Orange integrates Augtera Network AI platform to its NOC tools to leverage AI/ML in daily network operations. This will reduce Network Operation Centers alarms by 70% and prevent failures.

Augtera’s NLP Marks a New Era in Real-Time Action from Streaming Log Data

Augtera also announces Zero Day Anomalies for syslog, detecting unusual patterns when they first occur.

PALO ALTO, Calif., April 27, 2022 /PRNewswire/ — Augtera Networks, the industry leader in AI/ML-powered Network Operations platforms, today announced a major innovation in streaming log analysis, utilizing real-time natural language processing (NLP). The next evolution in log analysis is moving from text matching to understanding meaning, both the semantics and the context of text, in real-time, for proactive insights. Text matching is not scaling. It is brittle, hard to maintain, and generates more noise than operations teams can meaningfully digest. Natural language processing, combined with other AI/ML techniques, enables innovative new capabilities while also reducing noise.

“AI/ML is proving to be a major step forward in network operations, yet many Enterprises do not have budget and resources to successfully develop and maintain in-house implementations that are performant, scalable, and extensible,” said Nick Lippis, ONUG Co-Founder and Co-Chairman. “Commercial solutions from companies like Augtera Networks are filling the gap. Automated detection of new log messages and patterns like Augtera’s Zero Day Anomaly capability is a great example of the real-time anomaly detection that Enterprises will increasingly need across multiple network vendors and domains. This is particularly important as Networking and Security become more entangled.”

The first feature that Augtera is announcing based on NLP is Zero Day Anomalies for syslog, which also leverages clustering and machine learning. The conundrum of the current log processing paradigm is that an anomaly must be already well known before a text-based filter can be created to detect it. Even then, text-based filters based on approaches such as REGEX can be noisy and hard to maintain in the face of constant change and variation across multiple vendors.

“This is a new era in log analysis” said Rahul Aggarwal, Founder & CEO, Augtera Networks. “Operators increasingly want to move away from reactive historical mining of log data to proactive real-time insights. Our ability to discover meaning from log data and utilize it for real-time Zero Day ML Anomalies catalyzes this shift. This gives operators the peace of mind that an unknown hardware or software issue can be detected automatically before it impacts the rapidly evolving network infrastructure that creates even more unknown unknowns”.

These new additions to Augtera’s Network AI platform are the result of over a year of R&D and are powered by new proprietary algorithms. These algorithms build ML models that leverage NLP over Big Data. They are already deployed in production to predict Zero Day Anomalies in environments with hundreds of millions of syslog messages an hour.

“The ability to understand log message semantics will be the foundation of many future capabilities,” said Bhupesh Kothari, Co-Founder & VP of Engineering for Augtera Networks. “Augtera has leveraged the team’s experience in embedded software development, to write from scratch, high-performance and cost-effective AI/ML algorithms, that scale to billions of streaming log messages per day, without message loss. Engineering challenges for real-time streaming AI/ML are significantly different than those for historical data lake mining. Our implementation supports the largest data centers and networks.”

Augtera Network’s algorithms and models are optimized, based on real-world deployments, for network operations. While the Augtera platform supports the most demanding and largest network operations environments, it has also been developed to provide immediate value upon initial installation, without configuration. Our focus is network operations automation through automated anomaly detection, incident prevention, and trouble-ticketing.

Zero Day Anomaly Detection for Syslog is immediately available as a base capability in the platform, at no additional cost.

About Augtera Networks
Augtera Networks stops the noise, enables proactive operations, and prevents incidents, for Enterprise and Service Provider networks. The first AI/ML-powered network operations platform, Augtera is being used by hyperscale cloud platforms, financial institutions, communications service providers, managed service providers, and enterprises in multiple verticals. Additional information can be found at www.augtera.com.

Jim Meehan
Augtera Networks
415-269-3845
jmeehan@augtera.com
website: www.augtera.com

SOURCE Augtera Networks

Service Providers: “Time to get AI/ML out of the labs and into production”

Palo Alto, Calif., April 03, 2022 (GLOBE NEWSWIRE) — Augtera Networks the industry leader in AI/ML-powered Network Operations platforms, lead critical conversations on April 6th at the 22nd MPLS SD & AI Networld22 conference in Paris, in addition to being an event sponsor. 

Founder & CEO Rahul Aggarwal presented on the critical importance of Topology in next generation AI/ML-powered operations. Understanding networking constructs and relationships between them is essential to correlating multiple events into a single, operationally relevant, incident. This reduces noise and manual correlation. Business outcomes include improved KPIs, improved customer satisfaction, and reduced costs. 

VP Sales Engineering, Jean-Marc Uzé lead a panel of network operators in discussing “AI/ML adoption by SPs”. The message from the panel was clear “It is time to get AI/ML out of the lab and into production”, as it has already demonstrated the ability to detect anomalies not detected by traditional tools, reduce false positives for alarms, predict future defects, provide benefits for both infrastructure and SD-WAN use cases, and reduce mean time to detect and repair (MTTD & MTTR). One operator spoke of 30 million in savings from initial use cases, while another spoke of the potentially paradigm shifting effect of mean time to detect (MTTD) going from a positive number to a negative number. 

The message is clear, it is time to get AI/ML out of the labs and into production. 

About Augtera Networks 

Augtera Networks stops the noise, enables proactive operations, and prevents incidents, for Enterprise and Service Provider networks. The first AI/ML-powered network operations platform, Augtera is being used by hyperscale cloud platforms, financial institutions, communications service providers, managed service providers, and enterprises in multiple verticals. Additional information can be found at www.augtera.com  

Media Relations: 

Jim Meehan 

Augtera Networks 

415-269-3845 

Jmeehan@augtera.com 

“Get AI/ML out of the labs & into production,” Network Operators

One message came through clearly from today’s “AI/ML Adoption by SPs” panel at MPLSSD & AINETWORLD2022 in Paris, France: The value of AI/ML-powered network operations is clear, and it is time to get AI/ML out of the labs and into production. 

Service Providers stated that AI/ML-powered network operations can: 

  • Detect anomalies not detected by traditional tools 
  • Reduce false positives for alarms 
  • Predict future defects 
  • Reduce mean time to detect and repair (MTTD & MTTR) 
  • Provide benefits for both infrastructure and SD-WAN use cases 

Specific benefit examples stated included 

  • 30 million savings per year from initial use cases 
  • 50% of anomalies detected were not detected by existing tools 
  • Reduce level 1 to level 3 support time from 40 minutes to 5 minutes 
  • Predict cell radio battery failure 
  • Reduce truck rolls through anomaly prediction 
  • Paradigm reversing effect of MTTD going from a positive to a negative number 

Service Providers emphasized that AI/ML-based prediction works, and it is important to get out of POCs and give AI/ML-based platforms access to production data and get started. There are organizational and privacy challenges in implementing holistic data analysis, however, do not wait for the perfect environment, get started with the data that is accessible, and achieve benefits today. 

Panel sentiment was clear: get AI/ML out of the labs and into production.

There continues to be a mix of Service Providers primarily pursuing “do it yourself (DIY)” approaches and/or partnering with vendors. Partnering with vendors can help better define the use case and AI/ML-based modeling requirements. 

Both infrastructure and SD-WAN use cases are benefiting from AI/ML-powered operations. SD-WAN solution data and AI/ML analytics can be provided to benefit both managed service providers and SD-WAN customers, providing application experience insights, and tuning recommendations. 

AI/ML is not an all-knowing, all-powerful approach. However, AI/ML is already delivering real benefits to Service Providers. The ability to analyze large quantities of data, in a rapid fashion, to detect existing anomalies and predict future ones, reduces the load on L1 through L3 support, reducing MTTR, and increasing network uptime and quality of experience. It is time to get AI/ML of the labs and into production. 

Topology Matters for Networking Tools

A multilayer topology-aware network model is a critical building block for Network AIOps, resulting in: 

  • Network semantics aware anomaly detection 
  • Ad-hoc anomaly detection on networking constructs 
  • Topology aware autocorrelation 
  • Making machine learning (ML) results operationally relevant 
  • Network lifecycle aware ML 

Using this approach, Augtera Networks AIOps platform can correlate data & machine learning-based anomalies on multiple data sources to quickly determine the incident root. Augtera autocorrelates events and anomalies across multi-layer topologies and can create high-fidelity trouble tickets in platforms such as ServiceNow. 

Augtera's Network Aiops platform correlates many events into a single incident.
Augtera’s Network AIOps correlates many events into a single incident.

For more information, attend “The Power of Topology-aware ML for Log Data” presentation at MPLSSD & AINETWORLD22 on April 6th, at 15:20 pm. See agenda: https://www.uppersideconferences.com/mpls-sdn-nfv/mplswc_2022_agenda_day_2.html