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Which metrics are critical to monitor?

System Design/Architectureeasy0.2 min readPremium

**Pipeline:** Throughput, latency, failure rate, SLA attainment. **Infra:** CPU/memory, shuffle spill, GC. **Data quality:** Null rates, schema drift, freshness. **Cost:** Compute hours, storage. **Business:** Records processed, downstream impact. **Tools:** Grafana, Datadog;...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
179
questions in System Design/Architecture
Difficulty Split
15E|6M|158H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Moonfare
Interview Pro Tip

Pro-Move: SLA + business metrics combined. Red Flag: Only infra metrics, no data quality.

Why This Question Matters

This easy-level System Design/Architecture question appears frequently in data engineering interviews at companies like Moonfare. While less common, it tests deeper understanding that distinguishes strong candidates.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
48 words

Pipeline: Throughput, latency, failure rate, SLA attainment. Infra: CPU/memory, shuffle spill, GC. Data quality: Null rates, schema drift, freshness. Cost: Compute hours, storage. Business: Records processed, downstream impact. Tools: Grafana, Datadog; PagerDuty. Why: SLOs + alerts on breach. Business metrics for prioritization. Scalability: Cardinality limits; aggregate where possible.

The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations covering performance optimization and real-world examples.

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According to DataEngPrep.tech, this is one of the most frequently asked System Design/Architecture interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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