Distributed System and Microservices Security Questions

Focuses on security considerations for distributed systems, APIs, containers, and microservice ecosystems. Includes authentication and authorization approaches for APIs and service to service communication, token models and OAuth and JSON web tokens, API gateway and rate limiting strategies, secrets management and secure configuration, network segmentation and service mesh security, container and runtime image hardening, Kubernetes and orchestration security, vulnerability scanning and patch management, secure logging and tracing practices, dependency supply chain security, and compliance and governance implications. Emphasizes how security control implementation differs between monoliths and distributed architectures.

EasyTechnical

97 practiced

From a data engineer's perspective, explain how implementing security controls differs between a monolithic data platform and a microservices-based distributed data architecture. Discuss implications for authentication, secrets management, network boundaries, operational overhead, and failure modes.

MediumSystem Design

85 practiced

Design an approach for automated alerting and remediation when image vulnerability severity thresholds are exceeded for images used in production ETL pipelines. Include classification of severities, who gets notified, automated quarantines, and exception handling.

EasyTechnical

100 practiced

Explain 'least privilege' in the context of cloud IAM for data engineering workloads. Provide concrete examples of IAM policies for a data ingestion service that needs to write to S3, publish to a message queue, and read a secrets store. Include suggestions to reduce blast radius.

EasySystem Design

86 practiced

You must design an API gateway policy to protect a critical data ingestion API that receives 10k requests/minute. List the specific controls you would configure at the gateway (authentication, authorization, rate-limiting, throttling, IP allowlists, request validation) and explain why each is necessary in a distributed data platform.

MediumTechnical

97 practiced

As a data engineering manager, describe how you would build a security culture in the team responsible for data pipelines and infrastructure. Include hiring practices, training, onboarding checklists, code review standards, and incentives that encourage secure-by-default development.

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