Crash Course: AI-native observability

Overview

Crash Course: AI-native observability is a multi-session online course focused on building and operating modern observability in complex distributed systems. The program emphasizes integrating Logs, Metrics, Error Tracking, and Distributed Tracing into a cohesive monitoring strategy, with a dedicated look at how AI can enhance incident analysis, anomaly detection, and rapid diagnosis. Taught by Yozhef Hisem, a Solution Architect with MacPaw, the course is designed for engineers who want to understand how to move from chaotic monitoring to a unified observability approach that speeds up problem resolution and reduces MTTR.

What you will learn

The course covers the end-to-end observability lifecycle, including how to design effective logging, structure and correlate logs, manage events and business events, and implement robust tracing across distributed systems. It presents a practical framework for combining logs, metrics, and tracing into a single, understandable system, rather than treating them as separate silos. A core emphasis is the application of AI to assist in incident analysis, detect anomalies, and accelerate root cause identification. Concrete outcomes include a checklist for incident response, techniques for faster root cause analysis, and guidance for implementing or refining an observability strategy within a team or organization based on real industry experience.

Agenda and format

The program consists of three two-hour online sessions conducted via Zoom. Each session is structured to deliver theory, live demonstrations, and hands-on exercises. Day 1 focuses on production issues and the foundations of Observability, including how to structure and interpret logs and events. Day 2 covers Metrics and Alerting, exploring golden signals, dashboards, and how AI can assist in metrics analysis. Day 3 delves into Distributed Tracing, OpenTelemetry, and tracing architectures, with emphasis on identifying bottlenecks in multi-service environments. In addition to lectures, the schedule includes practical sessions on building a unified Observability standard and applying AI tools to real-world datasets and incidents.

Format and language

The event format is online with sessions starting at 18:30 Kyiv time (GMT+3). Platform details indicate Zoom as the main streaming venue, with access links provided on the landing page prior to the sessions and recordings available afterward on the learning platform. The event language is Ukrainian, with presentations delivered in Ukrainian and occasional English terms. Materials and recordings are accessible through the course platform for registered participants.

Who should attend

The course targets Junior+ developers, Technical Leads, Architects, and Staff/Principal Engineers who want to advance their understanding of Observability and improve incident response capabilities. It is especially relevant to teams building or maturing Observability strategies within modern, distributed architectures, who are looking to incorporate AI-driven analysis into their workflows.

Speakers and mentors

Mentor for the course is Yozhef Hisem, a Solution Architect at MacPaw Inc., who brings extensive experience in architecture, testing, Docker, Redis, and API solutions, and who actively participates in speaking engagements and educational programs across the tech community.

About the format and accessibility

The course runs three online sessions with additional access to recordings and course materials for one year on the learning platform. Attendees receive a certificate of participation upon completion of any required homework tasks. A price is listed as 7 800 UAH with earlier-bird and group discounts indicated on the event page. This structure supports flexible learning for professionals balancing work and education while providing long-term access to the course content and community channels for ongoing support.