Senser – a pioneer of zero-instrumentation production intelligence – recently emerged from stealth with $9.5 million in seed funding to launch an AIOps platform that utilizes Extended Berkeley Packet Filter (eBPF) technology to provide enterprises with deep insights into their complex cloud and IT environments. And the seed funding round was led by Eclipse with participation by Amdocs and other private investors.
Senser’s platform uses groundbreaking eBPF technology to collect dynamic, non-intrusive data with zero instrumentation or configuration required. And the platform also utilizes machine learning (ML) to deliver automated insights into root causes and business impact when issues like outages or service degradations arise. Senser’s AI-powered chatbot enables users from various technical backgrounds to quickly answer critical questions about their production environment using only natural language prompts.
As the adoption of cloud computing, microservices, and APIs has grown, cloud environments have become highly complex and interconnected, and businesses have increasingly turned to the observability sector to monitor these distributed service webs. However, traditional observability technology places a massive burden on organizations to implement, configure, and manage these tools and decode what a flood of alerts means for their bottom line.
Since legacy observability tools were designed to look at specific parts of a company’s environment (e.g., infrastructure, applications, or networks) in isolation without an overall view of business or user flows. And as a result, getting a complete picture of how services behave atop the environment requires tedious manual instrumentation or extensive configuration of modules and dashboards. But understanding the root cause and business impact of a system issue requires lengthy manual analysis, often while the clock is ticking on a critical failure.
Traditional application and performance monitoring (APM) and observability technology cost enterprises an average of 20-30% of overall infrastructure costs. But this does not include the expense of dedicated engineering resources to configure, customize, analyze, and maintain observability technology as a company’s cloud environment evolves.
Along with identifying service degradations, Senser’s technology helps companies manage the health and performance of their production environment more broadly. This includes identifying hidden drivers of cloud computing costs and leakage of potentially sensitive assets.
Since launching Senser in 2021, Krayden and co-founders Or Sadeh and Yuval Lev honed their skills as tech leaders at DriveNets, a leader in cloud-native networking solutions. And the company was selected for Intel Ignite’s startup accelerator in 2022.
KEY QUOTES:
“Industrial 4.0 apps — such as warehouse automation or robotics — and outdoor mapping apps like drones must run reliably on both clients and edge locations in order to power the foundation of physical industries. Through the underlying use of eBPF and machine learning, Senser is ensuring these apps are performing at the highest levels, while solving problems — like the staggering cost of configuration and maintenance, and the lack of usefull insights — in a unique way.”
- Lior Susan, founding partner of Eclipse
“Downtime costs enterprises an average of $1 million per hour and a long-term loss of customer trust. We built Senser to make it easy for SRE and DevOps leaders to go past alerts and dashboards and solve issues quickly. The average Senser customer reduces mean time to detect (MTTD) by 83% – an outcome made possible because eBPF enables immediate visibility across production systems with no overhead, and ML delivers answers, rather than alert floods.”
- Amir Krayden, Co-Founder and CEO of Senser
“Senser enables us to gain control over our environment with its unique zero-instrumentation approach. It takes minutes to deploy and automatically discover our complex environment. Senser uncovers blind spots that we were not necessarily monitoring, saving precious time in identifying, analyzing, and resolving service degradation issues.”
- Ohad Noam, director of site reliability engineering at blockchain company Consensys
