Interview Monitoring biz VictoriaMetrics is relatively unusual in its field.
It is yet to accept external investment, preferring instead to try to grow organically rather than being forced to through a private equity meat grinder by committing to grow by X every year until the investor exits.
In 100 percent of license changes, it's only a matter of money.
Khavronenko and his colleagues founded VictoriaMetrics in Kyiv, Ukraine, in 2018, although it is now headquartered in San Francisco.
The company operates open source time series database monitoring.
Monitoring solutions like VictoriaMetrics' product both record and query telemetry and metrics from a variety of sources.
Talk of avoiding pressure from investors inevitably leads the conversation to the recent moves towards license changes in the open source world.
VictoriaMetrics uses an Apache 2 license for its open source product, but the enterprise tooling is resolutely closed source and requires an activation key.
The company claims it can store millions of data points per second on a single instance or scale across multiple datacenters.
VictoriaMetrics' enterprise incarnation adds some extra functions, including improved alerts, machine learning for anomaly detection, and Kafka integration.
Perhaps most importantly for enterprise users, it also increases security and support directly from the company rather than the community.
The enterprise product is currently being offered under a 60-day free trial.
The company says it remains enthusiastic about open source, and values the community that has followed it from its beginnings on GitHub to where it is today, Khavronenko wants us to know.
Khavronenko also praises the feedback it gets from the community but admits that while VictoriaMetrics is receiving plenty of feature requests, it can't accept them all.
Not even from big companies with potentially deep pockets.
Particularly not if that feature has a minimal use case unlikely to benefit the rest of the community.
For the future, the co-founder sees potential in AI and machine learning - the company already has some machine learning in its anomaly detection, which was trained on historical time series data.
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Or perhaps tell the human that they're collecting too much data.
As Khavronenko notes, the amount of data collected continues to grow.
This Cyber News was published on go.theregister.com. Publication date: Mon, 11 Dec 2023 10:43:06 +0000