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1.
What is Cosmos DB and what are its core features?
Answer:
Cosmos DB Fundamentals
- 2.
Explain the different APIs provided by Cosmos DB. How do you choose the right one for your application?
Answer: - 3.
What is the data model used by Cosmos DB and how does it differ from relational databases?
Answer: - 4.
How does Cosmos DB ensure data durability?
Answer: - 5.
What is the Request Unit (RU) in Cosmos DB and how is it used?
Answer: - 6.
Can you describe the multi-model capabilities of Cosmos DB?
Answer: - 7.
Outline the types of indexing available in Cosmos DB. How does indexing affect performance?
Answer: - 8.
Discuss the ACID properties in the context of Cosmos DB transactions.
Answer:
Data Modeling and Partitioning
- 9.
What is a partition key in Cosmos DB and how is it used?
Answer: - 10.
Explain the concept of logical partitions vs physical partitions in Cosmos DB.
Answer: - 11.
What are the best practices for choosing a partition key in a Cosmos DB container?
Answer: - 12.
What considerations should be taken into account when modeling data for a Cosmos DB instance?
Answer: - 13.
How does partitioning impact the scalability and performance of a Cosmos DB application?
Answer: - 14.
How might you handle hot partitions in Cosmos DB?
Answer: - 15.
Describe some common anti-patterns in data modeling for Cosmos DB.
Answer:
Querying in Cosmos DB
- 16.
How do you perform SQL queries in Cosmos DB using the SQL API?
Answer: - 17.
Can you use LINQ to query Cosmos DB? If so, explain how.
Answer: - 18.
Explain how the Gremlin API can be used to query graph data in Cosmos DB.
Answer: - 19.
Describe how Cosmos DB’s MongoDB API differs from native MongoDB.
Answer: - 20.
Discuss the use of stored procedures, triggers, and UDFs (User-Defined Functions) in Cosmos DB.
Answer: - 21.
What is the impact of cross-partition queries on the performance of Cosmos DB?
Answer: - 22.
How can you optimize query performance in a Cosmos DB database?
Answer:
Performance Optimization
- 23.
How can you manage and optimize throughput in Cosmos DB?
Answer: - 24.
Explain the use of the indexing policy in Cosmos DB.
Answer: - 25.
Discuss the relevance of time-to-live (TTL) settings in Cosmos DB.
Answer: - 26.
What are some common performance bottlenecks in Cosmos DB and how can you address them?
Answer: - 27.
Discuss best practices for using the change feed to maintain materialized views in Cosmos DB.
Answer:
Cosmos DB Consistency Levels
- 28.
Enumerate the different consistency levels available in Cosmos DB.
Answer: - 29.
How does eventual consistency in Cosmos DB work and when would you use it?
Answer: - 30.
Explain the trade-offs between consistency, availability, and latency in Cosmos DB.
Answer: - 31.
What consistency level would you choose for a shopping cart application in Cosmos DB and why?
Answer:
Global Distribution and Multi-Region Writes
- 32.
How does Cosmos DB handle global distribution?
Answer: - 33.
Explain multi-region writes and how they affect consistency and performance.
Answer: - 34.
What are the benefits of geo-replication in Cosmos DB?
Answer: - 35.
How do you configure failover priorities for regions in Cosmos DB?
Answer:
Security and Compliance
- 36.
What security features does Cosmos DB provide to protect data?
Answer: - 37.
Describe how Cosmos DB integrates with Azure Active Directory.
Answer: - 38.
How does Cosmos DB handle data at rest and in transit encryption?
Answer: - 39.
Explain how you can secure access to Cosmos DB data using role-based access control (RBAC).
Answer:
Integration and Scalability
- 40.
How does Cosmos DB integrate with other Azure services such as Azure Functions?
Answer: - 41.
What options are available to scale out a Cosmos DB collection?
Answer: - 42.
Discuss how Cosmos DB fits into a microservices architecture.
Answer: - 43.
Can you integrate Cosmos DB with Azure Event Hubs or Azure Service Bus? If yes, how?
Answer:
Real-time Analytics and Stream Processing
- 44.
How can Cosmos DB be used for real-time analytics?
Answer: - 45.
Explain the integration options between Cosmos DB and Azure Stream Analytics.
Answer: - 46.
Discuss patterns for processing and analyzing streaming data in Cosmos DB.
Answer:
Cosmos DB SDKs and Development
- 47.
What SDKs are available for Cosmos DB and how do they cater to different languages?
Answer: - 48.
Explain how optimistic concurrency control works in Cosmos DB.
Answer: - 49.
What tools does Cosmos DB provide for local development and testing?
Answer: - 50.
Discuss best practices for managing the Cosmos DB lifecycle within a CI/CD pipeline.
Answer:
Backup, Recovery, and Monitoring
- 51.
Outline the backup and restore options available in Cosmos DB.
Answer: - 52.
What monitoring tools and metrics are important to keep an eye on for Cosmos DB performance?
Answer: - 53.
Explain the process of disaster recovery in the context of Cosmos DB.
Answer: - 54.
Can you monitor the throughput usage and performance metrics of your Cosmos DB account? If so, how?
Answer: - 55.
Describe how you would manage capacity planning for a Cosmos DB deployment.
Answer:
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