دو سؤال Senior-level مصاحبه که متخصصهای DevOps و Back-End باید بلد باشن جواب بدن!
اگه Senior-level هستید، احتمالاً میدونید مصاحبهکنندهها دنبال حفظیات نیستن…
دنبال طرز فکر، تجربه واقعی و عمق تصمیمگیری شما هستن.
برای همین تو این پست 2 تا سؤال واقعاً سینیور لِول گذاشتیم + نحوه جواب دادن + نمونه جواب انگلیسی با تکنیک STAR.
اگر مصاحبه دارید، اینا رو از دست ندید 👇
⚙️ 1) DevOps
❓ Question (English):
How do you guarantee a zero-downtime deployment for a microservices architecture when rolling out a breaking API change that affects multiple dependent services?
چطور جواب بدید؟
مصاحبهکننده دنبال اینه ببینه:
Blue/Green، Canary یا Progressive Delivery رو صحیح و اصولی استفاده میکنید
backward compatibility رو میفهمید
versioning سرویسها رو رعایت میکنید
rollback plan واقعی دارید
SLO/SLA برای ارورها و latency در نظر میگیرید
✅ Sample STAR Answer (English)
Situation:
We needed to release a breaking API change affecting five interdependent microservices with zero allowed downtime.
Task:
Deploy the change safely while ensuring a fast rollback option.
Action:
I implemented a Blue/Green deployment strategy on Kubernetes with Istio traffic shifting. All services exposed versioned endpoints (/v1 and /v2) to maintain backward compatibility. We rolled out traffic gradually (10→25→50→100%), and defined automated rollback triggers based on latency and error-rate thresholds.
Result:
The entire deployment completed with zero downtime and no customer impact. The approach became our standard for multi-service releases.
🧱 2) Back-End Engineering
❓ Question (English):
How would you design the data layer of a high-load system so that it remains horizontally scalable while still maintaining acceptable consistency guarantees?
چطور جواب بدید؟
تو جواب این موارد رو بگید:
اشاره به CAP و trade-offها
توضیح ترکیبی از sharding + caching + replication
استفاده از consistency modelهای مناسب (Read-Your-Writes، Eventual، Strong)
جداسازی OLTP و OLAP
تجربه عملی (مهمترین بخش!)
✅ Sample STAR Answer (English)
Situation:
Our analytics platform experienced severe read latency spikes during peak hours.
Task:
Redesign the data layer to scale horizontally while maintaining reasonable consistency.
Action:
I applied tenant-based sharding, added a Redis read-through cache, and separated OLTP from OLAP workloads. For consistency, I introduced a “read-your-writes” strategy for critical operations and used eventual consistency for non-critical data. I also implemented replication lag monitoring tied to automatic throttling.
Result:
Read latency improved by 60%, write throughput doubled, and the system handled 3× traffic without any degradation in user experience.
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پیشنهاد می کنم اگه به دنبال کاریابی بین المللی هستید تلگرام کیوُرک رو حتما دنبال کنید :
@keyworkir
@keyworkir
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