Observability Beyond Monitoring

Building Intelligent, Scalable, and Resilient Software Systems

🇬🇧 English

From Monitoring to Intelligent Observability

Modern software systems generate an ever growing amount of telemetry, but collecting metrics, logs, and traces is only the beginning. As cloud native architectures, AI powered applications, LLMs, and platform engineering become more complex, teams need observability strategies that provide actionable insights instead of isolated data.

In this course, you’ll discover how modern observability helps engineering teams understand distributed systems, accelerate incident response, improve developer experience, and operate reliable applications across cloud, AI, and serverless environments.

Observability for the Next Generation of Software Systems

This course combines conference talks, technical articles, and practical case studies to explore observability from multiple perspectives. You’ll learn how to automate observability platforms, apply OpenTelemetry to AI workloads, improve alert quality using statistical methods, strengthen LLM development through observability, and establish observability as a core capability of platform engineering.

Whether you’re building cloud native platforms, operating AI applications, or modernizing enterprise infrastructure, this course provides practical knowledge you can apply immediately.

Take Your Skills to The Next Level

Session | Simplifying and Scaling Observability for Non Enterprise Teams | Benjamin Lykins

Learn how to automate observability platforms using Terraform, Nomad, Vault, Grafana, and Infrastructure as Code. Discover practical deployment patterns, dynamic configuration, and automation strategies that make enterprise grade observability accessible to smaller engineering teams.

Session | De slobbing AI Observability with OpenTelemetry | Robin Jungbauer

Explore how OpenTelemetry enables observability for LLMs, AI agents, and modern AI infrastructure. Learn how to monitor autonomous systems, improve transparency, and detect issues such as hallucinations, prompt injection, and data leakage.

Article | Generative AI and Observability in the Serverless World | Diana Todea

Understand how AIOps, MLOps, and LLM observability are transforming DevOps. Discover how machine learning improves automation, predictive operations, and reliability across serverless and cloud native environments.

Article | Observability: The Statistics Behind the Alerts | Dave McAllister

Learn why effective observability depends on more than dashboards. Explore how mean, median, mode, and other statistical concepts help reduce alert noise, improve monitoring accuracy, and create more meaningful operational insights.

Article | Accelerating the LLM Development Cycle with Observability | Torsten Bøgh Köster

Discover why observability is essential for developing reliable LLM applications. Learn how telemetry supports quality assurance, debugging, evaluation, and continuous improvement throughout the AI development lifecycle.

Fullstack Live Event Recording | Embedding Observability as a Platform Engineering Pillar | Stelios Moschos

See how observability becomes a strategic capability within platform engineering. Learn practical patterns including observability as code, golden paths, self service platforms, and scalable monitoring across AWS, containers, serverless systems, and Infrastructure as Code.

Expert Knowledge for...

Platform Engineers who want to build scalable and self service observability platforms.
DevOps Engineers who want to automate observability across cloud native infrastructure.
Site Reliability Engineers who want to improve incident detection and operational resilience.
Cloud Architects who want to implement observability for distributed and serverless systems.
AI Engineers who want to monitor LLM applications and agent based AI systems effectively.

Complete the Course and Learn How to...

Build scalable observability platforms using automation and Infrastructure as Code.
Monitor AI and LLM applications with OpenTelemetry and modern telemetry standards.
Improve alert quality using statistical analysis and meaningful metrics.
Accelerate AI development through observability driven quality assurance.
Embed observability as a fundamental pillar of platform engineering.