πŸͺ

Essential cookies keep authentication working. With your permission, we also use analytics to improve the product. Privacy Policy

DDataEngPrep.tech
Home
PricingBlog
Sign InStart Free→
Home/Questions/System Design/Architecture/Which metrics are critical to monitor?

Which metrics are critical to monitor?

System Design/Architectureeasy0.2 min read

Reviewed by Aditya Kumar Β· Last reviewed 2026-03-24

**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;...

πŸ€– 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
Part of the Data Engineering System Design Interview Preparation Hub
Explore Data Engineering System Design Hub→
Reported in Interview Loops AtClick to view company-specific questions
🏒 Moonfare Interview Hubβ†’
Interview Pro Tip

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

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.

⚑
Pro Tip

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

Related System Design/Architecture Questions

hardWhat architecture are you following in your current project, and why?FreeeasyCDC During Migration - explain approaches for real-time Change Data CaptureFreehardBriefly explain the architecture of Kafka.FreehardDescribe the data pipeline architecture you've worked with.FreehardExplain the trade-offs between batch and real-time data processing. Provide examples of when each is appropriate.Free

According to DataEngPrep.tech, this is one of the most frequently asked System Design/Architecture interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.

← Back to all questionsMore System Design/Architecture questions β†’
Topic Hubs
All Topic Hubs (12 Competencies) β†’All 1,863+ QuestionsSQL Interview QuestionsApache Spark QuestionsPySpark QuestionsPython for Data EngineersSystem Design InterviewData Modeling & WarehousingStreaming (Kafka/Flink)SQL Window FunctionsETL Pipeline Design
Company Hubs
All Company Hubs (100+ Companies) β†’AmazonGoogleMetaDatabricksSnowflakeNetflixUberStripeMicrosoftAppleGoldman SachsAWS Engineering
Academies & Guides
All Guides & ArticlesData Engineering AcademyForward Deployed AI AcademyClient Simulation StudioApache Airflow QuestionsAzure Data EngineerBehavioral & STAR MethodCloud & Distributed Tools
AI Tools & Products
Answer Analyzer (Free)AI Mock InterviewsSQL PlaygroundATS Resume AnalyzerOffline PDF Answer VaultsMembership & Pricing
Company
About & Editorial PolicyContact UsAI DisclosureDisclaimerTerms of ServicePrivacy Policy
Β© 2026 DataEngPrep.tech. All rights reserved.
AboutBlogContactDisclaimer