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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.

HardSystem Design
0 practiced
Describe how to implement and operate a centralized secret access audit system so that every access to production secrets (e.g., database passwords, encryption keys) by services or humans is recorded, searchable, and linked to an identity for forensic analysis.
EasyTechnical
0 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.
MediumTechnical
0 practiced
Discuss how to secure backups and snapshots for analytic stores so that an attacker who gains access to storage cannot trivially obtain sensitive data. Cover encryption, key separation, access control, and verification of backup integrity.
HardSystem Design
0 practiced
You are asked to implement network egress restriction for ETL jobs to prevent phantom outbound connections. Describe how to implement egress controls on Kubernetes nodes and cloud VMs, how to whitelist service endpoints, and how to handle dynamic third-party endpoints used by some jobs.
MediumSystem Design
0 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.

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