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Cause and Effect: Solving the Observability Conundrum
Manage episode 412756173 series 3559948
İçerik Eric Kavanagh tarafından sağlanmıştır. Bölümler, grafikler ve podcast açıklamaları dahil tüm podcast içeriği doğrudan Eric Kavanagh veya podcast platform ortağı tarafından yüklenir ve sağlanır. Birinin telif hakkıyla korunan çalışmanızı izniniz olmadan kullandığını düşünüyorsanız burada https://tr.player.fm/legal özetlenen süreci takip edebilirsiniz.
The pressure on application teams has never been greater. Whether for Large Language Models, Cloud-Native Apps, Hybrid Cloud, IoT, or other critical business services, these teams are accountable for solving problems quickly and effectively, regardless of growing complexity.
The good news? There's a whole new array of tools and technologies for helping enable application monitoring and troubleshooting. Observability vendors are everywhere, and the maturation of machine learning is changing the game. The bad news? It's still largely up to these teams to put it all together.
Check out this episode of InsideAnalysis to learn how Causal AI can solve this challenge! As the name suggests, this tecnology focuses on correlating observability streams in order to dynamically ascertain root cause analysis, and even fix mistakes automatically! Tune in to hear Host @eric_kavanagh interview Ellen Ruben of Causely.ai, as they explore how this fascinating new technology works.
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