Cloud Platform Experience Questions

Personal account of hands on experience using public cloud providers and the concrete results delivered. Candidates should describe specific services and patterns they used for compute, storage, networking, managed databases, serverless and eventing, and explain their role in architecture decisions, deployments, automation and infrastructure as code practices, continuous integration and continuous delivery pipelines, container orchestration, scaling and performance tuning, monitoring and incident response, and cost management. Interviewees should quantify outcomes when possible with metrics such as latency reduction, cost savings, availability improvements or deployment frequency and note any formal training or certifications. This topic evaluates depth of practical experience, ownership, and the ability to operate and improve cloud systems in production.

MediumSystem Design

37 practiced

Given a terabyte-scale dataset arriving as daily CSV files into cloud object storage, design an ETL pipeline to validate, transform, and load data into a managed analytics store for near-real-time analytics. Specify services for ingestion, compute choice (serverless vs cluster), orchestration, schema evolution handling, idempotency, metadata capture, and retry behavior.

HardTechnical

34 practiced

You discover that a production model has been trained with features that leaked future information, inflating offline metrics. Outline an incident response plan: immediate mitigation (rollback or disable), scope analysis to identify affected models and data, remediation and retraining plan, how to estimate business impact and rollback cost, and how to update pipelines and tests to detect similar leakage in the future.

EasyTechnical

36 practiced

What is Infrastructure as Code (IaC) and why is it important for reproducible ML deployments? As a data scientist, describe how IaC helped your team (for example Terraform modules or CloudFormation stacks), and briefly compare Terraform to a provider-native template language. Give one concrete IaC pattern you used such as modules, remote state, or state locking.

MediumTechnical

34 practiced

You deploy a new model through your CI/CD pipeline and start seeing increased error rates and latency. Describe a practical rollback strategy that minimizes customer impact and data loss. Include detection mechanisms, automated rollback triggers, safe database migration rollback approaches, blue/green or canary strategies, and postmortem practices.

HardTechnical

43 practiced

Design a low-latency real-time feature store for high-cardinality keys with a sub-10ms lookup SLA. Compare using an in-memory cache (for example Redis), a low-latency key-value store (for example DynamoDB/Bigtable), and a hybrid approach. Discuss cost, consistency, eviction policies for hot keys, handling cold-starts, fallback strategies, and how to keep the cache warm for hot traffic.

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