Cloud Native Observability Foundation gives attendees a hands-on grounding in observability concepts, terminology, and best practices across two days. The course also covers some of the most popular tools and frameworks for putting observability into production. It also explores how AIOps can use emerging AI and machine learning technologies. These technologies help automate IT operations, spot patterns, and resolve issues intelligently.
The course organizes into modules with equal parts lecture and hands-on exercises. Day one opens with an infrastructure observability lab, then moves into logging and log management. Students generate and aggregate application logs with Fluent Bit and Grafana Loki. A distributed tracing module follows, capturing and exporting traces with OpenTelemetry and Grafana Tempo. Day one closes with a metrics module, where attendees instrument applications using OpenTelemetry and Prometheus.
Day two opens with monitoring, alerting, and event management, working with alerts through Grafana and Prometheus. It then moves into best practices, where students drive operational autoscaling using custom metrics. A microservice mapping module has attendees graph service topology with Grafana Tempo. The course closes with an AIOps module where students work hands-on with K8sGPT to triage issues intelligently. Throughout, students build containerized applications, deploy them in a Kubernetes environment, and explore tools such as OpenTelemetry, Prometheus, Grafana, and Loki. They work with features like log search, metrics charting, tracing, service graphing, and metrics-driven autoscaling.
By the end, attendees clearly understand why observability matters in cloud native environments. They also gain the tools and techniques to apply when developing applications or managing infrastructure.
Who Should Attend
K8s operators, Developers, IT and SREs
What Attendees Will Learn
Upon completing Cloud Native Observability Foundation, attendees will be able to:
- Explain observability core concepts and terminology
- Collect and manage application logs using Fluent Bit and Grafana Loki
- Apply distributed tracing using OpenTelemetry and Grafana Tempo
- Capture application metrics using OpenTelemetry and Prometheus
- Configure monitoring, alerting, and event management with Grafana and Prometheus
- Apply cloud native observability best practices, including metrics-driven autoscaling
- Map microservice topology using distributed system service graphing
- Apply AIOps techniques for observability using tools such as K8sGPT
Prerequisites
Attendees should have taken the RX-M “Docker Foundation” (Containers, Images, Containers in Practice) or “Kubernetes Foundation” (Containers & Orchestration, Kubernetes Architecture) courses, or have equivalent knowledge.