Loggly announced Gamut Search, log analysis technology designed to respond instantly for searches over massive data volumes covering long time periods.
Rather than waiting hours or days for a query to complete, the new capabilities enable users to begin analyzing the entire range, or the “gamut” of their log data, immediately, in a highly interactive fashion.
“Consider that a single movie at TV quality is a gigabyte,” said Charlie Oppenheimer, CEO at Loggly. “Companies are now generating thousands of gigabytes of log data or more every day, but until now most log management platforms have bogged down when processing searches at this scale. Gamut Search offers an innovative architectural approach built on years of experience with billions of interactions and petabytes of data. There’s is no longer a need to constantly reduce scope. More importantly, these productivity gains translate into faster mean time to resolution and fewer revenue leaks.”
Gamut Search changes users’ relationship with log data. Previously, users would submit their large queries, and often wait long for them to run and return results. Gamut makes the entire log analysis process more interactive, allowing users to instantly see results that can quickly be modified and optimized based on search terms. With Gamut Search, each search request is broken down into small time slices that are computed dynamically. The most recent time slice is processed first and the results of that time slice are presented instantly. The system then progresses through each earlier slice until the entire request has been fulfilled. With Gamut Search, you get results immediately, instead of waiting for the entire search to be processed before seeing results. Users can take action more quickly.
Every search displays a graphical event timeline that shows when the log events represented in the search results occurred, simplifying navigation over time periods. In addition, they have one-click access to the full unfiltered collection of events that occurred immediately before or after an event of interest via Loggly Surround Search.
With Gamut Search, caching is also optimized to provide even faster response for subsequent requests. “As part of Loggly’s ongoing analysis of user behavior, we have discovered that more than 50 percent of all search and analysis interactions are based on subsets of previously queried data within the last 30 minutes,” said Jon Gifford, founder and chief search officer at Loggly. “As a result, Gamut Search provides memory-speed responsiveness for subsequent analyses, thereby further boosting user productivity.”
Summary Benefits
● Faster mean time to resolution eliminates revenue leaks: Users get near instant search results across huge data volumes and over long time periods.
● Time savings for developers and DevOps: Users benefit from the pre-processing that Loggly does on log data and can iterate on their queries much faster than before.
● A more satisfying user experience: Users start seeing data immediately and have greater transparency on query response through progress indicators.
● Usability improvements eliminate many of the annoying things about searching logs, such as re-generating queries multiple times to get a slightly different time slice.
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