FaaST - Fault Analytics as a Service
Relieve your overwhelmed network operations center with TEOCO’s Fault Analytics service.
Many of today’s network (NOC) and service operations center (SOC) teams are overworked and overwhelmed. Managing thousands of network alarms each day, these dedicated experts spend too much time correlating alarms in order to identify the root cause of commonly recurring network problems.
This is why we developed FaaST – Fault Analytics as a Service by TEOCO. Built to help your operational teams focus on resolving network problems more quickly, FaaST automatically points to the root cause of symptoms and resolves issues as they arise. FaaST unveils valuable insights that often go overlooked, creating visibility into problematic parts of your network.
The result: more efficient operations, improved network performance, and customer experience.
- Solves recurring issues by finding their root cause
- TEOCO’s Machine-Learning Root-Cause Analysis (ML-RCA) extends the traditional rule-based RCA with adaptive mechanisms to detect alarms correlations and identify their root-cause.
- Reduces time to repair
- The service is built to help your operational teams focus on the right area, eliminate redundant trouble tickets and automate the analysis and resolution process.
- Increases network performance and stability
- FaaST unveils insights your teams could not notice before, creating visibility into problematic parts on the network.
- Immediate positive impact
- FaaST runs on top of any fault management system, enabling fast implementation and immediate effect on your NOC team’s efficiency.
- No need for inventory and topology data
- The only required input for the machine learning root cause analysis service is three months of alarms history data.
Stop Reacting to Symptoms & Start Identifying the Root of the Problem
FaaST follows a proven methodology that delivers actionable intelligence based on the latest machine-learning techniques for analyzing historical alarm data. This information is then reviewed by TEOCO’s team of telecom subject matter experts. We provide your operations and engineering teams with ongoing fault analytics and analysis through insight reports and actionable recommendations. These insights enable fast, reliable detection of the root cause of network outages and automate their resolution.
Machine-Learning Root Cause Analysis
Machine learning-based root cause analysis (ML-RCA) adds an important layer of automation to fault management; one that extends the traditional rules-based approach with adaptive mechanisms to more quickly locate the source of network problem. A set of proprietary patented algorithms study and analyze the stream of alarms coming from the network, both offline and in real-time, automatically suggesting groupings and correlations, then isolating and tagging the potential root-cause alarms among them.
ML-RCA is independent of your network technology or topology and can automatically derive the relationships between network elements and events – without predefined rules.
Anil Rao (Analysys Mason) – Author of ‘Automated Assurance Systems: Worldwide Market Shares’
Monica Paolini ( Senza Fili) – Author of ‘Mastering Analytics’
Geoffrey Moore - Author of ‘Crossing the Chasm’
Our customers trust in our ability to analyse information, unveil profitable knowledge, and offer products that power smarter operations. At TEOCO, we are client-driven and committed to ensuring substantial return on investment for every project. We truly believe that your success is ours, and we constantly innovate to make sure that you stay at the forefront of industry trends.
How can we help?
For over 25 years, TEOCO has helped network operators run state-of-the-art networks and profitable businesses. Learn how we can help you in the areas critical to the success of modern CSPs.