Digital Transformation has set the industry on the journey to realize a new operational model that leverages AI, ML, and Network Orchestration and Automation. VIAVI NITRO AIOps solutions empower Service Providers to evolve their legacy NOC to Dark NOC and get end-to-end network visibility across Cloud, Mobility, IT/MEC and IoT platforms.
The suite covers Cloud Native Inventory, Service Assurance, AI and ML driven Assurance, Customer and Service Analytics and Network Automation Solutions.
- Cloud-native asset discovery
- Inventory & topology
- Assurance & Analytics
- Fault management
- Visibility across multiple technology domains
- The ability to leverage AI, ML, and automation
- A seamless transition from manual and siloed network operations to fully automated cross-domain network operations
- Increased quality of the services delivered
- Optimized CAPEX and OPEX expenditures
- Field Services and Tower Management
- Advanced inventory: active and passive, physical and logical
- Topology: true end-to-end and vendor agnostic
- ServiceNow TNI integration (complete Network and Service Assurance Integration enabled by unparalleled access to traffic visibility)
- AI/ML-enabled packet/flow capture to evolve to probe-less Mobile CORE monitoring for 5G SA
- Seamless integration of IT, Telco, and Edge network AIOps functions
Click to discover the main applications of the NITRO AIOps suite:
- Dashboards and Trend analytics: users can generate on-the-fly reports and schedule on demand and troubleshoot faster with drill-down at KPI levels
- Dynamic Custom Dashboard: customized dashboard as per user preferences.
- Formula builder: customized formula across multi-domain and vendor for flexible KPI creation
- Alert Management: trigger alert in case of static or dynamic KPI deviation or anomaly detection
AIOPS & Fault Management
- By analyzing both historic and current alarms, the functionality automatically suggests groupings and correlations, and tags the potential root-cause.
- Identify network problems, predict their potential impact on services and enable corrective measures and maintenance planning.
Minerva E2E Topology
- Multi-vendor, Multi-Technology and Multi Domain tool. With a unique patented algorithm, it provides end-to-end topology & analytics capabilities.
- It gathers information from the network inventory and the configuration files, then network topology is generated to visualize the entire network elements of both layer-3 network (L3 devices) and transmission network.
Cloud Native Inventory Management
It comprises information on physical, logical and network resources. It acts as a one-stop solution for all the Network Monitoring needs and helps in bridging the Silos.
Discovery & Configuration Management
Map and monitor the networked infrastructure. It provides real time network discovery of the active network elements in the network. It allows to categorize the network elements on domain types and allows to select the elements based on which the attributes shall be shown.
NOA Workflow Automation
It enables to automate the mundane tasks by creating user specific workflows and automating to ensure closed loop automation. The number of man hours for scheduled maintenance tasks can be reduced by automating the entire process with ready to use Automation Templates across multiple platforms including but not limited to Python, Java, YAML, Shell Scripts, etc.
AI/ML with Anomaly Detection
Proactively plan the capacity across the network and avoid performance failure which affects OPEX and CAPEX. It plays a major role in the capacity or hardware sizing of network devices across the topology. It forecasts and detects anomalies for model building across domains and dub-domains.
Service Quality Management
It enables the proactive management of digital services in complex ecosystems. OptiGo monitors the end-to-end services of the customers. OOKLA Analytics provides a subscriber level analysis along with their geolocation to identify the subscriber pain points and network coverage. An overview of the download speeds, upload speeds and latency can be measured across different regions.