Currently set to Index
Currently set to Follow

Use Cases and ResultsThe failure rate was reduced by 28% avoiding the addition of 20 full-time staff at a cost of $2.3 million.

Use Cases and Results92% of incidents were detected prior to customer impact.

Use Cases and ResultsImproved service availability by 60% and reduced staffing requirements by 50%.

Use Cases and ResultsReduced MTTR by 40% for service disruption and by 80% for degradation issues.

APIs / Traps

Fault Management

APIs / Traps

Performance Management

APIs / Traps

Change Assurance

Enhance customer experience, lower cost, and improve operational efficiency with VIA AIOps

VIA AIOps enables a new service assurance operating model and a new way of working through automation powered by real-time analytics, artificial intelligence, and machine learning.

VIA AIOps
VIA AIOps
VIA AIOps
VIA AIOps
Leading Network Operator uses VIA AIOps for Automated Incident Management
VIA AIOps use case

Transform Fault Management with Process Automation

  • Monitor and analyze syslog, trap, and alarms events from physical and virtual hosts within and across technology layers and applications in real-time
  • Enriches data through contextualization using machine-learned topologies and dimension discovery analysis 
  • Automatically generates baselines for every metric and dimension combination to detect faults more accurately 
  • Aggregates as appropriate multiple signals though process automation that may appear across service domains to a single incident 
  • Process automation powered by AI and machine learning defines probable root cause, symptoms and population impacted for rapid action and resolution 
  • Communicates bidirectionally with service management systems 
An Over-the-Top Video Service Provider Improves Customer Experience with VIA AIOps

Transform Performance Management with Process Automation

  • Monitor and analyze KPI time-series data from elements & applications
  • Unified data collection and analysis in cloud-native environments 
  • Cloud monitoring for performance across clusters vertically and horizontally without human intervention 
  • Detects service performance and customer-impacting incidents earlier with machine-learned baselines, machine-learned topologies, and stochastic modelling 
  • Eliminates multiple teams working on the same root cause through affinity analysis
  • Process automation defines root cause, symptoms and population impacted to enable faster action 
  • Prescribes next best action for incident remediation or prevention  
Top-Tier Cable Operator uses VIA Ops to reduce cost and improve DevOps and change assurance processes
AIOps for content streaming narrative

Transfrom Change Assurance and Improve DevOps and CI/CD Processes

  • Discover dependencies with total ecosystem observability
  • Detect change to an entity’s attribute (e.g., subscriber’s device or element’s firmware)
  • Correlate alarms, events, incidents and change tickets
  • Monitor for and detect customer experience impact
  • Automate response with early anomaly detection resulting from change
  • Improves CI/CD Processes with the addition of AIOps 

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