Question 1

How do you handle expired secrets in a production environment?

Accepted Answer

**Prevention**: Rotate before expiry; automated (Secrets Manager, Vault). Alert 30 days before. **Detection**: Monitor expiry. **Update**: Propagate to consumers; gradual rollout. **Incident**: If expired causes outage—emergency rotation, deploy, verify. Never hardcode; use secret managers; test rotation in staging....

Question 2

How does resource allocation adjust when a job experiences a sudden load increase?

Accepted Answer

**Mechanisms**: (1) Auto-scale—K8s HPA, Spark dynamic allocation; (2) Queue—backlog in Kafka/SQS; (3) Burst—cloud scale; lag possible; (4) Shedding—drop low-priority. Example: Spark adds executors when backlog grows; removes when idle....

Question 3

What are the potential downsides of enabling dynamic resource allocation?

Accepted Answer

Dynamic allocation (Spark) downsides: (1) Latency—executor acquisition delay; short jobs suffer. (2) Uneven—stragglers if allocation slow. (3) Cost unpredictability—bursty in shared clusters. (4) External shuffle—may need extra service. (5) Small jobs—overhead not justified. Best: Dynamic for long, variable; static for predictable batch....

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