Log data is like "closed-captioned TV" for a software system, said Trevor Parsons, cofounder and chief scientist at Logentries, which provides log management and analytics software as a service. "It's essentially recording everything that happens in the system, including all user actions and system actions."
That can amount to tens of thousands of events per second, so finding meaning in all that data can be a challenge. Traditional search languages such as SQL can do it, but they often require considerable technical skill, putting them out of reach for most business users.
"Tools like Splunk have shown that log data can be used for lots of use cases, but what nobody has done is make it easy," according to Parsons.
Promising a more user-friendly alternative, the Logentries Query Language was designed to enable users throughout an organization to not only collect and search log data in real-time, but also to analyze it for high-level trends. Rather than simply monitoring performance, it aims to help shed light on usage data in particular, such as which pages on a company's website are most popular among its top customers.
Armed with such information, business users can then make better decisions.
"IT operations are often about keeping core systems up and running, but we're starting to see log data used for analytics and insight into usage patterns," Parsons said. "People are using it as a BI tool."
With search functions such as count, sum, average, minimum, group by and sort, the Logentries Query Language can see high-level trend reports and fine-grained performance details from a single tool, the company says. It's available now as part of the cloud-based Logentries service, which comes in free and paid versions.
Log data will become particularly important as the development of the Internet of Things (IoT) progresses, Parsons said.
"All these connected devices produce log data like exhaust fumes from a car," he said. "If you can capture it all in one place, you're sitting on a mine of information."