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.

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.

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...

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.

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.