FAQ
Performance and scaling
13 questions and answers about Performance and scaling, from Muhammad Shahid, Senior AI Software Engineer and Backend Developer.
Performance and scaling
1. Can you fix a slow API?
Yes. I profile the slow queries, then fix them with indexes, aggregation pipelines, caching and pagination. At Dlux Soft this cut average API response time by about 60%.
2. How did you scale CV Maker from 200K to 1M users?
With MongoDB indexing, aggregation pipelines, response caching and pagination on the Node.js backend, while keeping releases stable and free of downtime.
3. How do you fix high MongoDB CPU usage?
Find the slow queries, add the right compound indexes, rebuild the access patterns, and cache read-heavy endpoints in Redis. That is how I brought DOP’s database load back into a safe range.
4. What did you build for DOP?
DOP (Data Ownership Protocol, dop.org) is a privacy-focused blockchain protocol that lets users choose what on-chain data they reveal, using zero-knowledge selective disclosure. I engineered its backend services: the APIs, the data layer and the blockchain connectivity.
5. What usually causes API timeouts at scale?
In my experience, read-heavy queries without the right indexes and no caching layer. At DOP fixing exactly that eliminated the timeouts and stabilised response times under peak load.
6. Can you scale a backend without rewriting it?
Usually, yes. Slow queries, timeouts, 100% CPU and random logouts can almost always be fixed in place, and that is how I have handled them on live products.
7. How do you keep blockchain transactions working when an RPC node fails?
At DOP I integrated 5 RPC providers behind randomised selection with automatic failover, so a dead node never reaches the user. Transaction downtime from individual node failures dropped to zero.
8. Can you fix CPU and memory bottlenecks?
Yes. Query and aggregation tuning, CPU and memory bottlenecks, and session bugs are the problems I fix most often on live products.
9. Do you do zero-downtime releases?
Yes. While scaling the CV Maker backend from 200K to 1M+ users, every release stayed stable and free of downtime.
10. Can you rescue a product that keeps breaking in production?
Yes. I have fixed slow queries, timeouts, 100% CPU and random logouts on live products with millions of users, then added monitoring so the problems do not return quietly.
11. Can you scale Node.js and MongoDB systems to millions of users?
Yes. I have done it in production: DOP grew past 300M users, TheCryptoBasic serves 2M+ readers, and I scaled CV Maker from 200K to 1M+ users, all on Node.js and MongoDB backends.
12. How do you design high-performance REST APIs?
Indexed queries, Redis caching for read-heavy routes, pagination, lean responses, request validation, and slow work moved to background jobs. At Dlux Soft this cut average API response time by about 60%.
13. Do you do system design?
Yes. I design the services, data model, caching, queues and failover for a system and plan how it will scale. At DOP that meant Redis caching, new indexes and multi-provider RPC failover for 300M+ users.