Meeting the Augtera Team
I met Rahul Aggarwal in June of 2022 and took an immediate liking to the team. Early in a joint customer engagement, it became very clear that there was something special here – not just special but BIG. The customer knew it too. Little did I know it would lead to a dramatic personal change as well.
The BIG is AI, the special is that it will dramatically disrupt the networking industry that Cisco has dominated for 30 years in ways that white box, disaggregation, and software defined will never match. Augtera is an AI platform purpose-built for proactively identifying network disruptions and dramatically reducing downtime. Soon, Augtera will use its advanced AI/ML to provide suggested mitigations for some common network problems. Over time, we will instantly and automatically solve them with little to no human intervention.
Our large-scale enterprise and service provider customers are already seeing 90%+ reduction in time to detect, 55%+ reduction in mitigation times, and 4x increase in time between revenue impacting incidents and we are only just getting started.
I’ve been fortunate to have worked with some great leaders and visionaries, helping to bring disruption to the world of networking, supporting our war fighters in the most critical of missions, and building lifelong relationships along the way. Although I had just met him, I knew Rahul was going to be another one of those leaders.
SONiC and Dell’s work there will be transformative to the networking world, but it won’t solve the reality that networks have surpassed Human Scale. Augtera already does. At Dell, I built the best team I have ever worked with and was well positioned for continued success – but after six months of sleepless nights it was obvious – the time to move was now.
Many Network Performance Monitoring (NPM) tools are out there; some of which have been the standard of IT organizations since Bill Clinton’s first term – Many are proprietary, victimizing customers with vendor lock; while some network vendors even have multiple platforms that are incompatible with each other. From the perspective of being able to look backward whether it is visualizing the network, monitor SNMP and syslog and even analyze flows; these legacy tools are static, failed to evolve and certainly are incapable of surviving, much less thriving in the era of AI/ML. No one will ever confuse legacy NPM with “Best of Breed” anything, especially when it comes to protecting the security of their customers’ most trusted assets.
DevOps and Network Automation
Most enterprises have focused on the front end. Tools like Ansible and other Infrastructure such as Code Platforms focus on provisioning, configuration management and deployment. Once they are up and running, users are on their own setting thresholds and watching reruns of networking in the 90’s.
These days, every network and infrastructure vendor have some fancy GUI or widget that tells the user the “health” of the environment. It may even tell you when something breaks – but what it does not do is determine mean time to innocence or root cause analysis across silos. There is nothing agile or orchestrated about waiting for a dashboard to update after the phone calls and escalations have already started pouring in from end users.
Automating Network Observability with AI/ML
The elephant in the room is that there is no “automated” way to understand what is going on in these “automated” environments. Understanding the IT infrastructure of any modern enterprise has moved way beyond Human Scale.
There are billions of logs and metrics being created daily in a Fortune 500 environment and this is without even considering SD-WAN and Multi-Cloud connectivity. During a network outage or a security breach – teams do not have the time to sift through data manually one machine at a time only to deliver a root cause analysis 6 weeks later. Shareholders and customers are NOT that patient.
Augtera transforms IT operations by automating the observability of the network. We do that by using best in breed AI/ML – learning the network automatically from all dimensions and normalizing the data in a single model that predicts outages and downtime regardless of where it’s located in the network. Automating the observability of the network is the next step in any digital transformation, shifting the value of network operations from reactive to valuing prevention and preparation when and if the unfortunate happens.
