How would you optimize queries or the server when a social media platform goes down?

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When a social media platform's server goes down, it usually happens because of high traffic load, slow queries, unoptimized backend logic, or insufficient infrastructure resources. To bring the platform back up and ensure stability, you must optimize both database queries and the server architecture.

1. Identify the Root Cause

Before optimizing, quickly check:

• High CPU or memory usage
• Slow or long-running SQL queries
• Too many open connections
• Disk I/O bottleneck
• Sudden traffic spike or DDOS-like load
• Cache not working
• Unoptimized APIs

Use tools: top, htop, pm2 status, MySQL slow_query_log, Laravel Telescope, NewRelic, Grafana dashboards, etc.

2. Query Optimization Techniques

a) Enable Slow Query Log

Identify which queries are killing performance.

SET GLOBAL slow_query_log = 'ON';

b) Add Proper Indexes

90% of slow queries come from missing indexes.

Example:

CREATE INDEX idx_user_id ON posts(user_id);

**c) Avoid SELECT ***

Use only required columns:

SELECT id, name, email FROM users WHERE status = 1;

d) Use Joins Properly

Avoid nested queries or unnecessary joins.

e) Use Pagination for Large Data

Don’t return 10,000 records in one API.

f) Use Database Caching

Redis / Memcached to store:

• Frequently accessed queries
• User profile data
• Trending posts

g) Precompute Heavy Queries

For trending posts, analytics, or counts – store the result in cache and update every few seconds.

3. Server-Side Optimization

a) Add Load Balancing

Use Nginx Load Balancer or AWS ALB to share traffic across servers.

b) Use Horizontal Scaling

Increase the number of web and API servers automatically.

c) Implement Queue System

Move heavy tasks like:

• Sending notifications
• Resizing images
• Sending emails

to queues (RabbitMQ, SQS, Redis Queue).

d) Use CDN for Images & Videos

Offload media delivery from your main server.

e) Optimize API Response

• Use pagination
• Avoid heavy loops
• Return small JSON
• Pre-calc counts (likes/comments)

f) Enable HTTP Caching

Use browser caching + server caching headers.

4. Architecture Improvements

a) Microservices Approach

Separate modules:

• Auth service
• Post service
• Notification service
• Media service

This prevents one module from crashing the whole system.

b) Database Replication

Use READ replicas for high read queries:

• Master → Write
• Slaves → Read

c) Distributed Cache

Use clustering in Redis/Memcached.

d) Sharding & Partitioning

For HUGE tables like posts, likes, comments.

5. Immediate Steps When Server is Down

1. Enable Maintenance Mode Stop more users from hitting the server.

2. Restart services

   • Nginx/Apache
   • PHP-FPM
   • MySQL / MariaDB

3. Kill slow MySQL queries

SHOW FULL PROCESSLIST;
KILL query_id;

4. Flush Cache (if corrupted)

5. Check Disk & Memory

6. Scale server temporarily

6. Final Expected Interview Summary Answer

Below is the short, interview-perfect answer:

If a social media platform server goes down due to heavy load, I will first identify bottlenecks using monitoring tools. Then I will optimize slow SQL queries using indexes, caching, and pagination. On the server side, I will use load balancing, horizontal scaling, CDNs, and queue systems to handle heavy tasks. I will also implement microservices, database replication, Redis caching, and API optimization to stabilize the platform and prevent future downtime.