System Design Interview: Key Components and Best Practices

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System design interviews are crucial for assessing a candidate’s ability to architect scalable and efficient systems. Below are the core components often discussed in such interviews, along with practical commands and tools to implement them.

1. Load Balancer

Distributes traffic across multiple servers to ensure high availability.

You Should Know:

  • Nginx Load Balancing (Round Robin):
    http {
upstream backend {
server backend1.example.com;
server backend2.example.com;
}
server {
location / {
proxy_pass http://backend;
}
}
}
  • AWS Elastic Load Balancer (ELB) CLI Command:
    aws elb create-load-balancer --load-balancer-name my-load-balancer --listeners "Protocol=HTTP,LoadBalancerPort=80,InstanceProtocol=HTTP,InstancePort=80" --subnets subnet-123456

2. API Gateway

Manages API requests, authentication, and routing.

You Should Know:

  • Kong API Gateway Setup:
    docker run -d --name kong --network=kong-net -e "KONG_DATABASE=postgres" -e "KONG_PG_HOST=kong-database" -p 8000:8000 kong:latest
  • AWS API Gateway via CLI:
    aws apigateway create-rest-api --name 'MyAPI' --description 'Sample API Gateway'

3. Static Content & CDN

Improves load times using cached static assets.

You Should Know:

  • Cloudflare CDN Setup:
    curl -X POST "https://api.cloudflare.com/client/v4/zones/YOUR_ZONE_ID/purge_cache" -H "Authorization: Bearer YOUR_API_KEY" --data '{"purge_everything":true}'
  • AWS S3 + CloudFront:
    aws cloudfront create-distribution --origin-domain-name my-bucket.s3.amazonaws.com --default-root-object index.html

4. Distributed File Storage (HDFS, S3)

Stores data across multiple nodes for redundancy.

You Should Know:

  • HDFS Basic Commands:
    hdfs dfs -mkdir /data 
hdfs dfs -put localfile /data 
hdfs dfs -ls /data
  • AWS S3 CLI:
    aws s3 cp file.txt s3://my-bucket/ 
aws s3 sync localdir s3://my-bucket/

5. Caching (Redis/Memcached)

Speeds up repeated data access.

You Should Know:

  • Redis CLI:
    redis-cli 
SET key "value" 
GET key
  • Memcached Setup:
    memcached -d -m 1024 -p 11211 -u nobody

6. Distributed Logging (ELK Stack, Fluentd)

Centralizes logs for debugging.

You Should Know:

  • Elasticsearch + Kibana Setup:
    docker run -d --name elasticsearch -p 9200:9200 -p 9300:9300 elasticsearch:7.9.3 
docker run -d --name kibana --link elasticsearch:elasticsearch -p 5601:5601 kibana:7.9.3

7. Data Processing (Hadoop/Spark)

Handles large-scale data processing.

You Should Know:

  • Spark Submit Job:
    spark-submit --class com.example.MainApp --master yarn --deploy-mode cluster app.jar
  • Hadoop MapReduce Example:
    hadoop jar hadoop-mapreduce-examples.jar wordcount input output

What Undercode Say

System design interviews test real-world scalability knowledge. Mastering these components—load balancing, caching, distributed storage, and logging—ensures robust architecture. Practical implementation using Nginx, Redis, AWS, and Hadoop strengthens hands-on expertise.

Expected Output:

A well-structured system design with optimized performance, fault tolerance, and scalability.

Prediction:

Future system designs will increasingly integrate AI-driven auto-scaling and serverless architectures for cost efficiency.

Reference:

System Design Interview Guide

References:

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