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⚙️Backend Dev

Backend engineering, APIs, and databases

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Test yourself: Top 30 Backend Dev interview questionsMultiple choice, with the correct answer and why it is correct on every question. Free, no sign-in.

Interview questions in Backend Dev, page 26

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Go if err != nil versus Rust's ? operator

Go's explicit checks are verbose but make every error site visible; Rust's ? propagates concisely while still forcing the error into the type, reducing boilerplate.

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Pydantic computed fields in response models

A @computed_field decorated property is excluded from input and validation but included in serialization and the OpenAPI schema, ideal for values like full_name derived from other fields.

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Validating request bodies with Express middleware

Run validation middleware before the handler, check email format and password length, return 400 with errors on failure, call next on success.

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Optimizing queries on a billion-row fact table

Partition to prune scans, index for selective lookups, materialize views to precompute aggregates; each adds write or maintenance cost.

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anyhow versus thiserror in Rust error handling

Anyhow gives one opaque dynamic error type for applications where you mostly propagate and report; thiserror derives concrete typed enums for libraries so callers can match on variants.

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Streaming large file downloads efficiently

Use StreamingResponse with a generator that yields chunks (or FileResponse for an on-disk file), set media_type and a Content-Disposition header, so memory stays flat regardless of file size.

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Purpose of an ORM like Sequelize

Maps rows to objects, gives a model-based API, handles associations, migrations, and parameterized queries across dialects.

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Diagnosing and optimizing a slow production query

Read the EXPLAIN ANALYZE plan, find the costly node, then fix via indexing, rewrite, or stats.

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Implicit Go interfaces versus explicit Rust trait impls

Go's implicit satisfaction enables decoupling and retrofitting but hides who implements what and risks accidental conformance; Rust's explicit impls aid discovery, refactoring…

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Feature-based vs layer-based project structure

Layer-based groups by technical role and is simple early but scatters a feature across folders; feature-based groups by domain, improving cohesion and ownership at the cost of some duplication and…

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Pinpointing validation errors in nested request data

Use schema validation that reports a path, collect all errors not just the first, return a 400 with field paths and messages.

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Designing an HA/DR strategy for an OLTP database

Sync standby in-region for zero data loss, async cross-region for DR, automated failover with a quorum.

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Go scheduler work-stealing and blocking syscalls

The GMP model runs goroutines (G) on OS threads (M) attached to logical processors (P); idle P's steal half of another P's run queue; on a blocking syscall the M detaches with its G.

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selectinload vs joinedload for eager loading

Use eager loading options to avoid lazy N+1; joinedload uses a single JOIN (good for many-to-one) but can fan out rows on collections; selectinload issues a second IN query (better for one-to-many).

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Managing user presence with reconnection grace periods

Rely on heartbeats, apply a grace period before marking offline, reconcile reconnects by user not socket id, use a shared store for multi-instance.

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Cutting managed database costs without breaking SLOs

Pool connections, prune and tune indexes, offload reads, tier or partition cold data, right-size storage IOPS.

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Cancellation and cleanup: Go context/errgroup vs Tokio

Go propagates cancellation via context.Context that goroutines must poll, with errgroup canceling siblings on first error; Tokio cancels by dropping futures, which stops them at await…

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OAuth2 social login with your own JWT

A login endpoint redirects to the provider with a state param, a callback exchanges the code for the provider token, you fetch the user profile, upsert the local user, then mint your own JWT.

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Blocking versus non-blocking I/O in Node

Blocking calls halt the thread until done, non-blocking returns immediately and notifies via callback or promise, fs.readFileSync versus fs.readFile.

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Why choose Kafka over a REST endpoint for ingestion

Kafka buffers spikes, decouples producers from consumers, replays and fans out durably.

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