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Log Anomaly Detection Using Machine Learning

June 21, 2021 | 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 “structure”, or why it is a necessity for accurate log anomaly detection.

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 “structure”, or why it is a necessity for accurate log anomaly detection.

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Using GPT-3 for plain language incident root cause from logs

January 9, 2021 | Larry Lancaster

This project is a favorite of mine and so I wanted to share a glimpse of what we've been up to with OpenAI's amazing GPT-3 language model. Today I'll be sharing a couple of straightforward results.

 

Plain Language root cause summaries. Try it for free!
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This project is a favorite of mine and so I wanted to share a glimpse of what we've been up to with OpenAI's amazing GPT-3 language model. Today I'll be sharing a couple of straightforward results. There are more advanced avenues we're exploring for our use of GPT-3, such as fine-tuning (custom pre-training for specific datasets); you'll hear none of that today, but if you're interested in this topic, follow this blog for updates.

 

You can also see some real-world results from our customer base here.

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Virtual tracing: A simpler alternative to distributed tracing for troubleshooting

July 21, 2020 | Larry Lancaster

Distributed tracing is commonly used in Application Performance Monitoring (APM) to monitor and manage application performance, giving a view into what parts of a transaction call chain are slowest. It is a powerful tool for monitoring call completion times and examining particular requests and transactions.

The promise of tracing

Distributed tracing is commonly used in Application Performance Monitoring (APM) to monitor and manage application performance, giving a view into what parts of a transaction call chain are slowest. It is a powerful tool for monitoring call completion times and examining particular requests and transactions.

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Is Autonomous monitoring the anomaly detection you actually wanted?

April 15, 2020 | Larry Lancaster

Automatically Spot Critical Incidents and Show Me Root Cause

That's what I wanted from a tool when I first heard of anomaly detection. I wanted it to do this based only on the logs and metrics it ingests, and alert me right away, with all this context baked in...

Automatically Spot Critical Incidents and Show Me Root Cause

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Deploying into Production: The need for a Red Light

July 23, 2019 | Larry Lancaster

As scale and complexity grow, there are diminishing returns from pre-deployment testing. A test writer cannot envision the combinatoric explosion of coincidences that yield calamity. We must accept that deploying into production is the only definitive test.

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Structure is Strategic

October 31, 2018 | Larry Lancaster

We structure machine data at scale

Zebrium helps dev and test engineers find hidden issues in tests that “pass”, find root-cause faster than ever, and validate builds with self-maintaining problem signatures. We ingest, structure, and auto-analyze machine data - logs, stats, and config - collected from test runs.

 

We structure machine data at scale

 

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