Observability: logs, metrics, traces
Observability is what tells you whether the thing you just deployed is OK. We teach the three pillars (logs / metrics / traces), then instrument a real service with OpenTelemetry and watch the data flow into a Prometheus + Grafana stack. The signature artifact is a triage of a synthetic incident — given only logs, metrics, and traces, the learner finds and fixes the root cause without reading source code.
Taught by Amit Ranjan
What you'll learn
- The th\n\n**Next step:** Continue with free Observability Phases 01–10 (start at obs-01-foundations-lgtm) — same LGTM + order-pipeline depth path for early-career engineers.\n
Course content
1 sections · 4 lessons · 1h 52m
1.Module materials
4 lessons- Session lesson29mPreviewOpen preview
- Exercises31m
- Session guide26m
- Facilitator notes26m
Instructor
Amit Ranjan
Industry practitioners teaching AI-augmented software engineering.
Reviews
No reviews yet.
More in this category
Foundations: Modern SDLC + the AI-Augmented Engineer
Foundations: Modern SDLC + the AI-Augmented Engineer
Built for final-year students and early-career engineers. A grounding module: we define the modern SDLC (Plan → Design → Develop → Test → Release → Operate → Learn), show where AI augmentation slots in, and reset expectations about what an engineer's day looks like when an AI assistant is part of the workflow. By the end, every learner has a one-page diagram of an SDLC for a real product and a written list of…
Amit Ranjan
AI-Assisted Development & Vibe Coding
AI-Assisted Development & Vibe Coding
The signature module of the program. Learners spend most of the session doing, not listening. We tour the major AI coding tools (Cursor, GitHub Copilot, Claude Code, Aider), introduce four prompt patterns, then run a debug lab where each learner fixes a broken FastAPI endpoint using AI as a pair-programmer and documents every prompt. The point is to make AI a habit, not a curiosity.
Amit Ranjan
Prompt Engineering for Developers
Prompt Engineering for Developers
Module 02 introduced four patterns. This module goes one layer deeper: few-shot, chaining, output evaluation, and the discipline of a prompt library. The lab is hands-on: each learner builds a small reusable library for one task they actually do.
Amit Ranjan
Software Design: SOLID, clean architecture, DDD basics
Software Design: SOLID, clean architecture, DDD basics
Most early-career engineers can recite SOLID but can't spot violations in their own code. This module teaches recognition — then practice — in two languages. We finish with a refactor lab where AI is the pair and the rule is "tests stay green".
Amit Ranjan