Observability: Logs, Metrics & Tracing
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About this course
Observability: Logs, Metrics & Tracing teaches how engineers find out what is wrong in a running system. It starts from a live outage, separating symptoms from causes, and introduces the three signals. It then covers structured logging, metric types and percentiles, Prometheus and PromQL, Grafana dashboards, SLIs, SLOs and error budgets, alerting, distributed tracing, OpenTelemetry, debugging production incidents across all three signals, and running observability at scale. The course has 175 lessons and about 1312 minutes of content. Each lesson is a short reading card with narration and diagrams, followed by MCQ practice with an explanation for every answer.
Who this observability course is for
Backend developers, DevOps and site reliability aspirants, and freshers who have just joined an on-call rotation will find the course matches the questions they face during an incident. It assumes you know how a web service handles requests; ideas from system design foundations help in the tracing and scale sections. If your services run on containers, Kubernetes fundamentals fits alongside. No prior Prometheus or Grafana experience is needed.
How MCQ practice works on Abekus
Each lesson is a short reading card with narration and diagrams, such as a picture of spans nesting inside a trace across three services, or a view of how an error budget shrinks as the burn rate rises. After the card, you answer MCQ practice items one at a time. Every answer comes with an explanation, so a wrong choice shows you why the correct option works. The course runs guided or self-paced, so you can follow the curriculum in order or move at your own pace. It is free with Abekus Pro, and otherwise it is paid in credits.
MCQ practice vs video courses for observability
Udemy and Coursera host long video courses on monitoring tools, often built around installing one stack and clicking through its screens. That format suits learners who want a guided setup. This course asks the questions that matter during an incident: which signal to check first, why an average latency hides a slow tail, whether a label will cause a cardinality explosion, or which alert will wake someone up for nothing. MCQ practice in short sessions suits learners who want that reasoning ready before their first on-call shift.
Best way to learn observability
Instrument a small service of your own while you study: add structured JSON logs, expose a counter and a latency histogram, and send a trace through two endpoints. Answer each MCQ before reading its explanation. Revisit Quantiles and Percentiles and Burn-rate Alerts a few days later, since both are easy to get wrong. When you reach Debugging Production Incidents, write a short postmortem for an outage you have seen or read about, using the metric to trace pivot from the lessons.