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Managed Databases and Data Services Questions

Covers choosing and operating managed database offerings and complementary cloud data services. Candidates should understand managed relational database services such as Amazon Relational Database Service for MySQL PostgreSQL MariaDB Microsoft SQL Server and Oracle, and NoSQL document and key value stores such as Amazon DynamoDB Azure Cosmos Database Google Cloud Firestore and Datastore. Expect to explain when to choose relational versus NoSQL based on data shape query complexity transactional guarantees including atomicity consistency isolation and durability read and write patterns latency and scalability requirements. Understand scaling techniques including vertical scaling read replicas for read scaling horizontal scaling via partitioning or sharding and multi region replication and failover strategies. Be familiar with backup and restore approaches including snapshots point in time recovery cross region replication and disaster recovery planning. Know consistency models and trade offs such as strong eventual and causal consistency, and understand provisioned capacity versus serverless autoscaling models and their cost and operational implications. Candidates should also be able to discuss performance tuning topics such as indexing query optimization caching connection pooling storage and input output optimization monitoring and alerting, as well as security and compliance considerations including encryption access control and network isolation. Finally be prepared to recommend a database solution given workload characteristics such as data size read to write ratio latency targets and operational constraints.

HardTechnical
96 practiced
Design an online schema migration strategy to add a NOT NULL column with a default to a 5 TB PostgreSQL table on Amazon RDS that contains billions of rows. Compare approaches: native ALTER TABLE, logical replication to a shadow table, backfill jobs in chunks, and tools like gh-ost or pt-online-schema-change. Provide a step-by-step plan to implement this with minimal locks and downtime and a rollback approach.
HardSystem Design
67 practiced
Design a multi-region architecture to support a global service with OLTP requirements (p99 latency < 100ms for reads) and near-real-time analytics. Requirements: 200M users, peaks of 2k writes/sec, analytics updates within 30 seconds, GDPR constraints for EU-resident data. Propose managed products for OLTP and analytics, replication and CDC strategy, cross-region considerations, and how you'd ensure compliance for data residency.
HardTechnical
85 practiced
You want to reduce monthly costs by moving from provisioned RDS instances to a serverless model (Aurora Serverless v2) or DynamoDB on-demand. Create a migration and validation plan that addresses connection pooling differences, expected cold-start behaviors, schema or data-model changes, pricing model validation, performance testing, and rollback strategy.
HardTechnical
73 practiced
Design a secure key-management and encryption strategy for managed databases: cover KMS usage (key hierarchy, envelope encryption), cross-account key access, rotation policies, audit logging, encryption of snapshots and replicas, and how SREs can test and validate key rotation without service interruption. Also mention compliance considerations for PCI or SOC2.
MediumSystem Design
68 practiced
Design a multi-region failover strategy for a managed relational database with primary in us-east-1 and DR in eu-west-1. Compare and contrast approaches: cross-region read replicas and promotion, logical replication with custom tooling, and managed global DB products (Aurora Global DB, Cloud Spanner). Describe automated failover steps, DNS considerations, replication lag handling, and testing strategies.

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