What if your observability tools could predict incidents instead of just reacting to them?

In this webinar, CodiLime’s AI/ML expert Tomasz Janaszka and Engineering Manager Edyta Kałka reveal how GenAI can catapult observability beyond traditional dashboards and logs. Discover how combining telemetry data with large language models opens the door to powerful forecasting, faster troubleshooting, and more intelligent automation.

🔍 You’ll learn: 🔸 The challenges of modern observability 🔸 How GenAI can help analyze telemetry data 🔸 Real-life use cases, including predictions and automated root cause analysis 🔸 A behind-the-scenes look at the architecture 🔸 What this means for the future of NetOps

Perfect for network engineers, SREs, DevOps, and decision-makers responsible for the future of complex observability platforms.

[00:00 - 00:38] Introductions [00:39 - 01:19] Agenda [01:20 - 04:19] Current state of observability platforms (challenges and areas of improvement) [04:20 - 05:44] Demonstration: The environment [05:45 - 10:27] Demonstration: Using ML for Timeseries Forecasting [10:28 - 14:55] Demonstration: Using AI-powered natural language chat to faster retrieve and better present data [14:56 - 17:09] Demonstration: Extending situation awareness by forecasting [17:10 - 19:24] Demonstration: Extending situation awareness by data from network layer [19:25 - 20:53] Benefit analysis - Save time! [20:54 - 29:44] Demonstration: Automatic error detection, log analytics, root cause analysis, and recommended resolution actions [29:45 - 30:59] Summary of AI techniques used [31:00 - 32:28] Reported gains of AI/ChatOps in numbers [32:30 - 34:58] Deployment challenges [34:59 - 35:50] Three most important takeaways