email Management
No
Policy Management
No
Process Management
No
Roles Management
No
Storage Management
No
