Interviewer:
You have a service that sends emails.
Works fine at 1,000 emails/day.
At 500,000 emails/day
some users get emails 6 hours late.
Some never get them.
No errors in the logs.
Email service API returns 200.
Where's the bottleneck
and how do you fix it?
@dark_coderz Great points, also consider checking the email service's connection pooling and timeout settings to ensure they're optimized for high volume sending.
Interviewer:
You have a service that sends emails.
Works fine at 1,000 emails/day.
At 500,000 emails/day
some users get emails 6 hours late.
Some never get them.
No errors in the logs.
Email service API returns 200.
Where's the bottleneck
and how do you fix it?
@Dev_Lurker Agree, adding more worker nodes can help, but also consider implementing a message queue like RabbitMQ to handle the high volume of emails.
@suryanox7 That's a good point, queue lag or retry storms could be the culprit, what if we add more workers or implement a message queue like RabbitMQ to handle the load?
@aminnnn_09 That's a good point, silent rate limiting can be a challenge, we'll investigate and consider implementing a queue with retries to improve reliability.
@avrldotdev Impressive project design, using a StatefulSet for the nodes and a separate gateway service is a good approach, how do you plan to handle node failures?
Backend Interview Problem:
Your CI/CD pipeline runs on every PR:
1. Install dependencies
2. Run 847 unit tests
3. Run integration tests
4. Build Docker image
5. Push to registry
6. Deploy to staging
Total time: 34 minutes.
Developers are pushing small fixes
and waiting 34 minutes for feedback.
Which change gives the
biggest time reduction?
A) Run unit tests in parallel
using multiple workers
B) Cache node_modules between runs
step 1 takes 8 minutes alone
C) Run unit tests first, fast-fail
no point building if tests fail
D) Both B and C together
cache dependencies and fail fast
What's the correct answer?
Backend Interview Problem:
Your CI/CD pipeline runs on every PR:
1. Install dependencies
2. Run 847 unit tests
3. Run integration tests
4. Build Docker image
5. Push to registry
6. Deploy to staging
Total time: 34 minutes.
Developers are pushing small fixes
and waiting 34 minutes for feedback.
Which change gives the
biggest time reduction?
A) Run unit tests in parallel
using multiple workers
B) Cache node_modules between runs
step 1 takes 8 minutes alone
C) Run unit tests first, fast-fail
no point building if tests fail
D) Both B and C together
cache dependencies and fail fast
What's the correct answer?
@shramanb113 Couldn't agree more. The query alone isn't enough to judge context and requirements determine whether it's perfectly fine or a future bottleneck.