Loggly Gamut Search: High Performance for Power Users (and everybody else)

Today we are announcing Loggly Gamut Search™, a new powerful search feature that will become available to all Loggly users over the coming weeks.

Gamut Search is specifically designed to deliver near instant responsiveness even for searches over massive data volumes and long time periods. More and more users are dealing with log data in the range of hundreds of gigabytes or terabytes per day, and log retention times of 30 or more days. Submitting a search query over a long date range can make you stare at a spinning wheel for minutes or more… Exactly NOT what you need when you’re troubleshooting a server outage that impacts your revenue and literally lets time be money. Trying to get that complex RegEx right can easily become a task that will simply drive you crazy. That spinning wheel on your screen is a productivity killer and a torture device at the same time.

Goodbye Spin Wheels, Hello Gamut Search

Wouldn’t it be nice if, instead of staring at a throbber, you would see search results appear on your screen instantly as they are being found during the search, and while the search still runs? So you could actually get to work instead of waiting for the entire search to complete?

Well, that is exactly what Gamut Search does: it breaks your search into small time slices and gives you search results in the very moment they are being found, instantly and progressively. On top of that, we have re-engineered the search architecture and caching to allow for much better performance.

Gamut Search also employs some changes to the user interface to speed up navigation. With every search, you see a graphical event timeline showing when the log events represented in your search results occurred. You can click on the event timeline or highlight any time period with your mouse to zoom in on specific time periods. You can also zoom out with a single click.

No more spinning wheels, no more fear to hit the search button, no more going crazy – ain’t that good news 🙂

A Look behind the Scenes

If you want to know more about how Gamut Search was implemented, check out this detailed blog post or this video by Jon Gifford and Derek Jones.

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