What are some examples of custom metrics that can be collected in AWS?
- Application latency, API response time, custom error rates
- CPU utilization of Amazon S3 buckets
- Disk space usage of Amazon SQS queues
- Network bandwidth of Amazon RDS instances
Examples of custom metrics that can be collected in AWS include application latency, API response time, and custom error rates, allowing you to monitor and optimize various aspects of your applications or services.
AWS X-Ray provides __________ for analyzing performance trends and identifying anomalies in application behavior.
- Insights
- Logs
- Metrics
- Triggers
AWS X-Ray provides insights for analyzing performance trends and identifying anomalies in application behavior, allowing developers to optimize performance and troubleshoot issues.
__________ is a key AWS service that integrates with AWS X-Ray to provide comprehensive monitoring and analysis capabilities.
- Amazon CloudWatch
- Amazon RDS
- Amazon Redshift
- Amazon S3
Amazon CloudWatch is a key AWS service that integrates with AWS X-Ray to provide comprehensive monitoring and analysis capabilities, allowing you to monitor metrics, collect log files, and set alarms.
AWS X-Ray enables __________ to understand and optimize performance across microservices architectures.
- Administrators
- Database administrators
- Developers
- Network engineers
AWS X-Ray enables developers to understand and optimize performance across microservices architectures by providing insights into request flows, latency, and dependencies.
Scenario: You are tasked with optimizing the performance of a microservices-based application. How would you use AWS X-Ray to identify and address performance issues?
- Use X-Ray to manage database connections
- Use X-Ray to monitor server CPU utilization
- Use X-Ray to provision additional resources
- Use X-Ray traces to analyze the flow of requests between microservices
Using X-Ray traces, you can analyze the flow of requests between microservices to identify and address performance issues in a microservices-based application.
Scenario: Your team is deploying a new feature that involves multiple AWS services. How can AWS X-Ray help in ensuring the smooth integration and performance of these services?
- Use X-Ray to deploy the feature automatically
- Use X-Ray to manage user authentication
- Use X-Ray to provision additional resources
- Use X-Ray to trace requests across different AWS services
AWS X-Ray can be used to trace requests across different AWS services, ensuring smooth integration and identifying any performance issues or errors during the deployment of a new feature involving multiple services.
What are some best practices for using custom metrics in AWS?
- Define meaningful metrics
- Ignore anomalies
- Monitor regularly
- Use default alarms
Best practices for using custom metrics in AWS include defining meaningful metrics that align with business objectives, regularly monitoring metrics, and investigating anomalies rather than ignoring them.
Custom metrics in AWS are often collected using __________.
- Amazon CloudWatch
- Amazon EC2
- Amazon RDS
- Amazon S3
Custom metrics in AWS are often collected using Amazon CloudWatch.
What is the purpose of error handling in AWS Lambda?
- To automatically retry failed executions
- To gracefully manage runtime errors
- To increase function execution time
- To reduce the function's memory usage
Error handling in AWS Lambda is essential to gracefully manage runtime errors, ensuring that they are properly logged and handled without crashing the application.
Which AWS service is commonly used for logging AWS Lambda function output?
- AWS CloudTrail
- AWS Config
- Amazon CloudWatch
- Amazon S3
Amazon CloudWatch is commonly used for logging AWS Lambda function output, providing monitoring and logging capabilities for AWS resources and applications.