PHP Developer DBMS Concepts Interview Guide

At Read Committed, each statement receives a new snapshot, so later statements can see commits made in between. Higher isolation changes the guarantees and may require retrying serialization failures. Choose isolation from the business invariant, not from an assumption that every transaction freezes all reads.

Check your understanding: Interleave two sessions and document the snapshots each statement sees.

Common trap: Treating transaction atomicity and isolation as identical.

Concept reference: PostgreSQL: transaction isolation

An index is an option, not a command. The planner considers selectivity, statistics, table size and access cost. Read estimated and actual rows, filters and scan types before changing indexes. EXPLAIN ANALYZE executes the statement, so use safe data and transaction handling for writes.

Check your understanding: Compare estimated and actual row counts on representative data.

Common trap: Forcing an index without measuring the full query.

Concept reference: PostgreSQL: reading EXPLAIN plans

Check the grain of each table and whether the join creates several rows for one order. Aggregate at the intended business grain before joining, or use the correct relationship and key. Reconcile totals using a tiny fixture containing multiple child rows and an unmatched parent.

Check your understanding: Use one order with two child records and verify the total remains correct.

Common trap: Using DISTINCT as a universal repair for a wrong join.

Concept reference: PostgreSQL: reading EXPLAIN plans

Binding values keeps them separate from SQL structure and avoids relying on hand-built quoting rules. Use the database driver’s supported parameter API, validate input constraints and allowlist dynamic identifiers separately. A prepared value placeholder cannot safely stand for an arbitrary table name or SQL clause.

Check your understanding: Test quoted input and an unsupported dynamic sort column.

Common trap: Using parameter binding for values but concatenating untrusted identifiers.

Concept reference: PHP: preventing SQL injection

Prevent the injection first, then reduce the application account’s database permissions to necessary operations. Avoid exposing database error details and separate operational credentials from the web request path. Layered controls reduce impact but do not make unsafe query construction acceptable.

Check your understanding: Verify the application account cannot perform an unnecessary administrative operation.

Common trap: Relying on restricted permissions instead of fixing unsafe SQL.

Concept reference: PHP: preventing SQL injection

Return a consistent documented error contract and a status appropriate to the failure class. Do not report success with an embedded failure flag that callers may miss. Keep internal stack traces and credentials out of responses, and define retry behavior separately from user-correctable validation errors.

Check your understanding: Test invalid input, forbidden access and a failed downstream connection.

Common trap: One generic successful response for every outcome.

Concept reference: IETF RFC 9110: HTTP semantics

First, identify technical constraints and define measurable service objectives. Next, follow a request across validation, business logic, storage and asynchronous work. Contrast architectural trade-offs across write cost, read latency, consistency and operational complexity, explicitly mitigate the risk of the same job is processed twice and produces conflicting side effects, and confirm system stability using lease-expiry tests, idempotency records and a restart recovery drill.

Common trap: Reaching for a specific library or framework before defining constraints, failure envelopes, and automated verification criteria.

Prioritise the failure mode exhibiting the highest user blast radius and lowest observability. Formulate an explicit containment boundary, implement idempotent retries with jitter, and establish an automated rollback threshold. Verify resilience through a server-authoritative timestamp trace and boundary property tests.

Common trap: Relying on passive monitoring dashboards without defining explicit error-budget alerts, rollback triggers, and verified recovery procedures.

Structure the response using Context-Decision-Tradeoff-Result: articulate the business and technical constraints, compare viable alternatives, explain the implementation (follow a request across validation, business logic, storage and asynchronous work), and document the accepted trade-off. Provide concrete proof: an explain plan, concurrency test and recovery verification.

Common trap: Speaking only in high-level abstractions or team accomplishments without detailing your direct implementation decisions, trade-offs, and measured results.

Formulate a falsifiable hypothesis from observable telemetry before altering configurations. Then correlate the request trace with transaction state, queue ownership and dependency budgets. Isolate the defect to the smallest reproducible boundary, validate root cause with evidence, and confirm full resolution using a compatibility contract, expand-and-contract rollout and rollback rehearsal.

Common trap: Applying speculative fixes or restarting services blindly without establishing an observable signal connected to a falsifiable hypothesis.

Produce an idempotency test, failure trace and repeatable recovery runbook. Document baseline assumptions, technical mechanism (follow a request across validation, business logic, storage and asynchronous work), rejected alternatives, bounded failure envelopes, and deterministic pass criteria. Supply reproducible verification via a heap profile, bounded reproduction and post-fix soak-test result.

Common trap: Presenting architecture diagrams or slides lacking automated unit/integration tests, observable metrics, or automated rollback configurations.