“Holy crap. You guys are awesome… I’m already finding issues I wasn’t aware of. The ability to click on a piece of the log and find similar items is fantastic.”
18 months ago, we began developing Scalyr, which combines server monitoring, log collection and analysis, alerts, dashboards, and other functions into a practical, comprehensive DevOps tool. Last fall, we began real-world deployments in a closed beta program. The quote above was a comment – unsolicited – from one of our beta customers. Today, we’re excited to announce that we have exited beta and the service is available for all.
We are a team of ex-Google engineers with years of production experience. We know what it’s like to be on call, get a trouble alert, and not have enough information to narrow down the problem. We know what it’s like to juggle half a dozen balky monitoring systems in an effort to get a complete picture. We know what it’s like to scramble to respond to a crisis, casting about to find out what’s wrong, and have to wait agonizing seconds for each new graph to load. We know what it’s like to *know* that the information you need is in the logs somewhere, but not be able to get to it without taking time you don’t have to write code you don’t want to maintain.
Scalyr is the straightforward, comprehensive monitoring tool we’d always wanted. Using a simple agent, you upload logs, system metrics, custom metrics, and other data in realtime to our custom-built database. You can then search, analyze, graph, build dashboards, and define alerts, all in a single easy-to-use package. It’s a service, so there’s no management overhead. And it’s fast, practical, and powerful. So if your current monitoring solution is frustrating you, if you can’t get the information you need when you need it, or you’re spending too much time juggling tools, Scalyr is for you.
The reaction from our beta customers has been gratifyingly positive. More unsolicited quotes:
“This is the kind of tool… well, I sat down yesterday morning to glance at something, found myself exploring, and the next thing I knew it was time for lunch.”
“Love the performance.”
“You get an ‘aha’ moment when you’ve found it possible to pinpoint something that’s gone wrong using filters, facets and pivots.”
“This is great!”
“You guys are doing great work!”
“+1 on wallview. Great!”
“[log exploration] is great!”
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