Using machine learning to detect anomalies in logs

June 5, 2019 | Larry Lancaster
At Zebrium, we have a saying: “Structure First”. We talk a lot about structuring because it allows us to do amazing things with log data. But most people don’t know what we mean when we say the word “structure”, or why it allows for amazing things like anomaly detection. This is a gentle and intuitive introduction to “structure” as we mean it.

At Zebrium, we have a saying: “Structure First”. We talk a lot about structuring because it allows us to do amazing things with log data. But most people don’t know what we mean when we say the word “structure”, or why it allows for amazing things like anomaly detection. This is a gentle and intuitive introduction to “structure” as we mean it.

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Perfectly structuring logs without parsing

May 16, 2019 | Gavin Cohen

Developers and testers constantly use log files and metrics to find and troubleshoot failures. But their lack of structure makes extracting useful information without data wrangling, regexes and parsing scripts a challenge.

Developers and testers constantly use log files and metrics to find and troubleshoot failures. But their lack of structure makes extracting useful information without data wrangling, regexes and parsing scripts a challenge.

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Troubleshooting the easy way

February 9, 2019 | Gavin Cohen

It takes great skill, tenacity and sometimes blind luck to find the root cause of a technical issue. Zebrium has created a better way!

It takes great skill, tenacity and sometimes blind luck to find the root cause of a technical issue. And for complex problems, more often than not, it involves leveraging log files, metrics and traces.  Whether you’re a tester triaging problems found during automated test, or a developer assisting with a critical escalation, dealing with data is painful.

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