IT Interview Preparation

Core database concepts: relational vs non-relational, SQL, indexing, transactions, normalization, and scaling.

Cross-engine SQL fundamentals: SELECT, JOINs, GROUP BY, subqueries, CTEs, window functions, transactions, normalization, indexing, and query tuning.

PostgreSQL end to end: types, joins, CTEs, window functions, JSONB, indexes, MVCC, vacuum, partitioning, replication, and performance tuning.

Prisma v6, Drizzle, TypeORM, and Sequelize: schema design, migrations, relations, transactions, N+1, connection pooling, and modern ORM patterns for TypeScript backends.

Non-relational databases end to end: data models, storage engines, consistency, replication, sharding, transactions, and the main engines (MongoDB, Redis, DynamoDB, Cassandra, Neo4j).

MongoDB from CRUD and the aggregation pipeline to indexing, schema design, replica sets, sharding, transactions, and the WiredTiger storage engine.

Core JavaScript from the ground up: types, scope, closures, prototypes, this, the event loop, async patterns, and modern language features.

TypeScript from the type system's basics to advanced patterns: generics, utility types, narrowing, conditional and mapped types, and idioms for real-world code.

How JS engines work under the hood: V8 internals, parsing, JIT tiers, hidden classes, garbage collection, memory layout, and engine-level performance.

React from components and hooks to reconciliation, concurrent rendering, server components, and performance patterns.

Next.js framework: App Router, RSC, Server Actions, ISR/SSG/SSR, middleware, route handlers, Turbopack, image optimization, deployment.

Vue 3: Composition API, reactivity, components, directives, Pinia, Vue Router, Nuxt, performance, and ecosystem.

Building cross-platform mobile apps with React Native: Expo, navigation, lists, animations, native modules, Hermes, the new architecture, and shipping to stores.

Client state management: Redux Toolkit, Zustand, Jotai, MobX, Context, immutability, selectors, persistence, and architecture patterns.

Modern client-side data fetching: TanStack Query, SWR, caching, invalidation, optimistic updates, and the difference from client state.

Core Python from the ground up: types, data structures, functions, OOP, generators, decorators, type hints, and modern language features through Python 3.12+.

FastAPI fundamentals: path & query parameters, Pydantic v2 models, dependency injection, async handlers, routers, middleware, CORS, authentication (OAuth2/JWT), WebSockets, background tasks, lifespan events, file uploads, exception handling, testing with TestClient, settings management, and async SQLAlchemy integration.

Django 5.x: MTV architecture, ORM, class-based views, REST Framework, async views, caching, Celery, authentication, signals, and production best practices.

Deep dive into Python concurrency: the GIL, threading, multiprocessing, asyncio, concurrent.futures, and Python 3.12+ no-GIL experimental builds.

Pydantic v2 and SQLAlchemy 2.x: data validation, serialization, ORM declarative mapping, async sessions, relationship loading strategies, Alembic migrations, and production patterns for Python backends.

Python testing with pytest, fixtures, mocking, and async; plus modern tooling: uv, ruff, mypy, pyproject.toml, pre-commit, tox, and CI/CD.

Node.js runtime from fundamentals to production: the event loop, streams, async patterns, clustering, worker threads, memory, and performance.

NestJS framework: modules, providers/DI, controllers, decorators, pipes, guards, interceptors, exception filters, microservices, and testing.

Express.js fundamentals and limitations, Fastify v5 (schema validation, plugins, hooks, pino logging), Hono v4 (web-standards, multi-runtime, RPC mode), Elysia on Bun, edge deployment, WebSockets, and framework selection in 2026.

Modern JavaScript runtimes beyond Node: Deno's secure-by-default model, Bun's all-in-one toolchain, web standards, edge platforms, and migration trade-offs.

GraphQL fundamentals: schemas, resolvers, queries, mutations, subscriptions, DataLoader, federation, caching, codegen, security, and ecosystem tools.

gRPC fundamentals: Protocol Buffers (proto3), service definitions, the four communication patterns, code generation with buf, Node.js clients and servers, gRPC-Web, metadata, error codes, interceptors, deadlines, health checking, load balancing, NestJS integration, Connect protocol, and comparisons with REST, GraphQL, and tRPC.

Designing RESTful HTTP APIs: resources, methods, status codes, headers, versioning, pagination, errors, auth, caching, rate limiting, and OpenAPI tooling.

tRPC v11: end-to-end type-safe APIs without codegen. Routers, procedures, Zod validation, middleware, React Query integration, Next.js adapters, subscriptions, and testing.

Realtime web techniques: WebSocket protocol, Server-Sent Events, WebRTC peer connections, scaling, reconnection, presence, CRDTs, and managed realtime services.

Authentication and authorization fundamentals: JWT structure and verification, OAuth 2.0 / 2.1 flows, PKCE, OpenID Connect, token storage, refresh token rotation, revocation, passkeys/WebAuthn, SSO, multi-tenancy, and common attack vectors.

Asynchronous messaging end to end: why queues exist, delivery guarantees, BullMQ v5 (Queue, Worker, Job, flows, NestJS integration), RabbitMQ, Kafka, dead letter queues, idempotency, and scaling strategies.

Decomposition strategies, communication patterns, data consistency, resilience patterns (Circuit Breaker, Bulkhead, Saga), and operational concerns for building production microservices in 2026.

HTML end to end: semantic structure, forms, accessibility, metadata, performance hints, security attributes, and web components.

CSS from box model and selectors to flexbox, grid, custom properties, stacking contexts, container queries, cascade layers, and modern features.

Tailwind CSS from utility-first philosophy and responsive design to JIT, dark mode, theme customization, v4 CSS-first config, plugin authoring, and production optimization.

CSS-in-JS from core concepts and styled-components basics to Emotion, theming, dynamic styles, zero-runtime libraries (Vanilla Extract, Panda CSS, Linaria), SSR hydration, RSC compatibility, and migrating away from runtime solutions.

The browser-native component model: Custom Elements, Shadow DOM, HTML Templates, slots, lifecycle callbacks, form integration, accessibility, Lit 3.x, and SSR with Declarative Shadow DOM.

Browser platform APIs every front-end engineer should know: DOM, Fetch, observers, storage, workers, performance, and modern UX surfaces.

Measuring and optimizing front-end performance: Core Web Vitals, Lighthouse, lazy loading, caching, code splitting, edge delivery, and profiling tools.

Progressive Web Apps in depth: Service Worker lifecycle, caching strategies, Workbox, manifests, push notifications, background sync, and platform install nuances.

Core browser security model: Same-Origin Policy, CORS, XSS, CSP, CSRF, clickjacking, SRI, HTTPS/HSTS, cookie attributes, storage security, Trusted Types, and supply-chain attacks.

Testing front-end and Node code: Jest, Vitest, React Testing Library, Playwright, Cypress, mocking, contract tests, TDD, and CI integration.

Modern JS build tooling: Vite, Webpack, esbuild, Rollup, Turbopack, SWC, Babel, tree-shaking, code splitting, module formats.

Managing multiple packages and apps in one repo: pnpm/yarn/npm workspaces, Turborepo, Nx, Bazel, Changesets, caching, and CI strategies.

Logs, metrics, traces, and the OpenTelemetry ecosystem: instrumentation, the OTel SDK/Collector, distributed tracing, Prometheus/Grafana, SLI/SLO/SLA, sampling strategies, and Node.js OTel setup.

Amazon Aurora: architecture, storage layer, replicas, failover, Aurora Serverless, global databases, backtrack, and performance.

Amazon RDS (managed relational DBs, focused on Postgres): engines, Multi-AZ, read replicas, parameter groups, backups, Performance Insights, and operations.

Amazon Redshift: MPP data warehouse architecture, distribution/sort keys, columnar storage, Spectrum, Serverless, and performance tuning.

Amazon S3: object storage fundamentals, consistency model, storage classes, lifecycle, encryption, access control, and performance.

Amazon DynamoDB: key-value and document model, partition/sort keys, GSIs/LSIs, capacity modes, consistency, transactions, streams, and single-table design.

Amazon CloudFront CDN: edge locations, origins, caching behavior, invalidations, signed URLs/cookies, Lambda@Edge, CloudFront Functions, and WAF integration.

Amazon SES: sending and receiving email, domain/DKIM/SPF/DMARC setup, sandbox, reputation, bounces/complaints, configuration sets, and deliverability.

Amazon API Gateway: REST, HTTP, and WebSocket APIs, integration types, authorizers, throttling, caching, stages, deployments, and observability.

AWS Step Functions: state machines, ASL, Standard vs Express, integration patterns, error handling, retries, parallel/map states, and observability.

Amazon EventBridge: event buses, rules, targets, schemas, archives/replay, Pipes, Scheduler, and event-driven architecture patterns.

AWS SAM and CloudFormation: stacks, templates, parameters, intrinsic functions, change sets, drift, nested stacks, StackSets, SAM transforms, and best practices.

AWS Lambda and the serverless ecosystem: triggers, runtimes, layers, cold starts, concurrency, observability, packaging, and patterns.

AWS Identity and Access Management: users, roles, policies, federation, MFA, permissions boundaries, SCPs, and best practices.

Cloud security fundamentals: shared responsibility, identity, network, encryption, secrets, threat modeling, compliance, and incident response.

DevOps and SRE practices: CI/CD, IaC, observability, deployment strategies, SLI/SLO, incident response, automation, and chaos engineering.

Containers and Kubernetes: Docker fundamentals, images, networking, volumes, security, OCI, runtimes, and Kubernetes core concepts.

Core data structures: arrays, linked lists, hash maps, stacks/queues, trees, heaps, graphs, tries, and specialized structures like Bloom filters and union-find.

Algorithms from Big-O and sorting to graph traversals, dynamic programming, divide and conquer, two pointers, sliding windows, and bit manipulation.

Core system design concepts for technical interviews in 2026: scaling, caching, consistency models, load balancing, database design, rate limiting, back-of-the-envelope estimation, and distributed systems primitives.

End-to-end walkthroughs of classic system design interview problems: requirements, capacity estimation, API design, data modelling, architecture, and deep dives on bottlenecks. Covers distributed systems, scalability, and real-world trade-offs as asked in FAANG-style interviews in 2026.

WebAssembly in depth: binary format, .wat text format, JS interop (WebAssembly JS API, memory, imports/exports), compilation from Rust/C/AssemblyScript, WASI, streaming instantiation, threads, the Component Model, and performance characteristics in browser and server runtimes.

Desktop app development with Electron 33+ and Tauri 2.x: process model, IPC, security hardening, packaging, auto-updates, native integrations, and a head-to-head comparison of the two frameworks.

Core C# from the ground up: type system, OOP, generics, LINQ, async/await, pattern matching, records, and modern language features through C# 13 / .NET 9.

Async/await mechanics, Task-based programming, cancellation, thread-safety primitives, parallel patterns, channels, and async streams in modern .NET 9.

ASP.NET Core 9: middleware pipeline, dependency injection, minimal APIs, routing, model binding, filters, Web API, authentication, authorization, background services, SignalR, Blazor, configuration, OpenAPI, error handling, and testing.

EF Core 9 essentials: DbContext, migrations, relationships, loading strategies, LINQ queries, raw SQL, transactions, concurrency, global query filters, value converters, owned entities, and performance patterns.

Clean Architecture, SOLID principles, CQRS with MediatR v12, DDD, Repository & Unit of Work, Vertical Slice, Outbox pattern, domain events, Result pattern, FluentValidation pipeline, AutoMapper vs Mapster, Options pattern, feature flags, health checks, and global exception handling in .NET 9.

Blazor in .NET 9: Blazor United / Auto render modes, component model, lifecycle, data binding, routing, forms, dependency injection, JavaScript interop, authentication, state management, streaming rendering, WASM performance, SignalR, and testing with bUnit.

.NET MAUI (.NET 9): cross-platform mobile and desktop development with a single project, XAML, MVVM, Shell navigation, handlers, dependency injection, platform-specific code, SQLite, HTTP, Blazor hybrid, and performance.

Microsoft Azure cloud platform: compute, storage, networking, identity, messaging, observability, and infrastructure-as-code for modern cloud-native applications.

Large language models from the ground up: transformer architecture, attention, tokenization, prompting, fine-tuning, embeddings, safety, and production cost optimization — covering the 2026 landscape of Claude 4, GPT-4o, Gemini 2.x, Llama 4, and mainstream reasoning models.

RAG pipelines, vector databases, embeddings, LangChain, LlamaIndex, AI agents, function calling, structured output, prompt caching, streaming, context management, hybrid search, re-ranking, evaluation, guardrails, observability, multi-agent systems, and cost optimization.

Agentic AI systems, tool use, LangChain, LangGraph, multi-agent architectures, and autonomous workflows

Prompt design techniques, chain-of-thought, few-shot learning, system prompts, and LLM safety

RAG architecture, document chunking, embedding models, retrieval strategies, and production RAG pipelines

Embeddings, similarity search, ANN algorithms, and vector database systems like Pinecone, Weaviate, Chroma, and pgvector

Core ML from the ground up: learning paradigms, model evaluation, feature engineering, classical algorithms, ensemble methods, neural networks, and practical tooling with scikit-learn, pandas, and NumPy.

End-to-end machine learning operations: the ML lifecycle, model serving, experiment tracking, feature stores, data versioning, monitoring, CI/CD for ML, and LLM-specific ops.

Core Java fundamentals: OOP, generics, collections, streams, memory model, and more

Threads, synchronization, java.util.concurrent, CompletableFuture, reactive programming, and virtual threads

Spring Boot essentials: auto-configuration, dependency injection, REST APIs, security, testing, and actuator

Spring Data JPA, Hibernate ORM, entity mapping, repositories, transactions, and query optimization

Master behavioral interview questions using the STAR framework (Situation, Task, Action, Result). Covers teamwork, conflict, failure, leadership, ambiguity, and more — with concrete engineering examples.

Behavioral interview questions for senior engineers, tech leads, and engineering managers — answered with the STAR framework. Covers mentorship, technical decision-making, cross-functional influence, team dynamics, and organizational leadership.