Alex Chen

How to run production systems reliably, as Google's SRE books and common industry practice describe it: reliability targets and error budgets, alerting, incident response, postmortems, capacity, resilience patterns and chaos testing.

How containers are built and run with Docker, and how Kubernetes schedules, connects and heals them. Written for engineers who deploy and debug containerised apps.

How data engineers build and run the pipelines that move and shape data for analytics. Covers dimensional modelling, warehouses and lakes, batch and streaming pipelines, Spark, Kafka, Airflow, dbt and analytical SQL.

What security engineers work on outside application code: security principles, threat modelling, cryptography, identity and network controls. It also covers finding vulnerabilities, detecting attacks, responding to incidents, and how malware and social engineering work.

How teams build, test, release and run software with automation: CI pipelines, deployment strategies, Terraform and Ansible, artifact versioning, pipeline secrets and GitOps.

The common vulnerability classes in web applications and APIs, such as injection, XSS, CSRF, broken access control and SSRF, how each one works, and how to prevent it in code and in your build pipeline.

The Linux that cloud, DevOps and security engineers use every day on a modern systemd and bash system: files and permissions, processes and services, shell scripts, text tools, disks and finding performance problems.

The core ideas a cloud engineer works with every day: service models and regions, identity and access, virtual networks, compute, storage, managed databases, disaster recovery and cost. Examples use real AWS, Azure and Google Cloud service names.

How networks actually work, from the wire to the TLS handshake: the OSI and TCP/IP models, IP addressing and subnetting arithmetic, DNS records and resolution, TCP and UDP behaviour, the HTTP versions, and certificates. Vendor-neutral and precise.

Vendor-neutral fundamentals of working with large language models: tokens and sampling, prompting patterns, embeddings and vector search, retrieval-augmented generation, and the failure modes that bite in production.

Everything that goes into building a correct, fast, safe backend service: HTTP and REST, auth, SQL, indexing, transactions, and the caching/queueing patterns that keep it standing up. Language- and vendor-agnostic.

The frontend half of the engineering set: HTML semantics and accessibility, CSS layout and the cascade, JavaScript core semantics, the event loop, and React. Useful both for interviews and for day-to-day work.

The language-agnostic foundation deck for engineers: SOLID, design heuristics, naming, functions, code smells and refactoring moves — the vocabulary that code review assumes you already have.

The building blocks of system design interviews and real distributed systems: scaling, load balancing, caching, data partitioning, consistency models and event-driven architecture. Every concept is presented as a trade-off, because that is how it is actually assessed.

Data structures, algorithms, system design, and behavioral prep.