Core Fundamentals

When traffic grows, you have two moves. Vertical scaling means making one machine bigger, more CPU, more memory. It is the easy answer and it works until it does not, because there is a ceiling and a single machine is a single point of failure. Horizontal scaling means adding more machines and spreading the work across them. It has no real ceiling, but it forces you to answer a hard question: when a user's second request lands on a different server than their first, does anything break?

That question is why stateless versus stateful is on this list right next to scaling. A stateless service keeps no memory of past requests between calls, so any server can handle any request and you can add or remove servers freely. A stateful service remembers things locally, which means a specific user is tied to a specific server, and now horizontal scaling becomes a fight. Session management is the practical version of this problem. Where do you keep a logged-in user's session so that any server in the pool can serve them?

Scalability, elasticity, and load balancing complete the picture. Scalability is whether your system can grow at all. Elasticity is whether it can grow and shrink automatically as demand changes, which is what cloud autoscaling sells you. Load balancing is the traffic cop that spreads incoming requests across your pool so no single server gets buried. Caching sits alongside all of it as the cheapest performance win there is: store the answer once, serve it many times, and take the load off everything downstream.

A system is only as reliable as the agreements between its parts. REST API is the dominant style for those agreements over HTTP, a set of conventions for how services expose resources and how clients talk to them. The value of a convention is predictability. Anyone who knows REST can pick up your API and guess how it works, which is why it became the default.

But a convention is not enough on its own. JSON Schema and XML Schema let you write down exactly what a valid message looks like, so both sides agree on shape and types before anything goes wrong. API documentation through Swagger and OpenAPI turns that contract into something humans and tools can read, generate clients from, and test against. Semantic versioning is how you evolve the contract without breaking everyone who depends on it: a clear rule for which changes are safe, which add features, and which break compatibility.

The boundary is also where security lives. Input validation means never trusting what comes in from outside, checking every field before it touches your logic, because attackers send malformed and malicious data on purpose. Output encoding means safely formatting what you send back so that data can never be misread as code, which is the core defense against injection attacks. Validate on the way in, encode on the way out. These two habits prevent an entire family of breaches and belong in your reflexes from day one.