Senior
Who was responsible for the verification services (anti-fraud, image checking, text, spam, limits)?
sobes.tech AI
Answer from AI
The question concerns experience with verification services such as anti-fraud, image, text, spam, and limit checks.
These services are usually implemented as separate microservices or modules that process incoming data and make decisions based on rules, machine learning models, or heuristics. For example:
- Anti-fraud — analyzes transactions and user behavior to detect fraud.
- Image verification — may include content recognition, filtering unwanted content.
- Text and spam verification — filters messages, comments for spam, insults, or prohibited content.
- Limits — controls request or operation frequency to prevent abuse.
If you have worked with such services, you likely have experience with:
- Building and integrating APIs for interaction with other systems.
- Developing verification and filtering algorithms.
- Optimizing performance and scalability.
- Ensuring reliability and monitoring of services.
An example in Go for simple request limit checking:
package main
import (
"fmt"
"sync"
"time"
)
// Simple structure for request limit
type RateLimiter struct {
mu sync.Mutex
requests int
max int
resetTime time.Time
}
func NewRateLimiter(max int, interval time.Duration) *RateLimiter {
return &RateLimiter{max: max, resetTime: time.Now().Add(interval)}
}
func (r *RateLimiter) Allow() bool {
r.mu.Lock()
defer r.mu.Unlock()
now := time.Now()
if now.After(r.resetTime) {
r.requests = 0
r.resetTime = now.Add(time.Minute)
}
if r.requests < r.max {
r.requests++
return true
}
return false
}
func main() {
limiter := NewRateLimiter(5, time.Minute)
for i := 0; i < 10; i++ {
if limiter.Allow() {
fmt.Println("Request allowed")
} else {
fmt.Println("Request limit exceeded")
}
}
}
This approach can be expanded and integrated into more complex verification services.