How would you architect a scalable, maintainable LAMP app?

Long Answer

A production-grade LAMP stack architecture balances application structure, database design, and web server tuning. The goal is to scale traffic and teams while keeping the codebase simple to change and the system predictable under load.

1) PHP code organization and boundaries

Organize by domain, not frameworks or controllers. Use layers: Controllers (transport), Application Services (use cases), Domain (entities, policies, value objects), and Infrastructure (repositories, gateways). Keep controllers thin: validate, authorize, call a service, return a response. Repositories encapsulate queries; services perform orchestration and emit domain events for side effects. Use dependency injection, interfaces, and small, testable classes. Version shared contracts and keep backward compatibility during refactors.

2) MySQL schema and access patterns

Model data from read and write shapes, not just entity names. Use third normal form where it helps integrity; denormalize selectively for hot reads. Add composite indexes that match filter → range → sort, and prefer keyset pagination over offsets for large result sets. Constrain types, defaults, and nullability; use foreign keys with cascading rules where appropriate. Partition large append-only tables by time or tenant. Separate operational tables from analytical ones; run heavy reports from replicas or a warehouse, not the primary.

3) Query performance and transactions

Profile the top queries by total time and frequency. Replace SELECT * with explicit projections, avoid non-sargable predicates, and keep transactions short. Use optimistic concurrency or version columns where contention exists. Cache expensive read models in Redis with tags or precise keys that include tenant, locale, or version. Maintain counters and summaries via triggers or application events to avoid repeated aggregates on hot paths.

4) Apache configuration and delivery

Run Apache with a process manager that suits PHP execution (for example, prefork with PHP module or proxy to PHP-FPM via FastCGI). Keep static assets offloaded to a content delivery layer and enable gzip or Brotli, HTTP/2, persistent connections, and sensible timeouts. Use mod_expires or equivalent for cache headers, and configure connection limits, keep-alive, and request timeouts to protect the backend. Enable graceful restarts so deployments do not drop traffic. Put a reverse proxy or load balancer in front for horizontal scaling.

5) Caching and state

Adopt layered caching: HTTP caching for static pages or fragments, application caching for computed views, and database caching for repeated queries. Keys must be deterministic and scoped. Invalidate caches event-driven where possible; do not rely solely on long time-to-live values. Keep PHP workers stateless so scaling out does not require sticky sessions; store sessions in Redis or a database if necessary.

6) Asynchrony and background jobs

Move non-interactive workloads to queues: email, media processing, webhooks, bulk imports, and report generation. Make jobs idempotent with natural keys; use retries with jitter and a dead-letter route. Partition queues by priority to prevent low-value tasks from starving critical ones. For long-running processes, checkpoint progress so graceful shutdowns are safe.

7) Security and multi-tenancy

Authenticate at the edge; authorize in services with policies. Include tenant identifiers in tokens and indexes to isolate data. Sanitize inputs, parameterize queries, and enable output encoding. Encrypt sensitive fields at rest and in transit. Apply content security policy and strict cookie options; audit file uploads and cron tasks.

8) Observability and operations

Emit structured logs with correlation identifiers across web and workers. Track RED metrics (rate, errors, duration), slow query logs, error budgets, cache hit ratios, and queue depth. Use health endpoints for liveness and readiness; only take a node out of rotation once in-flight requests drain. Run canary or blue-green deployments with smoke tests and automatic rollback on failure.

9) Delivery, testing, and governance

Automate build and deployment: run static analysis, unit tests, integration tests against ephemeral MySQL, and performance smoke. Keep schema migrations backward-compatible: expand, backfill, switch reads, and contract. Maintain coding standards, API versioning rules, and migration playbooks. Document error envelopes, pagination, and retry semantics to keep clients stable.

10) Scaling strategy

Scale reads with caches and replicas, writes with careful sharding or partitioning where justified. Add idempotent endpoints for retries, circuit breakers around dependencies, and rate limits at the edge. Measure before optimizing; treat p95 and p99 as first-class success criteria. With these practices, LAMP stack architecture remains fast, maintainable, and ready for growth.

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Table

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Common Mistakes

• Controllers stuffed with business logic and database access, making tests hard and changes risky.
  
• Schemas with nullable everything, no constraints, and missing composite indexes.
  
• Offset pagination on large tables that degrades with size; no keyset strategy.
  
• Overusing denormalization without a rebuild path, causing drift and data anomalies.
  
• Apache defaults left untouched: poor keep-alive, missing compression, and no graceful deploys.
  
• Sticky in-process sessions that block horizontal scaling.
  
• Caching with vague keys and no invalidation plan, leading to stale or leaked data.
  
• One global queue where bulk exports starve critical notifications.
  
• No slow query logging, no p95 metrics, and no rollback on failed deployments.
  
  

Sample Answers (Junior / Mid / Senior)

Junior:
“I would keep controllers simple, move logic to services, and use repositories for queries. I would add composite indexes in MySQL, avoid SELECT *, and enable compression and HTTP/2 in Apache. I would cache hot reads and run emails as background jobs.”

Mid:
“My LAMP stack architecture separates PHP into controllers, services, and repositories with dependency injection. MySQL uses strict schemas, composite indexes, and keyset pagination. Apache serves compressed assets with keep-alive and graceful restarts. Redis caches read models; queues handle slow work with retries and dead-letter. Health checks and blue-green deployments protect releases.”

Senior:
“I align domains to modules, expose stable contracts, and enforce policies in services. MySQL is modeled from access paths, with partitioning where needed and replicas for analytics. Apache terminates TLS, enables HTTP/2, and proxies to stateless PHP workers. Layered caches and event-driven invalidation keep hot paths fast. Jobs are idempotent and prioritized. Observability covers RED metrics, slow queries, and queue lag with automated rollback.”

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Evaluation Criteria

A strong answer presents a LAMP stack architecture with: domain-first PHP layering; repositories and DI; MySQL schema with strict types, composite indexes, and keyset pagination; tuned Apache (compression, HTTP/2, caching, graceful restarts); layered caching and event-driven invalidation; queues with idempotency and priorities; and robust observability plus safe deployments. It should mention backward-compatible migrations and blue-green or canary releases. Red flags include fat controllers, offset pagination, schema anarchy, sticky sessions, default Apache settings, global queues, and missing telemetry.

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Preparation Tips

• Refactor one feature to controllers → services → repositories; add unit tests.
  
• Enable slow query log; fix the top queries with indexes and projections.
  
• Convert one endpoint from offset to keyset pagination.
  
• Tune Apache: compression, keep-alive, HTTP/2, cache headers, and graceful restarts.
  
• Add Redis caching with deterministic, tenant-scoped keys and event-based invalidation.
  
• Create a small job queue: implement idempotent retries and a dead-letter path.
  
• Introduce health probes, correlation identifiers, and RED metrics dashboards
  
• Practice zero-downtime migrations: expand, backfill, switch reads, contract.
  
• Script a blue-green workflow with smoke tests and automatic rollback triggers.
  
  

Real-world Context

A content platform restructured PHP into services and repositories, cutting controller size dramatically. MySQL got strict types and composite indexes; keyset pagination fixed slow scrolling pages. Apache enabled HTTP/2, compression, and graceful restarts, flattening deploy-time error spikes. Redis cached denormalized article summaries with event-driven invalidation; p95 read latency dropped. A queue handled image processing and webhooks with idempotent jobs and priorities, so exports no longer blocked notifications. With slow query logs, RED metrics, and blue-green releases, incidents were resolved faster and rollbacks were automatic when smoke tests failed. The LAMP stack architecture scaled predictably through seasonal peaks.

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Key Takeaways

• Structure PHP by domain with thin controllers, services, and repositories.
  
• Design MySQL from access paths: strict schemas, composite indexes, keyset pagination.
  
• Tune Apache for concurrency, compression, HTTP/2, and graceful deploys.
  
• Use layered caching and event-driven invalidation to keep hot paths fast.
  
• Offload heavy work to idempotent queued jobs with priorities.
  
• Instrument RED metrics, slow queries, and queue lag; deploy via blue-green.
  
  

Practice Exercise

Scenario:
You are building a multi-tenant reporting portal on the LAMP stack. Traffic is spiky during business hours, lists contain millions of rows, and exports should not impact interactive users.

Tasks:

1. Define a domain-first PHP structure: controllers → services → repositories. List the interfaces you will bind and the policies to enforce per tenant.
   
2. Design MySQL schemas for reports, report_rows, and subscriptions with strict types, foreign keys, and composite indexes. Show keyset pagination for listing rows by created_at, id.
   
3. Identify the top three queries and outline expected indexes. Describe a migration plan to add them without downtime.
   
4. Configure Apache with compression, HTTP/2, cache headers, connection limits, and graceful restarts behind a load balancer.
   
5. Implement Redis caching for report summaries with tenant-scoped keys and event-based invalidation when source data changes.
   
6. Create queues for exports and notifications. Make export jobs idempotent, checkpoint progress, and put them on a low-priority queue so notifications remain fast.
   
7. Add health probes and dashboards: RED metrics per endpoint, slow query log ingestion, cache hit ratio, and queue depth.
   
8. Ship via blue-green: run schema expand, deploy, backfill via jobs, run smoke tests, then switch traffic; roll back automatically on errors.
   
   

Deliverable:
A concise architecture and runbook demonstrating a scalable, maintainable LAMP stack architecture with balanced PHP code, MySQL design, and Apache configuration.