Lightstep Releases Change Intelligence
February 04, 2021
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Lightstep announced the general availability of Change Intelligence.

While AIOps is frequently advertised as a way to dramatically improve IT operations, it often fails to deliver, in part because today’s software applications are too dynamic: software, infrastructure, and user behavior are all changing faster than ever before. Lightstep has embraced those changes and put them at the center of analyzing application performance with Change Intelligence, inspired by work done by the Lightstep CEO Ben Sigelman on Google’s Monarch project.

The X-factor that makes Change Intelligence possible is Lightstep’s time-series database, which can process over a trillion events each day and is built by the same engineers that worked on the Monarch project at Google. Monarch is the globally-distributed in-memory time series database system in Google, that is used internally to monitor the availability, correctness, performance, load, and other aspects of billion-users scale applications and systems at Google. By tightly integrating these metrics with Lightstep’s existing distributed tracing data, engineers can connect cause and effect faster than what was previously possible.

“We took inspiration from the technology we built at Google, took it to the next level, and made it generally available to all Lightstep users,” said Ben Sigelman, Co-Founder and CEO of Lightstep. “With Change Intelligence, any developer, operator, or SRE can instantly understand changes in their service’s health and – most importantly – what caused those changes. In this way, we’re able to actually deliver on the promise of AIOps: to automate the process of investigating changes within complex systems.”

“The truth is that companies are already drowning in data from dashboards, alerts, endless logs – as an industry we’re so afraid of missing data that we collect all of it,” said Daniel ‘Spoons’ Spoonhower, Co-Founder and Chief Architect of Lightstep. “But from talking with customers, we’ve learned that this can create just as many problems as it solves. We’re not looking to add more data or noise – we’re looking to find root causes and resolve issues faster.”

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