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Application Performance Optimization Flashcards
| Front | Back |
| Auto-Scaling Groups | Automatically adjusts the number of servers based on traffic or load requirements |
| Caching | Improves application performance by storing frequently accessed data closer to the user |
| CloudWatch | AWS monitoring tool for tracking application performance and resources |
| Compression | Reduces file sizes to speed up data transfer between server and client |
| Connection Pooling | Reduces database connection overhead by reusing existing connections |
| Content Delivery Network (CDN) | Accelerates content delivery by caching assets on edge locations globally |
| Database Indexing | Speeds up database queries by organizing data for quick retrieval |
| Distributed Tracing | Tracks the flow of requests across multiple services in a distributed system |
| Horizontal Scaling | Increases performance by adding more machines to handle increased traffic |
| Lazy Loading | Optimizes performance by loading resources only when they are required |
| Load Balancing | Distributes network or application traffic across multiple servers to prevent overload |
| Memory Leak Detection | Identifies processes or code that cause excessive memory consumption |
| Query Optimization | Improves database performance by rewriting queries for efficiency |
| Rate Limiting | Controls the number of requests users can make to prevent abuse or traffic bursts |
| Server-Side Rendering (SSR) | Improves load times by rendering web pages on the server instead of the client |
| Simulated Load Testing | Tests application scalability by simulating high traffic or user activity |
| Software Profiling | Monitors application performance to identify bottlenecks or inefficient code |
| Throttling | Limits the rate at which application processes requests to prevent server overload |
| Vertical Scaling | Enhances performance by boosting the capacity of existing machines |
| X-Ray | AWS tracing tool for analyzing and debugging application requests and paths |
Front
Memory Leak Detection
Click the card to flip
Back
Identifies processes or code that cause excessive memory consumption
Front
Query Optimization
Back
Improves database performance by rewriting queries for efficiency
Front
CloudWatch
Back
AWS monitoring tool for tracking application performance and resources
Front
X-Ray
Back
AWS tracing tool for analyzing and debugging application requests and paths
Front
Caching
Back
Improves application performance by storing frequently accessed data closer to the user
Front
Connection Pooling
Back
Reduces database connection overhead by reusing existing connections
Front
Horizontal Scaling
Back
Increases performance by adding more machines to handle increased traffic
Front
Auto-Scaling Groups
Back
Automatically adjusts the number of servers based on traffic or load requirements
Front
Rate Limiting
Back
Controls the number of requests users can make to prevent abuse or traffic bursts
Front
Distributed Tracing
Back
Tracks the flow of requests across multiple services in a distributed system
Front
Software Profiling
Back
Monitors application performance to identify bottlenecks or inefficient code
Front
Lazy Loading
Back
Optimizes performance by loading resources only when they are required
Front
Throttling
Back
Limits the rate at which application processes requests to prevent server overload
Front
Server-Side Rendering (SSR)
Back
Improves load times by rendering web pages on the server instead of the client
Front
Compression
Back
Reduces file sizes to speed up data transfer between server and client
Front
Content Delivery Network (CDN)
Back
Accelerates content delivery by caching assets on edge locations globally
Front
Simulated Load Testing
Back
Tests application scalability by simulating high traffic or user activity
Front
Load Balancing
Back
Distributes network or application traffic across multiple servers to prevent overload
Front
Database Indexing
Back
Speeds up database queries by organizing data for quick retrieval
Front
Vertical Scaling
Back
Enhances performance by boosting the capacity of existing machines
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This deck addresses strategies for improving application performance, such as caching mechanisms, load balancing, auto-scaling groups, and monitoring tools like CloudWatch and X-Ray.