For final-year & early-career engineers
Browse courses
Beginner and Intermediate are free; Advanced modules are ₹999. Filter by level or search by skill. 21 courses available with current filters.
AI-Augmented Workflows end-to-end
AI-Augmented Workflows end-to-end
The capstone of the AI-augmented track. We take a small feature from request → branch → code → tests → PR → review → deploy → observe, with AI involved at every phase and a single prompt log as the spine. Then we triage a production incident with AI as a triage partner, while protecting secrets and avoiding fabrication risks. The deliverable is an evidence pack that future reviewers (or hiring managers) can… Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan
CI/CD: pipelines, environments, and AI-generated workflows
CI/CD: pipelines, environments, and AI-generated workflows
Pipelines are how software actually ships. This module teaches the anatomy of a CI/CD pipeline (independent of any one tool), then makes it concrete in GitHub Actions and GitLab CI side-by-side. We add environment gates, secrets, and a choice of deployment strategy. The lab generates a pipeline with AI as a pair and then critically reviews what AI got wrong — pipelines are exactly the place where AI is fluent… Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan
Containerization with Docker and Compose
Containerization with Docker and Compose
The minimum container literacy a working engineer needs. Multi-stage builds, Compose for local dev, the difference between `docker run` and `docker compose up`, and how to debug from outside the container. Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan
Distributed Tracing & TraceQL
Distributed Tracing & TraceQL
Metrics say p95 is high. Traces show *which* span — SNS publish vs S3 put — ate the time. TraceQL lets you ask about the *shape* of the request tree, not just attributes. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-02-metrics-and-logs System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana ·…
Amit Ranjan
Infrastructure as Code (Terraform + Pulumi)
Infrastructure as Code (Terraform + Pulumi)
A pragmatic intro: HCL fundamentals, a real `plan` / `apply` cycle, why state matters, and what GitOps looks like for cluster IaC. Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan
Kubernetes Observability on Kind
Kubernetes Observability on Kind
Compose taught the signals. Kubernetes is where MNCs actually run them — ServiceMonitors, Operators, and burn-rate alerts as CRDs. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-04-otel-collector; Kind installed System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki ·…
Amit Ranjan
Mastering AI-Assisted Development & Vibe Coding
Mastering AI-Assisted Development & Vibe Coding
A free 3-month, day-by-day program for final-year students and early-career engineers. Go from your first structured AI prompt to shipping a production-grade, AI-built application — prompting, Copilot, Cursor, Claude Code, visual AI builders, full-stack work, MCP, agents, SLMs, and n8n automation.
Amit Ranjan
Metrics & Logs: PromQL, Alerting, Loki
Metrics & Logs: PromQL, Alerting, Loki
A spike hits `/orders`. Without PromQL and structured logs you guess. With recording rules + LogQL you jump from alert → series → log line in one pane. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-01-foundations-lgtm System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki…
Amit Ranjan
Observability Foundations: LGTM + LocalStack Order Pipeline
Observability Foundations: LGTM + LocalStack Order Pipeline
At 3am an order API returns 202 but nothing lands in S3. Fixed dashboards say “CPU fine.” Observability means you can ask a *new* question — which hop broke? — without shipping code. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: Module 14-observability (pillars intro) recommended; Docker Desktop required. System under observation: api (Express) → SNS → SQS →…
Amit Ranjan
Observability: logs, metrics, traces
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.
Amit Ranjan
On-call, Postmortems & Chaos
On-call, Postmortems & Chaos
Alerts without process are noise. Chaos without a steady-state hypothesis is a stunt. MNCs formalize on-call, blameless postmortems, and declarative fault injection. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-07-perf-and-sre System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana ·…
Amit Ranjan
OpenTelemetry Collector Pipelines
OpenTelemetry Collector Pipelines
Apps should speak OTLP to one local endpoint and forget backends. The Collector is the data plane MNCs use to batch, scrub PII, sample, and fan-out. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-03-distributed-tracing System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki…
Amit Ranjan
Performance, SLOs & Data-store Signals
Performance, SLOs & Data-store Signals
One availability SLO on “the api service” can be green while users wait forever for async fulfillment. MNCs define SLIs per *user journey* and write error-budget policies before the incident. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-06-profiling-and-ebpf System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07)…
Amit Ranjan
Platform Observability: Cost, Governance, as-Code
Platform Observability: Cost, Governance, as-Code
Signal volume without governance becomes a second outage: the bill. Platforms win by golden paths, Obs-as-code, and clear vendor vs OSS tradeoffs. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-08-oncall-and-incidents System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki…
Amit Ranjan
Production Capstone & Portfolio
Production Capstone & Portfolio
Nobody hires “finished a course.” They hire evidence: a running system lineage, chaos catalog, SLOs, and a walkthrough you can narrate. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-01 through obs-09 System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki · Tempo ·…
Amit Ranjan
Profiling, eBPF, Beyla & Hubble
Profiling, eBPF, Beyla & Hubble
Traces point at a slow span. Profiles name the function. eBPF (Beyla) gives a zero-code floor when you cannot rebuild every service tomorrow. Audience: Final-year students and early-career engineers (0–3 years). Prerequisites: obs-05-k8s-observability System under observation: api (Express) → SNS → SQS → worker → S3 (+ Postgres/Redis from phase 07) Stack: Grafana · Prometheus/Mimir · Loki · Tempo…
Amit Ranjan
Security & Supply Chain
Security & Supply Chain
Practical security for the AI-augmented engineer: OWASP Top 10 you'll actually face, secrets management, SBOM + signing for the container, and a triage discipline for scanner output. Plus the constraint of not leaking sensitive context to AI during triage (callback to Module 17). Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
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
System Architecture: monolith, microservices, event-driven, serverless
System Architecture: monolith, microservices, event-driven, serverless
Architecture choices compound. This module teaches the decision framework — not the trends — and applies it through a case-study walkthrough. Learners leave with a written ADR for a product they own (or imagine).
Amit Ranjan
Technology Selection: ADRs and weighted scoring
Technology Selection: ADRs and weighted scoring
Picking a framework, database, queue, or cloud is the most common high-stakes decision early-career engineers face. This module gives them a repeatable framework: weighted scoring + ADR. The lab is to make and document a real choice.
Amit Ranjan
Testing & Quality
Testing & Quality
The testing pyramid, plus modern wrinkles: integration tests with real services via Testcontainers, and AI-generated tests with calibrated trust. Built for final-year students and early-career engineers. Includes a structured lesson plan and hands-on exercises you can complete with an AI coding assistant.
Amit Ranjan