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Top 30 Datadog Interview Questions with Answers

1. What is Datadog?

a. A cloud-based infrastructure monitoring and analytics platform
b. An open-source database
c. A programming language
d. A web development framework
Answer: a

2. Which programming languages does Datadog support for integrations?

a. Python, Java, Ruby, Go, Node.js
b. C++, C#, PHP, Swift
c. Perl, Rust, Scala, Kotlin
d. Objective-C, TypeScript, Pascal
Answer: a

3. What types of data can Datadog collect and monitor?

a. Metrics, traces, logs
b. Images, videos, audio
c. HTML, CSS, JavaScript
d. Text files, PDFs, spreadsheets
Answer: a

4. How does Datadog handle high-frequency metrics?

a. Aggregation and sampling
b. Ignoring high-frequency metrics
c. Deleting high-frequency metrics
d. Storing all high-frequency metrics
Answer: a

5. What is the purpose of Datadog's anomaly detection feature?

a. Identifying unusual patterns in metrics
b. Generating random data for testing
c. Predicting future metrics accurately
d. Calculating averages of metrics
Answer: a

6. What is a metric in Datadog?

a. A data point collected by Datadog
b. A type of log
c. A data storage format
d. A programming construct
Answer: a

7. What is the significance of a Datadog dashboard?

a. Visualizing metrics and monitoring data
b. Running background processes
c. Storing backup data
d. Performing security checks
Answer: a

8. How can you create a custom metric in Datadog?

a. Use the Datadog Agent to send the metric
b. Write a Python script to generate the metric
c. Modify the Datadog source code
d. Use a third-party plugin
Answer: a

9. What are tags in Datadog used for?

a. Adding metadata to metrics for better organization and filtering
b. Displaying ads on the Datadog interface
c. Blocking access to certain metrics
d. Encrypting metric data
Answer: a

10. What is a Datadog monitor used for?

a. Alerting based on predefined conditions
b. Viewing logs in real-time
c. Creating graphs for visual representation
d. Analyzing historical trends
Answer: a

11. Which integration is used to monitor AWS services in Datadog?

a. AWS CloudWatch integration
b. AWS Lambda integration
c. AWS RDS integration
d. AWS ECS integration
Answer: a

12. Which integration is used to monitor Kubernetes clusters in Datadog?

a. Kubernetes integration
b. KubeMonitor integration
c. K8sWatch integration
d. ClusterMonitor integration
Answer: a

13. Which integration is used to monitor Docker containers in Datadog?

a. Docker integration
b. ContainerMonitor integration
c. DockerWatch integration
d. ContainerInspector integration
Answer: a

14. Which integration is used to monitor PostgreSQL databases in Datadog?

a. PostgreSQL integration
b. PostgresMonitor integration
c. PostgresWatch integration
d. DatabaseMonitor integration
Answer: a

15. What is the purpose of Datadog's PagerDuty integration?

a. Alerting and incident management
b. Code deployment
c. Generating reports
d. Load testing
Answer: a

16. What is Datadog Logs?

a. A log management and analytics tool
b. A messaging platform
c. A file storage system
d. A web hosting service
Answer: a

17. Which protocol is commonly used to send logs to Datadog Logs?

a. syslog
c. FTP
Answer: a

18. How can you enrich logs in Datadog Logs?

a. Using parsing rules and grok patterns
b. Manually editing each log entry
c. Ignoring log enrichment
d. Using encryption techniques
Answer: a

19. What is a structured log in Datadog Logs?

a. A log message with a defined format, such as JSON or key-value pairs
b. A log message with unstructured text
c. A log message with ASCII art
d. A log message with encrypted content
Answer: a

20. What is the purpose of log retention in Datadog Logs?

a. Determining how long logs should be stored
b. Filtering logs based on specific criteria
c. Enabling real-time log streaming
d. Encrypting log data
Answer: a

21. What is Datadog APM used for?

a. Monitoring the performance of applications
b. Managing network infrastructure
c. Creating dashboards
d. Analyzing log data
Answer: a

22. Which programming languages are supported for APM in Datadog?

a. Multiple languages including Python, Java, Ruby, Go, and Node.js
b. Only Python and Java
c. Only Ruby and Go
d. Only C++ and C#
Answer: a

23. What is distributed tracing in Datadog APM?

a. Tracking requests across multiple services
b. Tracing requests within a single service
c. Tracking database queries only
d. Tracing requests based on IP addresses
Answer: a

24. What is a span in distributed tracing in Datadog APM?

a. A unit of work in an application, representing a specific operation
b. A unit of time
c. A database query
d. A log entry
Answer: a

25. How does Datadog APM help in identifying bottlenecks in an application?

a. By analyzing the traces and identifying slow operations
b. By deleting unnecessary traces
c. By generating random traces for comparison
d. By analyzing log data
Answer: a

26. What is Datadog Security Monitoring used for?

a. Detecting and investigating security threats
b. Optimizing application performance
c. Managing infrastructure
d. Generating reports
Answer: a

27. What is the purpose of Datadog Security Monitoring rules?

a. To define conditions that trigger alerts for security events
b. To define password policies
c. To define access control rules
d. To define encryption rules
Answer: a

28. Which AWS service can be integrated with Datadog Security Monitoring for threat detection?

a. AWS GuardDuty
c. AWS CloudTrail
d. AWS Key Management Service (KMS)
Answer: a

29. What is anomaly detection in Datadog Security Monitoring?

a. Identifying abnormal patterns in security-related metrics
b. Generating random security data for testing
c. Predicting future security incidents
d. Calculating averages of security metrics
Answer: a

30. What is a security detection rule in Datadog Security Monitoring?

a. A rule that defines conditions for detecting security events
b. A rule that defines user access permissions
c. A rule that defines log retention policies
d. A rule that defines encryption algorithms
Answer: a

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