Unlock PHP Magic: How to Take Input from User in PHP Easily
9 Aug 2025
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Performance & Scalability
Describe how a Message Queue (e.g., Kafka, RabbitMQ) and Rate Limiting can be used together to protect a vulnerable back-end service from being overwhelmed by spikes of inbound requests.
Explain the function of an API Gateway in a microservices environment. List 3 critical services (e.g., authentication, rate limiting, request routing) that the gateway should handle before traffic reaches the back-end services.
Develop a policy for monitoring and acting on application error logs. The policy must specify the minimum acceptable Error Rate (e.g., <0.1%) and the mandatory escalation path when the rate spikes above this threshold.
Explain the function and primary performance benefit of using Database Connection Pooling in a high-traffic application. Describe how connection pooling reduces the overhead associated with frequent database requests.
For a field service application (used often without reliable network), outline 3 techniques for ensuring Offline Capability. Techniques must cover data storage (e.g., local database), synchronization, and handling of conflicts upon reconnection.
Outline the mandatory best practice for storing and displaying time-sensitive data (e.g., order history) in a global application. Specify the single Time Format (e.g., UTC) that must be used for storage in the database and the required conversion for display to the user.
Describe how a Message Queue can be used to decouple a monolithic application into microservices. Provide an example of a long-running, non-critical task (e.g., report generation) that benefits from this decoupling.
Explain the concept of a Database Deadlock in a high-concurrency application. List two techniques that the application or database must implement to detect and resolve deadlocks gracefully (e.g., timeouts, locking order).
Describe the use of Asynchronous Tasks (background processing) to improve the responsiveness of a web application. List 3 specific operations (e.g., sending emails, large file exports) that are ideal candidates for asynchronous handling.
Define Idempotency in API design. Provide a specific example of an API request (e.g., a DELETE or PUT request) that should be idempotent and explain why non-idempotency leads to data corruption during retries.
For a serverless function (e.g., AWS Lambda), identify the two primary factors that determine the cost (e.g., execution time, memory allocated). Propose one method for optimizing the application code to reduce the execution time and cost.
Given a slow SQL query: SELECT * FROM users WHERE status = 'active' AND last_login < '2024-01-01', propose two distinct methods for optimization: 1. Indexing Strategy and 2. Query Refinement, explaining how each reduces load time.
Outline the difference between RTO (Recovery Time Objective) and RPO (Recovery Point Objective). For a critical financial application, propose an acceptable RTO and RPO and explain the architectural necessity for achieving them (e.g., multi-region deployment).
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