Notes

Every folder below is one of two things: a book — a README.md table of contents whose chapters wikilink out to concept notes instead of duplicating them — or an applied/reference folder (Projects) that the books link into. Single-tool/concept reference notes (e.g. Mimir, GitOps, Envoy) live in a reference/ subfolder inside the one book they belong to most, rather than in a separate staging folder. Start at a book’s README.md; follow wikilinks from there rather than browsing files directly.

MAANG interview-prep core

• Data Structures & Algorithms — Python foundations through advanced DS/algorithms and MAANG interview mastery
• Low-Level Design — OOP, SOLID, UML, and design patterns for LLD interviews
• Object-Oriented Programming — paradigm foundations through OOP at system scale
• System Design — Principal/Staff-level system design reference collection
• Operating Systems — processes, memory, file systems, and Linux internals at interview depth
• Computer Networks — Ethernet through QUIC, DNS, HTTP, and cloud networking
• Database Management Systems — relational foundations through distributed databases and NoSQL
• Aptitude — quantitative, logical, and verbal prep for aptitude-gated pipelines

Observability & SRE

• Observability Engineering — the full discipline, foundations through AI-driven operations
• Prometheus — monitoring foundations through PromQL and production operation
• Grafana Cloud — platform foundations through Mimir/Loki/Tempo/Pyroscope
• Site Reliability Engineering — the 184-chapter SRE curriculum, foundations through Staff/Principal interview prep

Platform & cloud-native engineering

• Kubernetes — cloud-native foundations through CKAD/CKA/CKS depth
• Kubernetes Platform Engineering — multi-tenancy, platform automation, Helm, Crossplane
• Infrastructure Platform Engineering — IaC, Terraform/OpenTofu, cloud platform design
• Internal Developer Platforms — IDP fundamentals, Backstage, golden paths
• Platform Engineering Fundamentals — platform-as-a-product thinking, DORA/SPACE metrics
• CI/CD Platform Engineering — pipeline foundations through GitHub Actions, Argo Workflows, Tekton
• Patterns — reusable engineering patterns across OOD, distributed systems, and agentic AI

AI & data systems

• AI & LLM Foundations — the pre-agentic substrate through turning a raw model API into a dependable component
• Agentic AI Engineering — agent cognition, memory, planning, tools, retrieval, and context engineering
• Building & Evaluating Agents — single- and multi-agent systems, evaluation, and the framework landscape
• Production Agent Systems — infrastructure, observability, reliability/security, performance/cost, and platform engineering
• AI Architecture & System Design — the cross-cutting pattern catalog and enterprise system-design case studies
• Agentic AI: Projects & Engineering Mastery — hands-on builds, Principal/Staff-level judgment, and reference appendices
• Data Engineering — modeling, storage, ingestion, Spark/Flink, pipeline observability

Personal practice

• Productivity for Knowledge Workers — self-management, PKM, task systems, digital productivity
• Philosophy — cognitive biases, mental models, stoic practice

Applied & reference

• Projects — real, running systems documented end to end (SignalForge, the ShipSolid platform)

Metadata

Author	Amit Singh
Scope	notes