__________ is a common use case for custom event sources, allowing Lambda functions to respond to specific application events.
- Asynchronous processing
- Authentication
- Load balancing
- Synchronous processing
Asynchronous processing is a common use case for custom event sources in AWS Lambda, allowing functions to respond to specific application events.
AWS Lambda provides __________ for integrating with custom event sources, ensuring scalability and reliability.
- API gateways
- Backup services
- Event source mappings
- Resource pools
Event source mappings in AWS Lambda allow you to connect functions with event sources such as Amazon S3, Amazon SQS, and Amazon Kinesis, ensuring scalability and reliability.
Implementing custom event sources may require __________ to manage event routing and processing efficiently.
- Encryption keys
- Event routers
- Load balancers
- Message brokers
Message brokers such as Amazon SQS or Apache Kafka may be used to manage event routing and processing efficiently when implementing custom event sources in AWS Lambda.
What are CloudWatch Metrics used for?
- Deploying applications
- Managing security groups
- Monitoring AWS resources and applications
- Storing log data
CloudWatch Metrics are used for monitoring AWS resources and applications by collecting and tracking data over time, enabling you to analyze performance and detect anomalies.
How are CloudWatch Metrics different from CloudWatch Logs?
- Metrics are stored in S3, while logs are stored in DynamoDB
- Metrics are used for monitoring, while logs are used for security
- Metrics store text-based data, while logs store numerical data
- Metrics track performance data over time, while logs capture real-time events and information
CloudWatch Metrics track performance data over time, while CloudWatch Logs capture real-time events and information, serving different purposes in monitoring and troubleshooting.
What are some common AWS services that automatically publish CloudWatch Metrics?
- AWS Lambda, Amazon SQS, Amazon DynamoDB
- Amazon CloudFront, AWS IAM, AWS Elastic Beanstalk
- Amazon EC2, Amazon RDS, Amazon S3
- Amazon Redshift, Amazon EKS, AWS Glue
Amazon EC2, Amazon RDS, and Amazon S3 are among the AWS services that automatically publish CloudWatch Metrics, providing insights into resource utilization and performance.
How do you configure custom event sources to trigger AWS Lambda functions?
- By configuring IAM roles
- By creating event source mappings
- By directly invoking the function
- By setting up AWS CloudWatch alarms
Custom event sources are configured to trigger AWS Lambda functions by creating event source mappings, which link a specific event source to a Lambda function, allowing it to trigger in response to events from that source.
How do you handle errors and retries when using custom event sources with AWS Lambda?
- Halt execution and alert administrator
- Ignore errors and proceed with execution
- Implement error handling and exponential backoff
- Retry immediately on failure
When using custom event sources with AWS Lambda, it's best practice to implement error handling mechanisms such as exponential backoff to manage retries and handle errors gracefully.
What are the best practices for monitoring and logging custom event sources in AWS Lambda?
- Disable logging to reduce overhead
- Manual logging in function code
- Use third-party logging services
- Utilize CloudWatch Metrics and Logs
Best practices for monitoring and logging custom event sources in AWS Lambda include utilizing CloudWatch Metrics and Logs to track function invocations, errors, and performance metrics.
CloudWatch Alarms can be configured to trigger actions based on defined __________ thresholds.
- Event
- Instance
- Metric
- Region
CloudWatch Alarms can be configured to trigger actions based on defined metric thresholds, allowing you to respond to performance or availability issues.